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Sample records for neuromorphic vision systems

  1. Neuromorphic vision sensors and preprocessors in system applications

    Science.gov (United States)

    Kramer, Joerg; Indiveri, Giacomo

    1998-09-01

    A partial review of neuromorphic vision sensors that are suitable for use in autonomous systems is presented. Interfaces are being developed to multiplex the high- dimensional output signals of arrays of such sensors and to communicate them in standard formats to off-chip devices for higher-level processing, actuation, storage and display. Alternatively, on-chip processing stages may be implemented to extract sparse image parameters, thereby obviating the need for multiplexing. Autonomous robots are used to test neuromorphic vision chips in real-world environments and to explore the possibilities of data fusion from different sensing modalities. Examples of autonomous mobile systems that use neuromorphic vision chips for line tracking and optical flow matching are described.

  2. Neuromorphic VLSI vision system for real-time texture segregation.

    Science.gov (United States)

    Shimonomura, Kazuhiro; Yagi, Tetsuya

    2008-10-01

    The visual system of the brain can perceive an external scene in real-time with extremely low power dissipation, although the response speed of an individual neuron is considerably lower than that of semiconductor devices. The neurons in the visual pathway generate their receptive fields using a parallel and hierarchical architecture. This architecture of the visual cortex is interesting and important for designing a novel perception system from an engineering perspective. The aim of this study is to develop a vision system hardware, which is designed inspired by a hierarchical visual processing in V1, for real time texture segregation. The system consists of a silicon retina, orientation chip, and field programmable gate array (FPGA) circuit. The silicon retina emulates the neural circuits of the vertebrate retina and exhibits a Laplacian-Gaussian-like receptive field. The orientation chip selectively aggregates multiple pixels of the silicon retina in order to produce Gabor-like receptive fields that are tuned to various orientations by mimicking the feed-forward model proposed by Hubel and Wiesel. The FPGA circuit receives the output of the orientation chip and computes the responses of the complex cells. Using this system, the neural images of simple cells were computed in real-time for various orientations and spatial frequencies. Using the orientation-selective outputs obtained from the multi-chip system, a real-time texture segregation was conducted based on a computational model inspired by psychophysics and neurophysiology. The texture image was filtered by the two orthogonally oriented receptive fields of the multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of FPGA. The present system is also useful for the investigation of the functions of the higher-order cells that can be obtained by combining the simple and complex cells.

  3. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

    Science.gov (United States)

    Indiveri, Giacomo

    2008-09-03

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  4. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    Directory of Open Access Journals (Sweden)

    Giacomo Indiveri

    2008-09-01

    Full Text Available Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  5. Neuromorphic sensory systems.

    Science.gov (United States)

    Liu, Shih-Chii; Delbruck, Tobi

    2010-06-01

    Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

  6. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    OpenAIRE

    Giacomo Indiveri

    2008-01-01

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computation...

  7. Towards a neuromorphic vestibular system.

    Science.gov (United States)

    Corradi, Federico; Zambrano, Davide; Raglianti, Marco; Passetti, Giovanni; Laschi, Cecilia; Indiveri, Giacomo

    2014-10-01

    The vestibular system plays a crucial role in the sense of balance and spatial orientation in mammals. It is a sensory system that detects both rotational and translational motion of the head, via its semicircular canals and otoliths respectively. In this work, we propose a real-time hardware model of an artificial vestibular system, implemented using a custom neuromorphic Very Large Scale Integration (VLSI) multi-neuron chip interfaced to a commercial Inertial Measurement Unit (IMU). The artificial vestibular system is realized with spiking neurons that reproduce the responses of biological hair cells present in the real semicircular canals and otholitic organs. We demonstrate the real-time performance of the hybrid analog-digital system and characterize its response properties, presenting measurements of a successful encoding of angular velocities as well as linear accelerations. As an application, we realized a novel implementation of a recurrent integrator network capable of keeping track of the current angular position. The experimental results provided validate the hardware implementation via comparisons with a detailed computational neuroscience model. In addition to being an ideal tool for developing bio-inspired robotic technologies, this work provides a basis for developing a complete low-power neuromorphic vestibular system which integrates the hardware model of the neural signal processing pathway described with custom bio-mimetic gyroscopic sensors, exploiting neuromorphic principles in both mechanical and electronic aspects.

  8. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    Science.gov (United States)

    Belbachir, A. N.; Hofstätter, M.; Litzenberger, M.; Schön, P.

    2009-10-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail.

  9. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    International Nuclear Information System (INIS)

    Belbachir, A N; Hofstätter, M; Litzenberger, M; Schön, P

    2009-01-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail

  10. Network-driven design principles for neuromorphic systems

    OpenAIRE

    Partzsch, Johannes; Sch?ffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures i...

  11. A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors.

    Science.gov (United States)

    Vanarse, Anup; Osseiran, Adam; Rassau, Alexander

    2016-01-01

    Conventional vision, auditory, and olfactory sensors generate large volumes of redundant data and as a result tend to consume excessive power. To address these shortcomings, neuromorphic sensors have been developed. These sensors mimic the neuro-biological architecture of sensory organs using aVLSI (analog Very Large Scale Integration) and generate asynchronous spiking output that represents sensing information in ways that are similar to neural signals. This allows for much lower power consumption due to an ability to extract useful sensory information from sparse captured data. The foundation for research in neuromorphic sensors was laid more than two decades ago, but recent developments in understanding of biological sensing and advanced electronics, have stimulated research on sophisticated neuromorphic sensors that provide numerous advantages over conventional sensors. In this paper, we review the current state-of-the-art in neuromorphic implementation of vision, auditory, and olfactory sensors and identify key contributions across these fields. Bringing together these key contributions we suggest a future research direction for further development of the neuromorphic sensing field.

  12. Neuromorphic cognitive systems a learning and memory centered approach

    CERN Document Server

    Yu, Qiang; Hu, Jun; Tan Chen, Kay

    2017-01-01

    This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromo...

  13. A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor

    OpenAIRE

    Blum, Hermann; Dietmüller, Alexander; Milde, Moritz; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

    2017-01-01

    Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low energy consumption and low response latency, which can be useful in robotic applications that require compact and low power embedded computing resources. However, these neuromorphic circuits still face significant limitations that make their usage challenging: these include low precision, variability of components, sensitivity to noise and temperature drifts, as well as the currently limited number of neuron...

  14. Systematic configuration and automatic tuning of neuromorphic systems

    OpenAIRE

    Sheik Sadique; Stefanini Fabio; Neftci Emre; Chicca Elisabetta; Indiveri Giacomo

    2011-01-01

    In the past recent years several research groups have proposed neuromorphic Very Large Scale Integration (VLSI) devices that implement event-based sensors or biophysically realistic networks of spiking neurons. It has been argued that these devices can be used to build event-based systems, for solving real-world applications in real-time, with efficiencies and robustness that cannot be achieved with conventional computing technologies. In order to implement complex event-based neuromorphic sy...

  15. Network-driven design principles for neuromorphic systems

    Directory of Open Access Journals (Sweden)

    Johannes ePartzsch

    2015-10-01

    Full Text Available Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  16. Network-driven design principles for neuromorphic systems.

    Science.gov (United States)

    Partzsch, Johannes; Schüffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  17. Finding a Roadmap to achieve Large Neuromorphic Hardware Systems

    Directory of Open Access Journals (Sweden)

    Jennifer eHasler

    2013-09-01

    Full Text Available Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are meeting hard physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Towards this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.

  18. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

    Directory of Open Access Journals (Sweden)

    Fabio eStefanini

    2014-08-01

    Full Text Available Neuromorphic hardware offers an electronic substrate for the realization of asynchronousevent-based sensory-motor systems and large-scale spiking neural network architectures. Inorder to characterize these systems, configure them, and carry out modeling experiments, it isoften necessary to interface them to workstations. The software used for this purpose typicallyconsists of a large monolithic block of code highly specific to the hardware setup used. While thisapproach can lead to highly integrated hardware/software systems, it hampers the developmentof modular and neuromorphic infrastructures. To alleviate this problem, we propose PyNCS,an open-source front-end for the definition of neural network models that is interfaced to thehardware through a set of Python Application Programming Interfaces (APIs. The designof PyNCS promotes modularity, portability and expandability and separates implementationfrom hardware description. The high-level front-end that comes with PyNCS includes tools todefine neural network models as well as to create, monitor and analyze spiking data. Here wereport the design philosophy behind the PyNCS framework and describe its implementation.We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carryingout a cognitive decision-making task involving state-dependent computation. PyNCS, alreadyapplicable to a wide range of existing spike-based neuromorphic setups, will accelerate thedevelopment of hybrid software/hardware neuromorphic systems, thanks to its code flexibility.The code developed is open-source and available online at https://github.com/inincs/pyNCS.

  19. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.

    Science.gov (United States)

    Stefanini, Fabio; Neftci, Emre O; Sheik, Sadique; Indiveri, Giacomo

    2014-01-01

    Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS.

  20. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

    Science.gov (United States)

    Stefanini, Fabio; Neftci, Emre O.; Sheik, Sadique; Indiveri, Giacomo

    2014-01-01

    Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS. PMID:25232314

  1. Neuromorphic elements and systems as the basis for the physical implementation of artificial intelligence technologies

    Science.gov (United States)

    Demin, V. A.; Emelyanov, A. V.; Lapkin, D. A.; Erokhin, V. V.; Kashkarov, P. K.; Kovalchuk, M. V.

    2016-11-01

    The instrumental realization of neuromorphic systems may form the basis of a radically new social and economic setup, redistributing roles between humans and complex technical aggregates. The basic elements of any neuromorphic system are neurons and synapses. New memristive elements based on both organic (polymer) and inorganic materials have been formed, and the possibilities of instrumental implementation of very simple neuromorphic systems with different architectures on the basis of these elements have been demonstrated.

  2. Neuromorphic adaptive plastic scalable electronics: analog learning systems.

    Science.gov (United States)

    Srinivasa, Narayan; Cruz-Albrecht, Jose

    2012-01-01

    Decades of research to build programmable intelligent machines have demonstrated limited utility in complex, real-world environments. Comparing their performance with biological systems, these machines are less efficient by a factor of 1 million1 billion in complex, real-world environments. The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program is a multifaceted Defense Advanced Research Projects Agency (DARPA) project that seeks to break the programmable machine paradigm and define a new path for creating useful, intelligent machines. Since real-world systems exhibit infinite combinatorial complexity, electronic neuromorphic machine technology would be preferable in a host of applications, but useful and practical implementations still do not exist. HRL Laboratories LLC has embarked on addressing these challenges, and, in this article, we provide an overview of our project and progress made thus far.

  3. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  4. Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable

    Energy Technology Data Exchange (ETDEWEB)

    Schuller, Ivan K. [Univ. of California, San Diego, CA (United States); Stevens, Rick [Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States); Pino, Robinson [Dept. of Energy (DOE) Office of Science, Washington, DC (United States); Pechan, Michael [Dept. of Energy (DOE) Office of Science, Washington, DC (United States)

    2015-10-29

    Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.

  5. Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

    Science.gov (United States)

    Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

    2015-01-01

    This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

  6. An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

    Directory of Open Access Journals (Sweden)

    Anup Vanarse

    2017-11-01

    Full Text Available The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses.

  7. Understanding a Deep Learning Technique through a Neuromorphic System a Case Study with SpiNNaker Neuromorphic Platform

    Directory of Open Access Journals (Sweden)

    Sugiarto Indar

    2018-01-01

    Full Text Available Deep learning (DL has been considered as a breakthrough technique in the field of artificial intelligence and machine learning. Conceptually, it relies on a many-layer network that exhibits a hierarchically non-linear processing capability. Some DL architectures such as deep neural networks, deep belief networks and recurrent neural networks have been developed and applied to many fields with incredible results, even comparable to human intelligence. However, many researchers are still sceptical about its true capability: can the intelligence demonstrated by deep learning technique be applied for general tasks? This question motivates the emergence of another research discipline: neuromorphic computing (NC. In NC, researchers try to identify the most fundamental ingredients that construct intelligence behaviour produced by the brain itself. To achieve this, neuromorphic systems are developed to mimic the brain functionality down to cellular level. In this paper, a neuromorphic platform called SpiNNaker is described and evaluated in order to understand its potential use as a platform for a deep learning approach. This paper is a literature review that contains comparative study on algorithms that have been implemented in SpiNNaker.

  8. Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

    Directory of Open Access Journals (Sweden)

    Mantas Mikaitis

    2018-02-01

    Full Text Available SpiNNaker is a digital neuromorphic architecture, designed specifically for the low power simulation of large-scale spiking neural networks at speeds close to biological real-time. Unlike other neuromorphic systems, SpiNNaker allows users to develop their own neuron and synapse models as well as specify arbitrary connectivity. As a result SpiNNaker has proved to be a powerful tool for studying different neuron models as well as synaptic plasticity—believed to be one of the main mechanisms behind learning and memory in the brain. A number of Spike-Timing-Dependent-Plasticity(STDP rules have already been implemented on SpiNNaker and have been shown to be capable of solving various learning tasks in real-time. However, while STDP is an important biological theory of learning, it is a form of Hebbian or unsupervised learning and therefore does not explain behaviors that depend on feedback from the environment. Instead, learning rules based on neuromodulated STDP (three-factor learning rules have been shown to be capable of solving reinforcement learning tasks in a biologically plausible manner. In this paper we demonstrate for the first time how a model of three-factor STDP, with the third-factor representing spikes from dopaminergic neurons, can be implemented on the SpiNNaker neuromorphic system. Using this learning rule we first show how reward and punishment signals can be delivered to a single synapse before going on to demonstrate it in a larger network which solves the credit assignment problem in a Pavlovian conditioning experiment. Because of its extra complexity, we find that our three-factor learning rule requires approximately 2× as much processing time as the existing SpiNNaker STDP learning rules. However, we show that it is still possible to run our Pavlovian conditioning model with up to 1 × 104 neurons in real-time, opening up new research opportunities for modeling behavioral learning on SpiNNaker.

  9. Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

    Science.gov (United States)

    Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

    2017-08-01

    Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a

  10. Neuromorphic olfaction neuromorphic olfaction

    CERN Document Server

    Persaud, Krishna C; Marco, Santiago

    2016-01-01

    Engineering Aspects of Olfaction; Krishna C. PersaudStudy of the Coding Efficiency of Populations of OlfactoryReceptor Neurons and Olfactory Glomeruli; Agustín Gutiérrez-Gálvez and Santiago MarcoMimicking Biological Olfaction with Very Large ChemicalArrays; Mara Bernabei, Romeo Beccherelli, Emiliano Zampetti,Simone Pantalei, and Krishna C. PersaudThe Synthetic Moth: A Neuromorphic Approach towardArtificial Olfaction in Robots; Vasiliki Vouloutsi, Lucas L. Lopez-Serrano,Zenon Mathews, Alex Escuredo Chimeno, Andrey Ziyatdinov, Alexandre Perera i Lluna, Sergi Bermúdez i Badia, and Paul F. M. J. Verschure Reactive and Cognitive Search Strategies for Olfactory Robots; Dominique Martinez and Eduardo Martin MoraudPerformance of a Computational Model of the MammalianOlfactory System; Simon Benjaminsson, Pawel Herman, and Anders LansnerIndex.

  11. Coupling an aVLSI neuromorphic vision chip to a neurotrophic model of synaptic plasticity: the development of topography.

    Science.gov (United States)

    Elliott, Terry; Kramer, Jörg

    2002-10-01

    We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target neurons. We find that the plasticity model can indeed drive topographic refinement in the presence of afferent activity patterns generated by a real-world device. We examine the resilience of the developing system to the presence of high levels of noise by adjusting the spontaneous firing rate of the silicon neurons.

  12. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system

    Directory of Open Access Journals (Sweden)

    Daniel Brüderle

    2009-06-01

    Full Text Available Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  13. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.

    Science.gov (United States)

    Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

    2009-01-01

    Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  14. Recent Advances on Neuromorphic Systems Using Phase-Change Materials

    Science.gov (United States)

    Wang, Lei; Lu, Shu-Ren; Wen, Jing

    2017-05-01

    Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.

  15. Recent Advances on Neuromorphic Systems Using Phase-Change Materials.

    Science.gov (United States)

    Wang, Lei; Lu, Shu-Ren; Wen, Jing

    2017-12-01

    Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.

  16. A Neuromorphic Approach for Tracking using Dynamic Neural Fields on a Programmable Vision-chip

    OpenAIRE

    Martel Julien N.P.; Sandamirskaya Yulia

    2016-01-01

    In artificial vision applications, such as tracking, a large amount of data captured by sensors is transferred to processors to extract information relevant for the task at hand. Smart vision sensors offer a means to reduce the computational burden of visual processing pipelines by placing more processing capabilities next to the sensor. In this work, we use a vision-chip in which a small processor with memory is located next to each photosensitive element. The architecture of this device is ...

  17. Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

    Directory of Open Access Journals (Sweden)

    Emre eNeftci

    2014-01-01

    Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  18. Event-driven contrastive divergence for spiking neuromorphic systems.

    Science.gov (United States)

    Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2013-01-01

    Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  19. Energy-efficient neuromorphic classifiers

    OpenAIRE

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2015-01-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. Neuromorphic engineering promises extremely low energy consumptions, comparable to those of the nervous system. However, until now the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, rendering el...

  20. Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

    OpenAIRE

    Massimiliano Giulioni; Federico Corradi; Vittorio Dante; Paolo del Giudice

    2015-01-01

    Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction compri...

  1. Emergent auditory feature tuning in a real-time neuromorphic VLSI system

    Directory of Open Access Journals (Sweden)

    Sadique eSheik

    2012-02-01

    Full Text Available Many sounds of ecological importance, such as communication calls, are characterised by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamocortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP, which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectrotemporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step towards the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  2. Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

    Science.gov (United States)

    Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

    2012-01-01

    Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  3. A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

    Science.gov (United States)

    Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

    2014-03-01

    This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

  4. Low Vision Enhancement System

    Science.gov (United States)

    1995-01-01

    NASA's Technology Transfer Office at Stennis Space Center worked with the Johns Hopkins Wilmer Eye Institute in Baltimore, Md., to incorporate NASA software originally developed by NASA to process satellite images into the Low Vision Enhancement System (LVES). The LVES, referred to as 'ELVIS' by its users, is a portable image processing system that could make it possible to improve a person's vision by enhancing and altering images to compensate for impaired eyesight. The system consists of two orientation cameras, a zoom camera, and a video projection system. The headset and hand-held control weigh about two pounds each. Pictured is Jacob Webb, the first Mississippian to use the LVES.

  5. A neuromorphic VLSI device for implementing 2-D selective attention systems.

    Science.gov (United States)

    Indiveri, G

    2001-01-01

    Selective attention is a mechanism used to sequentially select and process salient subregions of the input space, while suppressing inputs arriving from nonsalient regions. By processing small amounts of sensory information in a serial fashion, rather than attempting to process all the sensory data in parallel, this mechanism overcomes the problem of flooding limited processing capacity systems with sensory inputs. It is found in many biological systems and can be a useful engineering tool for developing artificial systems that need to process in real-time sensory data. In this paper we present a neuromorphic hardware model of a selective attention mechanism implemented on a very large scale integration (VLSI) chip, using analog circuits. The chip makes use of a spike-based representation for receiving input signals, transmitting output signals and for shifting the selection of the attended input stimulus over time. It can be interfaced to neuromorphic sensors and actuators, for implementing multichip selective attention systems. We describe the characteristics of the circuits used in the architecture and present experimental data measured from the system.

  6. [Quality system Vision 2000].

    Science.gov (United States)

    Pasini, Evasio; Pitocchi, Oreste; de Luca, Italo; Ferrari, Roberto

    2002-12-01

    A recent document of the Italian Ministry of Health points out that all structures which provide services to the National Health System should implement a Quality System according to the ISO 9000 standards. Vision 2000 is the new version of the ISO standard. Vision 2000 is less bureaucratic than the old version. The specific requests of the Vision 2000 are: a) to identify, to monitor and to analyze the processes of the structure, b) to measure the results of the processes so as to ensure that they are effective, d) to implement actions necessary to achieve the planned results and the continual improvement of these processes, e) to identify customer requests and to measure customer satisfaction. Specific attention should be also dedicated to the competence and training of the personnel involved in the processes. The principles of the Vision 2000 agree with the principles of total quality management. The present article illustrates the Vision 2000 standard and provides practical examples of the implementation of this standard in cardiological departments.

  7. Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

    Science.gov (United States)

    Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

    2015-10-01

    Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

  8. Implementation of neuromorphic systems: from discrete components to analog VLSI chips (testing and communication issues).

    Science.gov (United States)

    Dante, V; Del Giudice, P; Mattia, M

    2001-01-01

    We review a series of implementations of electronic devices aiming at imitating to some extent structure and function of simple neural systems, with particular emphasis on communication issues. We first provide a short overview of general features of such "neuromorphic" devices and the implications of setting up "tests" for them. We then review the developments directly related to our work at the Istituto Superiore di Sanità (ISS): a pilot electronic neural network implementing a simple classifier, autonomously developing internal representations of incoming stimuli; an output network, collecting information from the previous classifier and extracting the relevant part to be forwarded to the observer; an analog, VLSI (very large scale integration) neural chip implementing a recurrent network of spiking neurons and plastic synapses, and the test setup for it; a board designed to interface the standard PCI (peripheral component interconnect) bus of a PC with a special purpose, asynchronous bus for communication among neuromorphic chips; a short and preliminary account of an application-oriented device, taking advantage of the above communication infrastructure.

  9. Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

    Science.gov (United States)

    Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

    2017-10-01

    Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

  10. 2D MoS2 Neuromorphic Devices for Brain-Like Computational Systems.

    Science.gov (United States)

    Jiang, Jie; Guo, Junjie; Wan, Xiang; Yang, Yi; Xie, Haipeng; Niu, Dongmei; Yang, Junliang; He, Jun; Gao, Yongli; Wan, Qing

    2017-08-01

    Hardware implementation of artificial synapses/neurons with 2D solid-state devices is of great significance for nanoscale brain-like computational systems. Here, 2D MoS 2 synaptic/neuronal transistors are fabricated by using poly(vinyl alcohol) as the laterally coupled, proton-conducting electrolytes. Fundamental synaptic functions, such as an excitatory postsynaptic current, paired-pulse facilitation, and a dynamic filter for information transmission of biological synapse, are successfully emulated. Most importantly, with multiple input gates and one modulatory gate, spiking-dependent logic operation/modulation, multiplicative neural coding, and neuronal gain modulation are also experimentally demonstrated. The results indicate that the intriguing 2D MoS 2 transistors are also very promising for the next-generation of nanoscale neuromorphic device applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. An Energy Efficient Neuromorphic Computing System Using Real Time Sensing Method

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    2017-01-01

    In spintronic-based neuromorphic computing systems (NCS), the switching of magnetic moment in a magnetic tunnel junction (MTJ) is used to mimic neuron firing. However, the stochastic switching behavior of the MTJ and process variations effect leads to extra stimulation time. This leads to extra...... energy consumption and delay of such NCSs. In this paper, a new real-time sensing (RTS) circuit is proposed to track the MTJ state and terminate stimulation phase immediately after MTJ switching. This leads to significant degradation in energy consumption and delay of NCS. The simulation results using...... a 65-nm CMOS technology and a 40-nm MTJ technology confirm that the energy consumption of a RTS-based NCS is improved by 50% in comparison with a typical NCS. Moreover, utilizing RTS circuit improves the overall speed of an NCS by 2.75x....

  12. Coherent laser vision system

    International Nuclear Information System (INIS)

    Sebastion, R.L.

    1995-01-01

    The Coherent Laser Vision System (CLVS) is being developed to provide precision real-time 3D world views to support site characterization and robotic operations and during facilities Decontamination and Decommissioning. Autonomous or semiautonomous robotic operations requires an accurate, up-to-date 3D world view. Existing technologies for real-time 3D imaging, such as AM laser radar, have limited accuracy at significant ranges and have variability in range estimates caused by lighting or surface shading. Recent advances in fiber optic component technology and digital processing components have enabled the development of a new 3D vision system based upon a fiber optic FMCW coherent laser radar. The approach includes a compact scanner with no-moving parts capable of randomly addressing all pixels. The system maintains the immunity to lighting and surface shading conditions which is characteristic to coherent laser radar. The random pixel addressability allows concentration of scanning and processing on the active areas of a scene, as is done by the human eye-brain system

  13. Coherent laser vision system

    Energy Technology Data Exchange (ETDEWEB)

    Sebastion, R.L. [Coleman Research Corp., Springfield, VA (United States)

    1995-10-01

    The Coherent Laser Vision System (CLVS) is being developed to provide precision real-time 3D world views to support site characterization and robotic operations and during facilities Decontamination and Decommissioning. Autonomous or semiautonomous robotic operations requires an accurate, up-to-date 3D world view. Existing technologies for real-time 3D imaging, such as AM laser radar, have limited accuracy at significant ranges and have variability in range estimates caused by lighting or surface shading. Recent advances in fiber optic component technology and digital processing components have enabled the development of a new 3D vision system based upon a fiber optic FMCW coherent laser radar. The approach includes a compact scanner with no-moving parts capable of randomly addressing all pixels. The system maintains the immunity to lighting and surface shading conditions which is characteristic to coherent laser radar. The random pixel addressability allows concentration of scanning and processing on the active areas of a scene, as is done by the human eye-brain system.

  14. Modeling selective attention using a neuromorphic analog VLSI device.

    Science.gov (United States)

    Indiveri, G

    2000-12-01

    Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

  15. Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

    Science.gov (United States)

    Abdul-Kreem, Luma Issa; Neumann, Heiko

    2015-01-01

    The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells. PMID:26554589

  16. Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System.

    Directory of Open Access Journals (Sweden)

    Luma Issa Abdul-Kreem

    Full Text Available The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields. In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells.

  17. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

    Science.gov (United States)

    Wang, Zhongqiang; Ambrogio, Stefano; Balatti, Simone; Ielmini, Daniele

    2014-01-01

    Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.

  18. An exploration of neuromorphic systems and related design issues/challenges in dark silicon era

    Science.gov (United States)

    Chandaliya, Mudit; Chaturvedi, Nitin; Gurunarayanan, S.

    2018-03-01

    The current microprocessors has shown a remarkable performance and memory capacity improvement since its innovation. However, due to power and thermal limitations, only a fraction of cores can operate at full frequency at any instant of time irrespective of the advantages of new technology generation. This phenomenon of under-utilization of microprocessor is called as dark silicon which leads to distraction in innovative computing. To overcome the limitation of utilization wall, IBM technologies explored and invented neurosynaptic system chips. It has opened a wide scope of research in the field of innovative computing, technology, material sciences, machine learning etc. In this paper, we first reviewed the diverse stages of research that have been influential in the innovation of neurosynaptic architectures. These, architectures focuses on the development of brain-like framework which is efficient enough to execute a broad set of computations in real time while maintaining ultra-low power consumption as well as area considerations in mind. We also reveal the inadvertent challenges and the opportunities of designing neuromorphic systems as presented by the existing technologies in the dark silicon era, which constitute the utmost area of research in future.

  19. Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

    Energy Technology Data Exchange (ETDEWEB)

    Malyshev, K. V., E-mail: malyshev@bmstu.ru [Electronics and Laser Technology Department, Bauman Moscow State Technical University, Moscow 105005 (Russian Federation)

    2015-01-28

    The application of quasiperiodic AlGaAs superlattices as a nonlinear element of the FitzHugh–Nagumo neuromorphic network is proposed and theoretically investigated on the example of Fibonacci and figurate superlattices. The sequences of symbols for the figurate superlattices were produced by decomposition of the Fibonacci superlattices' symbolic sequences. A length of each segment of the decomposition was equal to the corresponding figurate number. It is shown that a nonlinear network based upon Fibonacci and figurate superlattices provides better parallel filtration of a half-tone picture; then, a network based upon traditional diodes which have cubic voltage-current characteristics. It was found that the figurate superlattice F{sup 0}{sub 11}(1) as a nonlinear network's element provides the filtration error almost twice less than the conventional “cubic” diode. These advantages are explained by a wavelike shape of the decreasing part of the quasiperiodic superlattice's voltage-current characteristic, which leads to multistability of the network's cell. This multistability promises new interesting nonlinear dynamical phenomena. A variety of wavy forms of voltage-current characteristics opens up new interesting possibilities for quasiperiodic superlattices and especially for figurate superlattices in many areas—from nervous system modeling to nonlinear control systems development.

  20. Energy-Efficient Neuromorphic Classifiers.

    Science.gov (United States)

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2016-10-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

  1. An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

    Science.gov (United States)

    Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

    2018-04-01

    Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

  2. Smart vision chips: An overview

    Science.gov (United States)

    Koch, Christof

    1994-01-01

    This viewgraph presentation presents four working analog VLSI vision chips: (1) time-derivative retina, (2) zero-crossing chip, (3) resistive fuse, and (4) figure-ground chip; work in progress on computing motion and neuromorphic systems; and conceptual and practical lessons learned.

  3. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2017-08-23

    Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  4. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System

    Directory of Open Access Journals (Sweden)

    Zhen Zhang

    2017-08-01

    Full Text Available Artificial Neural Networks (ANNs, including Deep Neural Networks (DNNs, have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP. The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  5. Neuromorphic atomic switch networks.

    Directory of Open Access Journals (Sweden)

    Audrius V Avizienis

    Full Text Available Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.

  6. Foundations of Neuromorphic Computing

    Science.gov (United States)

    2013-05-01

    paradigms: few sensors/complex computations and many sensors/simple computation. Challenges with Nano-enabled Neuromorphic Chips A wide variety of...FOUNDATIONS OF NEUROMORPHIC COMPUTING MAY 2013 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION...2009 – SEP 2012 4. TITLE AND SUBTITLE FOUNDATIONS OF NEUROMORPHIC COMPUTING 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER N/A 5c. PROGRAM

  7. Real-time vision systems

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, R.; Hernandez, J.E.; Lu, Shin-yee [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    Many industrial and defence applications require an ability to make instantaneous decisions based on sensor input of a time varying process. Such systems are referred to as `real-time systems` because they process and act on data as it occurs in time. When a vision sensor is used in a real-time system, the processing demands can be quite substantial, with typical data rates of 10-20 million samples per second. A real-time Machine Vision Laboratory (MVL) was established in FY94 to extend our years of experience in developing computer vision algorithms to include the development and implementation of real-time vision systems. The laboratory is equipped with a variety of hardware components, including Datacube image acquisition and processing boards, a Sun workstation, and several different types of CCD cameras, including monochrome and color area cameras and analog and digital line-scan cameras. The equipment is reconfigurable for prototyping different applications. This facility has been used to support several programs at LLNL, including O Division`s Peacemaker and Deadeye Projects as well as the CRADA with the U.S. Textile Industry, CAFE (Computer Aided Fabric Inspection). To date, we have successfully demonstrated several real-time applications: bullet tracking, stereo tracking and ranging, and web inspection. This work has been documented in the ongoing development of a real-time software library.

  8. A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

    Science.gov (United States)

    Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

    2018-02-01

    Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

  9. Bio-inspired vision

    International Nuclear Information System (INIS)

    Posch, C

    2012-01-01

    Nature still outperforms the most powerful computers in routine functions involving perception, sensing and actuation like vision, audition, and motion control, and is, most strikingly, orders of magnitude more energy-efficient than its artificial competitors. The reasons for the superior performance of biological systems are subject to diverse investigations, but it is clear that the form of hardware and the style of computation in nervous systems are fundamentally different from what is used in artificial synchronous information processing systems. Very generally speaking, biological neural systems rely on a large number of relatively simple, slow and unreliable processing elements and obtain performance and robustness from a massively parallel principle of operation and a high level of redundancy where the failure of single elements usually does not induce any observable system performance degradation. In the late 1980's, Carver Mead demonstrated that silicon VLSI technology can be employed in implementing ''neuromorphic'' circuits that mimic neural functions and fabricating building blocks that work like their biological role models. Neuromorphic systems, as the biological systems they model, are adaptive, fault-tolerant and scalable, and process information using energy-efficient, asynchronous, event-driven methods. In this paper, some basics of neuromorphic electronic engineering and its impact on recent developments in optical sensing and artificial vision are presented. It is demonstrated that bio-inspired vision systems have the potential to outperform conventional, frame-based vision acquisition and processing systems in many application fields and to establish new benchmarks in terms of redundancy suppression/data compression, dynamic range, temporal resolution and power efficiency to realize advanced functionality like 3D vision, object tracking, motor control, visual feedback loops, etc. in real-time. It is argued that future artificial vision systems

  10. Neuromorphic Modeling of Moving Target Detection in Insects

    Science.gov (United States)

    2007-12-31

    Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected

  11. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  12. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  13. A Low-Power High-Speed Spintronics-Based Neuromorphic Computing System Using Real Time Tracking Method

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    2018-01-01

    In spintronic-based neuromorphic computing systems (NCS), the switching of magnetic moment in a magnetic tunnel junction (MTJ) is used to mimic neuron firing. However, the stochastic switching behavior of the MTJ and process variations effect lead to a significant increase in stimulation time...... of such NCSs. Moreover, current NCSs need an extra phase to read the MTJ state after stimulation which is in contrast with real neuron functionality in human body. In this paper, the read circuit is replaced with a proposed real-time sensing (RTS) circuit. The RTS circuit tracks the MTJ state during...... stimulation phase. As soon as switching happens, the RTS circuit terminates the MTJ current and stimulates the post neuron. Hence, the RTS circuit not only improves the energy consumption and speed, but also makes the operation of NCS similar to real neuron functionality. The simulation results in 65-nm CMOS...

  14. Dynamical Systems and Motion Vision.

    Science.gov (United States)

    1988-04-01

    TASK Artificial Inteligence Laboratory AREA I WORK UNIT NUMBERS 545 Technology Square . Cambridge, MA 02139 C\\ II. CONTROLLING OFFICE NAME ANO0 ADDRESS...INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I.Memo No. 1037 April, 1988 Dynamical Systems and Motion Vision Joachim Heel Abstract: In this... Artificial Intelligence L3 Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory’s [1 Artificial Intelligence Research is

  15. Neuromorphic walking gait control.

    Science.gov (United States)

    Still, Susanne; Hepp, Klaus; Douglas, Rodney J

    2006-03-01

    We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

  16. Computer vision in control systems

    CERN Document Server

    Jain, Lakhmi

    2015-01-01

    Volume 1 : This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: ·         Morphological Image Analysis for Computer Vision Applications. ·         Methods for Detecting of Structural Changes in Computer Vision Systems. ·         Hierarchical Adaptive KL-based Transform: Algorithms and Applications. ·         Automatic Estimation for Parameters of Image Projective Transforms Based on Object-invariant Cores. ·         A Way of Energy Analysis for Image and Video Sequence Processing. ·         Optimal Measurement of Visual Motion Across Spatial and Temporal Scales. ·         Scene Analysis Using Morphological Mathematics and Fuzzy Logic. ·         Digital Video Stabilization in Static and Dynamic Scenes. ·         Implementation of Hadamard Matrices for Image Processing. ·         A Generalized Criterion ...

  17. Basic design principles of colorimetric vision systems

    Science.gov (United States)

    Mumzhiu, Alex M.

    1998-10-01

    Color measurement is an important part of overall production quality control in textile, coating, plastics, food, paper and other industries. The color measurement instruments such as colorimeters and spectrophotometers, used for production quality control have many limitations. In many applications they cannot be used for a variety of reasons and have to be replaced with human operators. Machine vision has great potential for color measurement. The components for color machine vision systems, such as broadcast quality 3-CCD cameras, fast and inexpensive PCI frame grabbers, and sophisticated image processing software packages are available. However the machine vision industry has only started to approach the color domain. The few color machine vision systems on the market, produced by the largest machine vision manufacturers have very limited capabilities. A lack of understanding that a vision based color measurement system could fail if it ignores the basic principles of colorimetry is the main reason for the slow progress of color vision systems. the purpose of this paper is to clarify how color measurement principles have to be applied to vision systems and how the electro-optical design features of colorimeters have to be modified in order to implement them for vision systems. The subject of this presentation far exceeds the limitations of a journal paper so only the most important aspects will be discussed. An overview of the major areas of applications for colorimetric vision system will be discussed. Finally, the reasons why some customers are happy with their vision systems and some are not will be analyzed.

  18. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.; Zidan, Mohammed A.; Salama, Khaled N.; Hussain, Muhammad Mustafa

    2014-01-01

    foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench

  19. Neuromorphic Data Microscope

    Energy Technology Data Exchange (ETDEWEB)

    Naegle, John H.; Suppona, Roger A.; Aimone, James Bradley; James, Conrad D.; Follett, David R.; Townsend, Duncan C.M.; Follett, Pamela L.; Karpman, Gabe D.

    2017-08-01

    In 2016, Lewis Rhodes Labs, (LRL), shipped the first commercially viable Neuromorphic Processing Unit, (NPU), branded as a Neuromorphic Data Microscope (NDM). This product leverages architectural mechanisms derived from the sensory cortex of the human brain to efficiently implement pattern matching. LRL and Sandia National Labs have optimized this product for streaming analytics, and demonstrated a 1,000x power per operation reduction in an FPGA format. When reduced to an ASIC, the efficiency will improve to 1,000,000x. Additionally, the neuromorphic nature of the device gives it powerful computational attributes that are counterintuitive to those schooled in traditional von Neumann architectures. The Neuromorphic Data Microscope is the first of a broad class of brain-inspired, time domain processors that will profoundly alter the functionality and economics of data processing.

  20. STDP and STDP Variations with Memristors for Spiking Neuromorphic Learning Systems

    Directory of Open Access Journals (Sweden)

    Teresa eSerrano-Gotarredona

    2013-02-01

    Full Text Available In this paper we review several ways of realizing asynchronous Spike-Timing Dependent Plasticity (STDP using memristors as synapses. Our focus is on how to use individual memristors to implement synaptic weight multiplications, in a way such that it is not necessary to (a introduce global synchronization and (b to separate memristor learning phases from memristor performing phases. In the approaches described, neurons fire spikes asynchronously when they wish and memristive synapses perform computation and learn at their own pace, as it happens in biological neural systems. We distinguish between two different memristor physics, depending on whether they respond to the original ``moving wall'' or to the ``filament creation and annihilation'' models. Independent of the memristor physics, we discuss two different types of STDP rules that can be implemented with memristors: either the pure timing-based rule that takes into account the arrival time of the spikes from the pre- and the post-synaptic neurons, or a hybrid rule that takes into account only the timing of pre-synaptic spikes and the membrane potential and other state variables of the post-synaptic neuron. We show how to implement these rules in cross-bar architectures that comprise massive arrays of memristors, and we discuss applications for artificial vision.

  1. Parallel Evolutionary Optimization for Neuromorphic Network Training

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

    2016-01-01

    One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

  2. Vision based systems for UAV applications

    CERN Document Server

    Kuś, Zygmunt

    2013-01-01

    This monograph is motivated by a significant number of vision based algorithms for Unmanned Aerial Vehicles (UAV) that were developed during research and development projects. Vision information is utilized in various applications like visual surveillance, aim systems, recognition systems, collision-avoidance systems and navigation. This book presents practical applications, examples and recent challenges in these mentioned application fields. The aim of the book is to create a valuable source of information for researchers and constructors of solutions utilizing vision from UAV. Scientists, researchers and graduate students involved in computer vision, image processing, data fusion, control algorithms, mechanics, data mining, navigation and IC can find many valuable, useful and practical suggestions and solutions. The latest challenges for vision based systems are also presented.

  3. Progress in neuromorphic photonics

    Science.gov (United States)

    Ferreira de Lima, Thomas; Shastri, Bhavin J.; Tait, Alexander N.; Nahmias, Mitchell A.; Prucnal, Paul R.

    2017-03-01

    As society's appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is becoming a limiting factor in certain areas such as data links, cognitive radio, and ultrafast control. Analog photonic devices have found relatively simple signal processing niches where electronics can no longer provide sufficient speed and reconfigurability. Recently, the landscape for commercially manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. By bridging the mathematical prowess of artificial neural networks to the underlying physics of optoelectronic devices, neuromorphic photonics could breach new domains of information processing demanding significant complexity, low cost, and unmatched speed. In this article, we review the progress in neuromorphic photonics, focusing on photonic integrated devices. The challenges and design rules for optoelectronic instantiation of artificial neurons are presented. The proposed photonic architecture revolves around the processing network node composed of two parts: a nonlinear element and a network interface. We then survey excitable lasers in the recent literature as candidates for the nonlinear node and microring-resonator weight banks as the network interface. Finally, we compare metrics between neuromorphic electronics and neuromorphic photonics and discuss potential applications.

  4. Artificial vision support system (AVS(2)) for improved prosthetic vision.

    Science.gov (United States)

    Fink, Wolfgang; Tarbell, Mark A

    2014-11-01

    State-of-the-art and upcoming camera-driven, implanted artificial vision systems provide only tens to hundreds of electrodes, affording only limited visual perception for blind subjects. Therefore, real time image processing is crucial to enhance and optimize this limited perception. Since tens or hundreds of pixels/electrodes allow only for a very crude approximation of the typically megapixel optical resolution of the external camera image feed, the preservation and enhancement of contrast differences and transitions, such as edges, are especially important compared to picture details such as object texture. An Artificial Vision Support System (AVS(2)) is devised that displays the captured video stream in a pixelation conforming to the dimension of the epi-retinal implant electrode array. AVS(2), using efficient image processing modules, modifies the captured video stream in real time, enhancing 'present but hidden' objects to overcome inadequacies or extremes in the camera imagery. As a result, visual prosthesis carriers may now be able to discern such objects in their 'field-of-view', thus enabling mobility in environments that would otherwise be too hazardous to navigate. The image processing modules can be engaged repeatedly in a user-defined order, which is a unique capability. AVS(2) is directly applicable to any artificial vision system that is based on an imaging modality (video, infrared, sound, ultrasound, microwave, radar, etc.) as the first step in the stimulation/processing cascade, such as: retinal implants (i.e. epi-retinal, sub-retinal, suprachoroidal), optic nerve implants, cortical implants, electric tongue stimulators, or tactile stimulators.

  5. Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

    OpenAIRE

    Romeira, B.; Figueiredo, J. M. L.; Javaloyes, J.

    2017-01-01

    With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this ...

  6. Vision systems for scientific and engineering applications

    International Nuclear Information System (INIS)

    Chadda, V.K.

    2009-01-01

    Human performance can get degraded due to boredom, distraction and fatigue in vision-related tasks such as measurement, counting etc. Vision based techniques are increasingly being employed in many scientific and engineering applications. Notable advances in this field are emerging from continuing improvements in the fields of sensors and related technologies, and advances in computer hardware and software. Automation utilizing vision-based systems can perform repetitive tasks faster and more accurately, with greater consistency over time than humans. Electronics and Instrumentation Services Division has developed vision-based systems for several applications to perform tasks such as precision alignment, biometric access control, measurement, counting etc. This paper describes in brief four such applications. (author)

  7. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-07-01

    Neuromorphic computer will need folded architectural form factor to match brain cortex\\'s folded pattern for ultra-compact design. In this work, we show a state-of-the-art CMOS compatible pragmatic fabrication approach of building structurally foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench-protect-release-recycle process transform the silicon wafer with devices into a flexible and semi-transparent silicon fabric while recycling the remaining wafer for further use. This process unconditionally offers the ultra-large-scale-integration opportunity-increasingly critical for ultra-compact memory.

  8. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  9. Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture

    Science.gov (United States)

    2012-06-01

    system level built upon the conventional Von Neumann computer architecture [2][3]. Developing the neuromorphic architecture at chip level by...SCHEME FOR NEUROMORPHIC COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-11-2-0046 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor

  10. Health system vision of iran in 2025.

    Science.gov (United States)

    Rostamigooran, N; Esmailzadeh, H; Rajabi, F; Majdzadeh, R; Larijani, B; Dastgerdi, M Vahid

    2013-01-01

    Vast changes in disease features and risk factors and influence of demographic, economical, and social trends on health system, makes formulating a long term evolutionary plan, unavoidable. In this regard, to determine health system vision in a long term horizon is a primary stage. After narrative and purposeful review of documentaries, major themes of vision statement were determined and its context was organized in a work group consist of selected managers and experts of health system. Final content of the statement was prepared after several sessions of group discussions and receiving ideas of policy makers and experts of health system. Vision statement in evolutionary plan of health system is considered to be :"a progressive community in the course of human prosperity which has attained to a developed level of health standards in the light of the most efficient and equitable health system in visionary region(1) and with the regarding to health in all policies, accountability and innovation". An explanatory context was compiled either to create a complete image of the vision. Social values and leaders' strategic goals, and also main orientations are generally mentioned in vision statement. In this statement prosperity and justice are considered as major values and ideals in society of Iran; development and excellence in the region as leaders' strategic goals; and also considering efficiency and equality, health in all policies, and accountability and innovation as main orientations of health system.

  11. Toward exascale computing through neuromorphic approaches.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D.

    2010-09-01

    While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.

  12. A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications.

    Science.gov (United States)

    Kim, Kuk-Hwan; Gaba, Siddharth; Wheeler, Dana; Cruz-Albrecht, Jose M; Hussain, Tahir; Srinivasa, Narayan; Lu, Wei

    2012-01-11

    Crossbar arrays based on two-terminal resistive switches have been proposed as a leading candidate for future memory and logic applications. Here we demonstrate a high-density, fully operational hybrid crossbar/CMOS system composed of a transistor- and diode-less memristor crossbar array vertically integrated on top of a CMOS chip by taking advantage of the intrinsic nonlinear characteristics of the memristor element. The hybrid crossbar/CMOS system can reliably store complex binary and multilevel 1600 pixel bitmap images using a new programming scheme. © 2011 American Chemical Society

  13. Neuron Design in Neuromorphic Computing Systems and Its Application in Wireless Communications

    Science.gov (United States)

    2017-03-01

    26 21 Measurement Results of Two Samples……………………………………………………….26 22 Normalized Verification Value……………………………………………………………….27 23...currently the most popular choice, and has been adopted in modern Long-Term Evolution ( LTE )/ LTE -Advanced systems. The result of this task included a...reviews, a final technical report, as well as the following items: • Circuit design, fabrication, and measurement materials including SPICE (Simulation

  14. AN INVESTIGATION OF VISION PROBLEMS AND THE VISION CARE SYSTEM IN RURAL CHINA.

    Science.gov (United States)

    Bai, Yunli; Yi, Hongmei; Zhang, Linxiu; Shi, Yaojiang; Ma, Xiaochen; Congdon, Nathan; Zhou, Zhongqiang; Boswell, Matthew; Rozelle, Scott

    2014-11-01

    This paper examines the prevalence of vision problems and the accessibility to and quality of vision care in rural China. We obtained data from 4 sources: 1) the National Rural Vision Care Survey; 2) the Private Optometrists Survey; 3) the County Hospital Eye Care Survey; and 4) the Rural School Vision Care Survey. The data from each of the surveys were collected by the authors during 2012. Thirty-three percent of the rural population surveyed self-reported vision problems. Twenty-two percent of subjects surveyed had ever had a vision exam. Among those who self-reported having vision problems, 34% did not wear eyeglasses. Fifty-four percent of those with vision problems who had eyeglasses did not have a vision exam prior to receiving glasses. However, having a vision exam did not always guarantee access to quality vision care. Four channels of vision care service were assessed. The school vision examination program did not increase the usage rate of eyeglasses. Each county-hospital was staffed with three eye-doctors having one year of education beyond high school, serving more than 400,000 residents. Private optometrists often had low levels of education and professional certification. In conclusion, our findings shows that the vision care system in rural China is inadequate and ineffective in meeting the needs of the rural population sampled.

  15. Detection of Visual Events in Underwater Video Using a Neuromorphic Saliency-based Attention System

    Science.gov (United States)

    Edgington, D. R.; Walther, D.; Cline, D. E.; Sherlock, R.; Salamy, K. A.; Wilson, A.; Koch, C.

    2003-12-01

    The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment on remotely operated vehicles (ROV) to obtain quantitative data on the distribution and abundance of oceanic animals. High-quality video data supplants the traditional approach of assessing the kinds and numbers of animals in the oceanic water column through towing collection nets behind ships. Tow nets are limited in spatial resolution, and often destroy abundant gelatinous animals resulting in species undersampling. Video camera-based quantitative video transects (QVT) are taken through the ocean midwater, from 50m to 4000m, and provide high-resolution data at the scale of the individual animals and their natural aggregation patterns. However, the current manual method of analyzing QVT video by trained scientists is labor intensive and poses a serious limitation to the amount of information that can be analyzed from ROV dives. Presented here is an automated system for detecting marine animals (events) visible in the videos. Automated detection is difficult due to the low contrast of many translucent animals and due to debris ("marine snow") cluttering the scene. Video frames are processed with an artificial intelligence attention selection algorithm that has proven a robust means of target detection in a variety of natural terrestrial scenes. The candidate locations identified by the attention selection module are tracked across video frames using linear Kalman filters. Typically, the occurrence of visible animals in the video footage is sparse in space and time. A notion of "boring" video frames is developed by detecting whether or not there is an interesting candidate object for an animal present in a particular sequence of underwater video -- video frames that do not contain any "interesting" events. If objects can be tracked successfully over several frames, they are stored as potentially "interesting" events. Based on low-level properties, interesting events are

  16. Vision based flight procedure stereo display system

    Science.gov (United States)

    Shen, Xiaoyun; Wan, Di; Ma, Lan; He, Yuncheng

    2008-03-01

    A virtual reality flight procedure vision system is introduced in this paper. The digital flight map database is established based on the Geographic Information System (GIS) and high definitions satellite remote sensing photos. The flight approaching area database is established through computer 3D modeling system and GIS. The area texture is generated from the remote sensing photos and aerial photographs in various level of detail. According to the flight approaching procedure, the flight navigation information is linked to the database. The flight approaching area vision can be dynamic displayed according to the designed flight procedure. The flight approaching area images are rendered in 2 channels, one for left eye images and the others for right eye images. Through the polarized stereoscopic projection system, the pilots and aircrew can get the vivid 3D vision of the flight destination approaching area. Take the use of this system in pilots preflight preparation procedure, the aircrew can get more vivid information along the flight destination approaching area. This system can improve the aviator's self-confidence before he carries out the flight mission, accordingly, the flight safety is improved. This system is also useful in validate the visual flight procedure design, and it helps to the flight procedure design.

  17. Missileborne Artificial Vision System (MAVIS)

    Science.gov (United States)

    Andes, David K.; Witham, James C.; Miles, Michael D.

    1994-01-01

    Several years ago when INTEL and China Lake designed the ETANN chip, analog VLSI appeared to be the only way to do high density neural computing. In the last five years, however, digital parallel processing chips capable of performing neural computation functions have evolved to the point of rough equality with analog chips in system level computational density. The Naval Air Warfare Center, China Lake, has developed a real time, hardware and software system designed to implement and evaluate biologically inspired retinal and cortical models. The hardware is based on the Adaptive Solutions Inc. massively parallel CNAPS system COHO boards. Each COHO board is a standard size 6U VME card featuring 256 fixed point, RISC processors running at 20 MHz in a SIMD configuration. Each COHO board has a companion board built to support a real time VSB interface to an imaging seeker, a NTSC camera, and to other COHO boards. The system is designed to have multiple SIMD machines each performing different corticomorphic functions. The system level software has been developed which allows a high level description of corticomorphic structures to be translated into the native microcode of the CNAPS chips. Corticomorphic structures are those neural structures with a form similar to that of the retina, the lateral geniculate nucleus, or the visual cortex. This real time hardware system is designed to be shrunk into a volume compatible with air launched tactical missiles. Initial versions of the software and hardware have been completed and are in the early stages of integration with a missile seeker.

  18. Vision enhanced navigation for unmanned systems

    Science.gov (United States)

    Wampler, Brandon Loy

    A vision based simultaneous localization and mapping (SLAM) algorithm is evaluated for use on unmanned systems. SLAM is a technique used by a vehicle to build a map of an environment while concurrently keeping track of its location within the map, without a priori knowledge. The work in this thesis is focused on using SLAM as a navigation solution when global positioning system (GPS) service is degraded or temporarily unavailable. Previous work on unmanned systems that lead up to the determination that a better navigation solution than GPS alone is first presented. This previous work includes control of unmanned systems, simulation, and unmanned vehicle hardware testing. The proposed SLAM algorithm follows the work originally developed by Davidson et al. in which they dub their algorithm MonoSLAM [1--4]. A new approach using the Pyramidal Lucas-Kanade feature tracking algorithm from Intel's OpenCV (open computer vision) library is presented as a means of keeping correct landmark correspondences as the vehicle moves through the scene. Though this landmark tracking method is unusable for long term SLAM due to its inability to recognize revisited landmarks, as opposed to the Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), its computational efficiency makes it a good candidate for short term navigation between GPS position updates. Additional sensor information is then considered by fusing INS and GPS information into the SLAM filter. The SLAM system, in its vision only and vision/IMU form, is tested on a table top, in an open room, and finally in an outdoor environment. For the outdoor environment, a form of the slam algorithm that fuses vision, IMU, and GPS information is tested. The proposed SLAM algorithm, and its several forms, are implemented in C++ using an Extended Kalman Filter (EKF). Experiments utilizing a live video feed from a webcam are performed. The different forms of the filter are compared and conclusions are made on

  19. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

    Science.gov (United States)

    Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

    2016-01-01

    Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

  20. American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Rivera-Acosta

    2017-09-01

    Full Text Available This paper reports the design and analysis of an American Sign Language (ASL alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage. The last stage of the system process is the classification of the ASL alphabet, achieved with a single artificial neural network implemented in digital hardware for higher speed. The overall result is the development of a classification system using the ASL signs contour, fully implemented in a reconfigurable device. The experimental results consist of a comparative analysis of the recognition rate among the alphabet signs using the neuromorphic camera in order to prove the proper operation of the digital image processing algorithms. In the experiments performed with 720 samples of 24 signs, a recognition accuracy of 79.58% was obtained.

  1. Semiautonomous teleoperation system with vision guidance

    Science.gov (United States)

    Yu, Wai; Pretlove, John R. G.

    1998-12-01

    This paper describes the ongoing research work on developing a telerobotic system in Mechatronic Systems and Robotics Research group at the University of Surrey. As human operators' manual control of remote robots always suffer from reduced performance and difficulties in perceiving information from the remote site, a system with a certain level of intelligence and autonomy will help to solve some of these problems. Thus, this system has been developed for this purpose. It also serves as an experimental platform to test the idea of using the combination of human and computer intelligence in teleoperation and finding out the optimum balance between them. The system consists of a Polhemus- based input device, a computer vision sub-system and a graphical user interface which communicates the operator with the remote robot. The system description is given in this paper as well as the preliminary experimental results of the system evaluation.

  2. Multi-channel automotive night vision system

    Science.gov (United States)

    Lu, Gang; Wang, Li-jun; Zhang, Yi

    2013-09-01

    A four-channel automotive night vision system is designed and developed .It is consist of the four active near-infrared cameras and an Mulit-channel image processing display unit,cameras were placed in the automobile front, left, right and rear of the system .The system uses near-infrared laser light source,the laser light beam is collimated, the light source contains a thermoelectric cooler (TEC),It can be synchronized with the camera focusing, also has an automatic light intensity adjustment, and thus can ensure the image quality. The principle of composition of the system is description in detail,on this basis, beam collimation,the LD driving and LD temperature control of near-infrared laser light source,four-channel image processing display are discussed.The system can be used in driver assistance, car BLIS, car parking assist system and car alarm system in day and night.

  3. Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

    Science.gov (United States)

    Walter, Florian; Röhrbein, Florian; Knoll, Alois

    2015-12-01

    The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high level of abstraction but employs highly realistic simulations of actual biological nervous systems. Even today, carrying out these simulations efficiently at appropriate timescales is challenging. Neuromorphic chip designs specially tailored to this task therefore offer an interesting perspective for neurorobotics. Unlike Von Neumann CPUs, these chips cannot be simply programmed with a standard programming language. Like real brains, their functionality is determined by the structure of neural connectivity and synaptic efficacies. Enabling higher cognitive functions for neurorobotics consequently requires the application of neurobiological learning algorithms to adjust synaptic weights in a biologically plausible way. In this paper, we therefore investigate how to program neuromorphic chips by means of learning. First, we provide an overview over selected neuromorphic chip designs and analyze them in terms of neural computation, communication systems and software infrastructure. On the theoretical side, we review neurobiological learning techniques. Based on this overview, we then examine on-die implementations of these learning algorithms on the considered neuromorphic chips. A final discussion puts the findings of this work into context and highlights how neuromorphic hardware can potentially advance the field of autonomous robot systems. The paper thus gives an in-depth overview of neuromorphic implementations of basic mechanisms of synaptic plasticity which are required to realize advanced cognitive capabilities with spiking neural networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Adaptive WTA with an analog VLSI neuromorphic learning chip.

    Science.gov (United States)

    Häfliger, Philipp

    2007-03-01

    In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

  5. Synthetic vision systems: operational considerations simulation experiment

    Science.gov (United States)

    Kramer, Lynda J.; Williams, Steven P.; Bailey, Randall E.; Glaab, Louis J.

    2007-04-01

    Synthetic vision is a computer-generated image of the external scene topography that is generated from aircraft attitude, high-precision navigation information, and data of the terrain, obstacles, cultural features, and other required flight information. A synthetic vision system (SVS) enhances this basic functionality with real-time integrity to ensure the validity of the databases, perform obstacle detection and independent navigation accuracy verification, and provide traffic surveillance. Over the last five years, NASA and its industry partners have developed and deployed SVS technologies for commercial, business, and general aviation aircraft which have been shown to provide significant improvements in terrain awareness and reductions in the potential for Controlled-Flight-Into-Terrain incidents / accidents compared to current generation cockpit technologies. It has been hypothesized that SVS displays can greatly improve the safety and operational flexibility of flight in Instrument Meteorological Conditions (IMC) to a level comparable to clear-day Visual Meteorological Conditions (VMC), regardless of actual weather conditions or time of day. An experiment was conducted to evaluate SVS and SVS-related technologies as well as the influence of where the information is provided to the pilot (e.g., on a Head-Up or Head-Down Display) for consideration in defining landing minima based upon aircraft and airport equipage. The "operational considerations" evaluated under this effort included reduced visibility, decision altitudes, and airport equipage requirements, such as approach lighting systems, for SVS-equipped aircraft. Subjective results from the present study suggest that synthetic vision imagery on both head-up and head-down displays may offer benefits in situation awareness; workload; and approach and landing performance in the visibility levels, approach lighting systems, and decision altitudes tested.

  6. Synthetic Vision Systems - Operational Considerations Simulation Experiment

    Science.gov (United States)

    Kramer, Lynda J.; Williams, Steven P.; Bailey, Randall E.; Glaab, Louis J.

    2007-01-01

    Synthetic vision is a computer-generated image of the external scene topography that is generated from aircraft attitude, high-precision navigation information, and data of the terrain, obstacles, cultural features, and other required flight information. A synthetic vision system (SVS) enhances this basic functionality with real-time integrity to ensure the validity of the databases, perform obstacle detection and independent navigation accuracy verification, and provide traffic surveillance. Over the last five years, NASA and its industry partners have developed and deployed SVS technologies for commercial, business, and general aviation aircraft which have been shown to provide significant improvements in terrain awareness and reductions in the potential for Controlled-Flight-Into-Terrain incidents/accidents compared to current generation cockpit technologies. It has been hypothesized that SVS displays can greatly improve the safety and operational flexibility of flight in Instrument Meteorological Conditions (IMC) to a level comparable to clear-day Visual Meteorological Conditions (VMC), regardless of actual weather conditions or time of day. An experiment was conducted to evaluate SVS and SVS-related technologies as well as the influence of where the information is provided to the pilot (e.g., on a Head-Up or Head-Down Display) for consideration in defining landing minima based upon aircraft and airport equipage. The "operational considerations" evaluated under this effort included reduced visibility, decision altitudes, and airport equipage requirements, such as approach lighting systems, for SVS-equipped aircraft. Subjective results from the present study suggest that synthetic vision imagery on both head-up and head-down displays may offer benefits in situation awareness; workload; and approach and landing performance in the visibility levels, approach lighting systems, and decision altitudes tested.

  7. DLP™-based dichoptic vision test system

    Science.gov (United States)

    Woods, Russell L.; Apfelbaum, Henry L.; Peli, Eli

    2010-01-01

    It can be useful to present a different image to each of the two eyes while they cooperatively view the world. Such dichoptic presentation can occur in investigations of stereoscopic and binocular vision (e.g., strabismus, amblyopia) and vision rehabilitation in clinical and research settings. Various techniques have been used to construct dichoptic displays. The most common and most flexible modern technique uses liquid-crystal (LC) shutters. When used in combination with cathode ray tube (CRT) displays, there is often leakage of light from the image intended for one eye into the view of the other eye. Such interocular crosstalk is 14% even in our state of the art CRT-based dichoptic system. While such crosstalk may have minimal impact on stereo movie or video game experiences, it can defeat clinical and research investigations. We use micromirror digital light processing (DLP™) technology to create a novel dichoptic visual display system with substantially lower interocular crosstalk (0.3% remaining crosstalk comes from the LC shutters). The DLP system normally uses a color wheel to display color images. Our approach is to disable the color wheel, synchronize the display directly to the computer's sync signal, allocate each of the three (former) color presentations to one or both eyes, and open and close the LC shutters in synchrony with those color events.

  8. Embedded Active Vision System Based on an FPGA Architecture

    Directory of Open Access Journals (Sweden)

    Chalimbaud Pierre

    2007-01-01

    Full Text Available In computer vision and more particularly in vision processing, the impressive evolution of algorithms and the emergence of new techniques dramatically increase algorithm complexity. In this paper, a novel FPGA-based architecture dedicated to active vision (and more precisely early vision is proposed. Active vision appears as an alternative approach to deal with artificial vision problems. The central idea is to take into account the perceptual aspects of visual tasks, inspired by biological vision systems. For this reason, we propose an original approach based on a system on programmable chip implemented in an FPGA connected to a CMOS imager and an inertial set. With such a structure based on reprogrammable devices, this system admits a high degree of versatility and allows the implementation of parallel image processing algorithms.

  9. Embedded Active Vision System Based on an FPGA Architecture

    Directory of Open Access Journals (Sweden)

    Pierre Chalimbaud

    2006-12-01

    Full Text Available In computer vision and more particularly in vision processing, the impressive evolution of algorithms and the emergence of new techniques dramatically increase algorithm complexity. In this paper, a novel FPGA-based architecture dedicated to active vision (and more precisely early vision is proposed. Active vision appears as an alternative approach to deal with artificial vision problems. The central idea is to take into account the perceptual aspects of visual tasks, inspired by biological vision systems. For this reason, we propose an original approach based on a system on programmable chip implemented in an FPGA connected to a CMOS imager and an inertial set. With such a structure based on reprogrammable devices, this system admits a high degree of versatility and allows the implementation of parallel image processing algorithms.

  10. An Application Development Platform for Neuromorphic Computing

    Energy Technology Data Exchange (ETDEWEB)

    Dean, Mark [University of Tennessee (UT); Chan, Jason [University of Tennessee (UT); Daffron, Christopher [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT); Rose, Garrett [University of Tennessee (UT); Plank, James [University of Tennessee (UT); Birdwell, John Douglas [University of Tennessee (UT); Schuman, Catherine D [ORNL

    2016-01-01

    Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

  11. All-memristive neuromorphic computing with level-tuned neurons

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-01

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

  12. All-memristive neuromorphic computing with level-tuned neurons.

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-02

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

  13. A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

    Science.gov (United States)

    Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

    1990-01-01

    Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

  14. Serendipitous Offline Learning in a Neuromorphic Robot

    Directory of Open Access Journals (Sweden)

    Terrence C Stewart

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviours. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviours. All sensor data is provided via a spike-based silicon retina camera (eDVS, and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker. Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where he robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behaviour.

  15. Analysis of the resistive network in a bio-inspired CMOS vision chip

    Science.gov (United States)

    Kong, Jae-Sung; Sung, Dong-Kyu; Hyun, Hyo-Young; Shin, Jang-Kyoo

    2007-12-01

    CMOS vision chips for edge detection based on a resistive circuit have recently been developed. These chips help develop neuromorphic systems with a compact size, high speed of operation, and low power dissipation. The output of the vision chip depends dominantly upon the electrical characteristics of the resistive network which consists of a resistive circuit. In this paper, the body effect of the MOSFET for current distribution in a resistive circuit is discussed with a simple model. In order to evaluate the model, two 160×120 CMOS vision chips have been fabricated by using a standard CMOS technology. The experimental results have been nicely matched with our prediction.

  16. Convolutional networks for fast, energy-efficient neuromorphic computing.

    Science.gov (United States)

    Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

    2016-10-11

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

  17. Convolutional networks for fast, energy-efficient neuromorphic computing

    Science.gov (United States)

    Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

    2016-01-01

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

  18. Hi-Vision telecine system using pickup tube

    Science.gov (United States)

    Iijima, Goro

    1992-08-01

    Hi-Vision broadcasting, offering far more lifelike pictures than those produced by existing television broadcasting systems, has enormous potential in both industrial and commercial fields. The dissemination of the Hi-Vision system will enable vivid, movie theater quality pictures to be readily enjoyed in homes in the near future. To convert motion film pictures into Hi-Vision signals, a telecine system is needed. The Hi-Vision telecine systems currently under development are the "laser telecine," "flying-spot telecine," and "Saticon telecine" systems. This paper provides an overview of the pickup tube type Hi-Vision telecine system (referred to herein as the Saticon telecine system) developed and marketed by Ikegami Tsushinki Co., Ltd.

  19. Intelligent Computer Vision System for Automated Classification

    International Nuclear Information System (INIS)

    Jordanov, Ivan; Georgieva, Antoniya

    2010-01-01

    In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

  20. Vision Systems with the Human in the Loop

    Science.gov (United States)

    Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

    2005-12-01

    The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

  1. Vision Systems with the Human in the Loop

    Directory of Open Access Journals (Sweden)

    Bauckhage Christian

    2005-01-01

    Full Text Available The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

  2. Machine Vision Systems for Processing Hardwood Lumber and Logs

    Science.gov (United States)

    Philip A. Araman; Daniel L. Schmoldt; Tai-Hoon Cho; Dongping Zhu; Richard W. Conners; D. Earl Kline

    1992-01-01

    Machine vision and automated processing systems are under development at Virginia Tech University with support and cooperation from the USDA Forest Service. Our goals are to help U.S. hardwood producers automate, reduce costs, increase product volume and value recovery, and market higher value, more accurately graded and described products. Any vision system is...

  3. Enhanced Flight Vision Systems and Synthetic Vision Systems for NextGen Approach and Landing Operations

    Science.gov (United States)

    Kramer, Lynda J.; Bailey, Randall E.; Ellis, Kyle K. E.; Williams, Steven P.; Arthur, Jarvis J., III; Prinzel, Lawrence J., III; Shelton, Kevin J.

    2013-01-01

    Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment with equivalent efficiency as visual operations. To meet this potential, research is needed for effective technology development and implementation of regulatory standards and design guidance to support introduction and use of SVS/EFVS advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. A fixed-base pilot-in-the-loop simulation test was conducted at NASA Langley Research Center that evaluated the use of SVS/EFVS in NextGen low visibility approach and landing operations. Twelve crews flew approach and landing operations in a simulated NextGen Chicago O'Hare environment. Various scenarios tested the potential for using EFVS to conduct approach, landing, and roll-out operations in visibility as low as 1000 feet runway visual range (RVR). Also, SVS was tested to evaluate the potential for lowering decision heights (DH) on certain instrument approach procedures below what can be flown today. Expanding the portion of the visual segment in which EFVS can be used in lieu of natural vision from 100 feet above the touchdown zone elevation to touchdown and rollout in visibilities as low as 1000 feet RVR appears to be viable as touchdown performance was acceptable without any apparent workload penalties. A lower DH of 150 feet and/or possibly reduced visibility minima using SVS appears to be viable when implemented on a Head-Up Display, but the landing data suggests further study for head-down implementations.

  4. Intensity measurement of automotive headlamps using a photometric vision system

    Science.gov (United States)

    Patel, Balvant; Cruz, Jose; Perry, David L.; Himebaugh, Frederic G.

    1996-01-01

    Requirements for automotive head lamp luminous intensity tests are introduced. The rationale for developing a non-goniometric photometric test system is discussed. The design of the Ford photometric vision system (FPVS) is presented, including hardware, software, calibration, and system use. Directional intensity plots and regulatory test results obtained from the system are compared to corresponding results obtained from a Ford goniometric test system. Sources of error for the vision system and goniometer are discussed. Directions for new work are identified.

  5. Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

    Science.gov (United States)

    Romeira, Bruno; Figueiredo, José M. L.; Javaloyes, Julien

    2017-11-01

    With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

  6. Physics Based Vision Systems for Robotic Manipulation

    Data.gov (United States)

    National Aeronautics and Space Administration — With the increase of robotic manipulation tasks (TA4.3), specifically dexterous manipulation tasks (TA4.3.2), more advanced computer vision algorithms will be...

  7. A Fast Vision System for Soccer Robot

    Directory of Open Access Journals (Sweden)

    Tianwu Yang

    2012-01-01

    Full Text Available This paper proposes a fast colour-based object recognition and localization for soccer robots. The traditional HSL colour model is modified for better colour segmentation and edge detection in a colour coded environment. The object recognition is based on only the edge pixels to speed up the computation. The edge pixels are detected by intelligently scanning a small part of whole image pixels which is distributed over the image. A fast method for line and circle centre detection is also discussed. For object localization, 26 key points are defined on the soccer field. While two or more key points can be seen from the robot camera view, the three rotation angles are adjusted to achieve a precise localization of robots and other objects. If no key point is detected, the robot position is estimated according to the history of robot movement and the feedback from the motors and sensors. The experiments on NAO and RoboErectus teen-size humanoid robots show that the proposed vision system is robust and accurate under different lighting conditions and can effectively and precisely locate robots and other objects.

  8. INVIS : Integrated night vision surveillance and observation system

    NARCIS (Netherlands)

    Toet, A.; Hogervorst, M.A.; Dijk, J.; Son, R. van

    2010-01-01

    We present the design and first field trial results of the all-day all-weather INVIS Integrated Night Vision surveillance and observation System. The INVIS augments a dynamic three-band false-color nightvision image with synthetic 3D imagery in a real-time display. The night vision sensor suite

  9. Vision system for dial gage torque wrench calibration

    Science.gov (United States)

    Aggarwal, Neelam; Doiron, Theodore D.; Sanghera, Paramjeet S.

    1993-11-01

    In this paper, we present the development of a fast and robust vision system which, in conjunction with the Dial Gage Calibration system developed by AKO Inc., will be used by the U.S. Army in calibrating dial gage torque wrenches. The vision system detects the change in the angular position of the dial pointer in a dial gage. The angular change is proportional to the applied torque. The input to the system is a sequence of images of the torque wrench dial gage taken at different dial pointer positions. The system then reports the angular difference between the different positions. The primary components of this vision system include modules for image acquisition, linear feature extraction and angle measurements. For each of these modules, several techniques were evaluated and the most applicable one was selected. This system has numerous other applications like vision systems to read and calibrate analog instruments.

  10. Using neuromorphic optical sensors for spacecraft absolute and relative navigation

    Science.gov (United States)

    Shake, Christopher M.

    We develop a novel attitude determination system (ADS) for use on nano spacecraft using neuromorphic optical sensors. The ADS intends to support nano-satellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real time spacecraft operations. The ADS is experimentally validated with commercial-off-the-shelf optical devices that perform sensing and image processing on the same circuit board and are biologically inspired by insects' vision systems, which measure optical flow while navigating in the environment. The firmware on the devices is modified to both perform the additional biologically inspired task of tracking objects and communicate with a PC/104 form-factor embedded computer running Real Time Application Interface Linux used on a spacecraft simulator. Algorithms are developed for operations using optical flow, point tracking, and hybrid modes with the sensors, and the performance of the system in all three modes is assessed using a spacecraft simulator in the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory at Rensselaer. An existing relative state determination method is identified to be combined with the novel ADS to create a self-contained navigation system for nano spacecraft. The performance of the method is assessed in simulation and found not to match the results from its authors using only conditions and equations already published. An improved target inertia tensor method is proposed as an update to the existing relative state method, but found not to perform as expected, but is presented for others to build upon.

  11. Digital characterization of a neuromorphic IRFPA

    Science.gov (United States)

    Caulfield, John T.; Fisher, John; Zadnik, Jerome A.; Mak, Ernest S.; Scribner, Dean A.

    1995-05-01

    This paper reports on the performance of the Neuromorphic IRFPA, the first IRFPA designed and fabricated to conduct temporal and spatial processing on the focal plane. The Neuromorphic IRFPA's unique on-chip processing capability can perform retina-like functions such as lateral inhibition and contrast enhancement, spatial and temporal filtering, image compression and edge enhancement, and logarithmic response. Previously, all evaluations of the Neuromorphic IRFPA camera have been performed on the analog video output. In the work leading up to this paper, the Neuromorphic was integrated to a digital recorder to collect quantitative laboratory and field data. This paper describes the operation and characterization of specific on-chip processes such as spatial and temporal kernel size control. The use of Neuromorphic on-chip processing in future IRFPAs is analyzed as applied to improving SNR via adaptive nonuniformity, charge handling, and dynamic range problems.

  12. Visions of sustainable urban energy systems. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Pietzsch, Ursula [HFT Stuttgart (Germany). zafh.net - Centre of Applied Research - Sustainable Energy Technology; Mikosch, Milena [Steinbeis-Zentrum, Stuttgart (Germany). Europaeischer Technologietransfer; Liesner, Lisa (eds.)

    2010-09-15

    Within the polycity final conference from 15th to 17th September, 2010, in Stuttgart (Federal Republic of Germany) the following lectures were held: (1) Visions of sustainable urban energy system (Ursula Eicker); (2) Words of welcome (Tanja Goenner); (3) Zero-energy Europe - We are on our way (Jean-Marie Bemtgen); (4) Polycity - Energy networks in sustainable cities An introduction (Ursula Pietzsch); (5) Energy efficient city - Successful examples in the European concerto initiative (Brigitte Bach); (6) Sustainable building and urban concepts in the Catalonian polycity project contributions to the polycity final conference 2010 (Nuria Pedrals); (7) Energy efficient buildings and renewable supply within the German polycity project (Ursula Eicker); (8) Energy efficient buildings and cities in the US (Thomas Spiegehalter); (9) Energy efficient communities - First results from an IEA collaboration project (Reinhard Jank); (10) The European energy performance of buildings directive (EPBD) - Lessons learned (Eduardo Maldonado); (11) Passive house standard in Europe - State-of-the-art and challenges (Wolfgang Feist); (12) High efficiency non-residential buildings: Concepts, implementations and experiences from the UK (Levin Lomas); (13) This is how we can save our world (Franz Alt); (14) Green buildings and renewable heating and cooling concepts in China (Yanjun Dai); (15) Sustainable urban energy solutions for Asia (Brahmanand Mohanty); (16) Description of ''Parc de l'Alba'' polygeneration system: A large-scale trigeneration system with district heating within the Spanish polycity project (Francesc Figueras Bellot); (17) Improved building automation and control systems with hardware-in-the loop solutions (Martin Becker); (18) The Italian polycity project area: Arquata (Luigi Fazari); (19) Photovoltaic system integration: In rehabilitated urban structures: Experiences and performance results from the Italian polycity project in Turin (Franco

  13. Airborne Use of Night Vision Systems

    Science.gov (United States)

    Mepham, S.

    1990-04-01

    Mission Management Department of the Royal Aerospace Establishment has won a Queen's Award for Technology, jointly with GEC Sensors, in recognition of innovation and success in the development and application of night vision technology for fixed wing aircraft. This work has been carried out to satisfy the operational needs of the Royal Air Force. These are seen to be: - Operations in the NATO Central Region - To have a night as well as a day capability - To carry out low level, high speed penetration - To attack battlefield targets, especially groups of tanks - To meet these objectives at minimum cost The most effective way to penetrate enemy defences is at low level and survivability would be greatly enhanced with a first pass attack. It is therefore most important that not only must the pilot be able to fly at low level to the target but also he must be able to detect it in sufficient time to complete a successful attack. An analysis of the average operating conditions in Central Europe during winter clearly shows that high speed low level attacks can only be made for about 20 per cent of the 24 hours. Extending this into good night conditions raises the figure to 60 per cent. Whilst it is true that this is for winter conditions and in summer the situation is better, the overall advantage to be gained is clear. If our aircraft do not have this capability the potential for the enemy to advance his troops and armour without hinderance for considerable periods is all too obvious. There are several solutions to providing such a capability. The one chosen for Tornado GR1 is to use Terrain Following Radar (TFR). This system is a complete 24 hour capability. However it has two main disadvantages, it is an active system which means it can be jammed or homed into, and is useful in attacking pre-planned targets. Second it is an expensive system which precludes fitting to other than a small number of aircraft.

  14. Building Artificial Vision Systems with Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    LeCun, Yann [New York University

    2011-02-23

    Three questions pose the next challenge for Artificial Intelligence (AI), robotics, and neuroscience. How do we learn perception (e.g. vision)? How do we learn representations of the perceptual world? How do we learn visual categories from just a few examples?

  15. Vision system for diagnostic task | Merad | Global Journal of Pure ...

    African Journals Online (AJOL)

    Due to environment degraded conditions, direct measurements are not possible. ... Degraded conditions: vibrations, water and chip of metal projections, ... Before tooling, the vision system has to answer: “is it the right piece at the right place?

  16. An Integrated Calibration Technique for Stereo Vision Systems (PREPRINT)

    Science.gov (United States)

    2010-03-01

    technique for stereo vision systems has been developed. To demonstrate and evaluate this calibration technique, multiple Wii Remotes (Wiimotes) from Nintendo ...from Nintendo were used to form stereo vision systems to perform 3D motion capture in real time. This integrated technique is a two-step process...Wiimotes) used in Nintendo Wii games. Many researchers have successfully dealt with the problem of camera calibration by taking images from a 2D

  17. Vision/INS Integrated Navigation System for Poor Vision Navigation Environments

    Directory of Open Access Journals (Sweden)

    Youngsun Kim

    2016-10-01

    Full Text Available In order to improve the performance of an inertial navigation system, many aiding sensors can be used. Among these aiding sensors, a vision sensor is of particular note due to its benefits in terms of weight, cost, and power consumption. This paper proposes an inertial and vision integrated navigation method for poor vision navigation environments. The proposed method uses focal plane measurements of landmarks in order to provide position, velocity and attitude outputs even when the number of landmarks on the focal plane is not enough for navigation. In order to verify the proposed method, computer simulations and van tests are carried out. The results show that the proposed method gives accurate and reliable position, velocity and attitude outputs when the number of landmarks is insufficient.

  18. Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis

    Science.gov (United States)

    Choudhary, Alok Nidhi

    1989-01-01

    Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.

  19. Neuromorphic photonic networks using silicon photonic weight banks.

    Science.gov (United States)

    Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

    2017-08-07

    Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

  20. Six networks on a universal neuromorphic computing substrate

    Directory of Open Access Journals (Sweden)

    Thomas ePfeil

    2013-02-01

    Full Text Available In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

  1. Six networks on a universal neuromorphic computing substrate.

    Science.gov (United States)

    Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

    2013-01-01

    In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

  2. Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Andreas Stöckel

    2017-08-01

    Full Text Available Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP. Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard- and software development. In this paper we describe a scalable benchmark based on a spiking neural network implementation of the binary neural associative memory. We treat neuromorphic hardware and software simulators as black-boxes and execute exactly the same network description across all devices. Experiments on the HBP platforms under varying configurations of the associative memory show that the presented method allows to test the quality of the neuron model implementation, and to explain significant deviations from the expected reference output.

  3. Grasping Unknown Objects in an Early Cognitive Vision System

    DEFF Research Database (Denmark)

    Popovic, Mila

    2011-01-01

    Grasping of unknown objects presents an important and challenging part of robot manipulation. The growing area of service robotics depends upon the ability of robots to autonomously grasp and manipulate a wide range of objects in everyday environments. Simple, non task-specific grasps of unknown ...... and comparing vision-based grasping methods, and the creation of algorithms for bootstrapping a process of acquiring world understanding for artificial cognitive agents....... presents a system for robotic grasping of unknown objects us- ing stereo vision. Grasps are defined based on contour and surface information provided by the Early Cognitive Vision System, that organizes visual informa- tion into a biologically motivated hierarchical representation. The contributions...... of the thesis are: the extension of the Early Cognitive Vision representation with a new type of feature hierarchy in the texture domain, the definition and evaluation of contour based grasping methods, the definition and evaluation of surface based grasping methods, the definition of a benchmark for testing...

  4. Anthropomorphic reasoning about neuromorphic AGI safety

    Science.gov (United States)

    Jilk, David J.; Herd, Seth J.; Read, Stephen J.; O'Reilly, Randall C.

    2017-11-01

    One candidate approach to creating artificial general intelligence (AGI) is to imitate the essential computations of human cognition. This process is sometimes called 'reverse-engineering the brain' and the end product called 'neuromorphic.' We argue that, unlike with other approaches to AGI, anthropomorphic reasoning about behaviour and safety concerns is appropriate and crucial in a neuromorphic context. Using such reasoning, we offer some initial ideas to make neuromorphic AGI safer. In particular, we explore how basic drives that promote social interaction may be essential to the development of cognitive capabilities as well as serving as a focal point for human-friendly outcomes.

  5. Latency in Visionic Systems: Test Methods and Requirements

    Science.gov (United States)

    Bailey, Randall E.; Arthur, J. J., III; Williams, Steven P.; Kramer, Lynda J.

    2005-01-01

    A visionics device creates a pictorial representation of the external scene for the pilot. The ultimate objective of these systems may be to electronically generate a form of Visual Meteorological Conditions (VMC) to eliminate weather or time-of-day as an operational constraint and provide enhancement over actual visual conditions where eye-limiting resolution may be a limiting factor. Empirical evidence has shown that the total system delays or latencies including the imaging sensors and display systems, can critically degrade their utility, usability, and acceptability. Definitions and measurement techniques are offered herein as common test and evaluation methods for latency testing in visionics device applications. Based upon available data, very different latency requirements are indicated based upon the piloting task, the role in which the visionics device is used in this task, and the characteristics of the visionics cockpit display device including its resolution, field-of-regard, and field-of-view. The least stringent latency requirements will involve Head-Up Display (HUD) applications, where the visionics imagery provides situational information as a supplement to symbology guidance and command information. Conversely, the visionics system latency requirement for a large field-of-view Head-Worn Display application, providing a Virtual-VMC capability from which the pilot will derive visual guidance, will be the most stringent, having a value as low as 20 msec.

  6. A SYSTEMIC VISION OF BIOLOGY: OVERCOMING LINEARITY

    Directory of Open Access Journals (Sweden)

    M. Mayer

    2005-07-01

    Full Text Available Many  authors have proposed  that contextualization of reality  is necessary  to teach  Biology, empha- sizing students´ social and  economic realities.   However, contextualization means  more than  this;  it is related  to working with  different kinds of phenomena  and/or objects  which enable  the  expression of scientific concepts.  Thus,  contextualization allows the integration of different contents.  Under this perspective,  the  objectives  of this  work were to articulate different  biology concepts  in order  to de- velop a systemic vision of biology; to establish  relationships with other areas of knowledge and to make concrete the  cell molecular  structure and organization as well as their  implications  on living beings´ environment, using  contextualization.  The  methodology  adopted  in this  work  was based  on three aspects:  interdisciplinarity, contextualization and development of competences,  using energy:  its flux and transformations as a thematic axis and  an approach  which allowed the  interconnection between different situations involving  these  concepts.   The  activities developed  were:  1.   dialectic exercise, involving a movement around  micro and macroscopic aspects,  by using questions  and activities,  sup- ported  by the use of alternative material  (as springs, candles on the energy, its forms, transformations and  implications  in the  biological way (microscopic  concepts;  2, Construction of molecular  models, approaching the concepts of atom,  chemical bonds and bond energy in molecules; 3. Observations de- veloped in Manguezal¨(mangrove swamp  ecosystem (Itapissuma, PE  were used to work macroscopic concepts  (as  diversity  and  classification  of plants  and  animals,  concerning  to  energy  flow through food chains and webs. A photograph register of all activities  along the course plus texts

  7. A Vision for Systems Engineering Applied to Wind Energy (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Felker, F.; Dykes, K.

    2015-01-01

    This presentation was given at the Third Wind Energy Systems Engineering Workshop on January 14, 2015. Topics covered include the importance of systems engineering, a vision for systems engineering as applied to wind energy, and application of systems engineering approaches to wind energy research and development.

  8. Machine vision systems using machine learning for industrial product inspection

    Science.gov (United States)

    Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

    2002-02-01

    Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

  9. Visual Peoplemeter: A Vision-based Television Audience Measurement System

    Directory of Open Access Journals (Sweden)

    SKELIN, A. K.

    2014-11-01

    Full Text Available Visual peoplemeter is a vision-based measurement system that objectively evaluates the attentive behavior for TV audience rating, thus offering solution to some of drawbacks of current manual logging peoplemeters. In this paper, some limitations of current audience measurement system are reviewed and a novel vision-based system aiming at passive metering of viewers is prototyped. The system uses camera mounted on a television as a sensing modality and applies advanced computer vision algorithms to detect and track a person, and to recognize attentional states. Feasibility of the system is evaluated on a secondary dataset. The results show that the proposed system can analyze viewer's attentive behavior, therefore enabling passive estimates of relevant audience measurement categories.

  10. Exploration of a Vision for Actor Database Systems

    DEFF Research Database (Denmark)

    Shah, Vivek

    of these services. Existing popular approaches to building these services either use an in-memory database system or an actor runtime. We observe that these approaches have complementary strengths and weaknesses. In this dissertation, we propose the integration of actor programming models in database systems....... In doing so, we lay down a vision for a new class of systems called actor database systems. To explore this vision, this dissertation crystallizes the notion of an actor database system by defining its feature set in light of current application and hardware trends. In order to explore the viability...... of the outlined vision, a new programming model named Reactors has been designed to enrich classic relational database programming models with logical actor programming constructs. To support the reactor programming model, a high-performance in-memory multi-core OLTP database system named REACTDB has been built...

  11. Remote-controlled vision-guided mobile robot system

    Science.gov (United States)

    Ande, Raymond; Samu, Tayib; Hall, Ernest L.

    1997-09-01

    Automated guided vehicles (AGVs) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of the remote controlled emergency stop and vision systems for an autonomous mobile robot. The remote control provides human supervision and emergency stop capabilities for the autonomous vehicle. The vision guidance provides automatic operation. A mobile robot test-bed has been constructed using a golf cart base. The mobile robot (Bearcat) was built for the Association for Unmanned Vehicle Systems (AUVS) 1997 competition. The mobile robot has full speed control with guidance provided by a vision system and an obstacle avoidance system using ultrasonic sensors systems. Vision guidance is accomplished using two CCD cameras with zoom lenses. The vision data is processed by a high speed tracking device, communicating with the computer the X, Y coordinates of blobs along the lane markers. The system also has three emergency stop switches and a remote controlled emergency stop switch that can disable the traction motor and set the brake. Testing of these systems has been done in the lab as well as on an outside test track with positive results that show that at five mph the vehicle can follow a line and at the same time avoid obstacles.

  12. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  13. Neuromorphic UAS Collision Avoidance

    Data.gov (United States)

    National Aeronautics and Space Administration — Collision avoidance for unmanned aerial systems (UAS) traveling at high relative speeds is a challenging task. It requires both the detection of a possible collision...

  14. A Layered Active Memory Architecture for Cognitive Vision Systems

    OpenAIRE

    Kolonias, Ilias; Christmas, William; Kittler, Josef

    2007-01-01

    Recognising actions and objects from video material has attracted growing research attention and given rise to important applications. However, injecting cognitive capabilities into computer vision systems requires an architecture more elaborate than the traditional signal processing paradigm for information processing. Inspired by biological cognitive systems, we present a memory architecture enabling cognitive processes (such as selecting the processes required for scene understanding, laye...

  15. Reconfigurable vision system for real-time applications

    Science.gov (United States)

    Torres-Huitzil, Cesar; Arias-Estrada, Miguel

    2002-03-01

    Recently, a growing community of researchers has used reconfigurable systems to solve computationally intensive problems. Reconfigurability provides optimized processors for systems on chip designs, and makes easy to import technology to a new system through reusable modules. The main objective of this work is the investigation of a reconfigurable computer system targeted for computer vision and real-time applications. The system is intended to circumvent the inherent computational load of most window-based computer vision algorithms. It aims to build a system for such tasks by providing an FPGA-based hardware architecture for task specific vision applications with enough processing power, using the minimum amount of hardware resources as possible, and a mechanism for building systems using this architecture. Regarding the software part of the system, a library of pre-designed and general-purpose modules that implement common window-based computer vision operations is being investigated. A common generic interface is established for these modules in order to define hardware/software components. These components can be interconnected to develop more complex applications, providing an efficient mechanism for transferring image and result data among modules. Some preliminary results are presented and discussed.

  16. A robotic vision system to measure tree traits

    Science.gov (United States)

    The autonomous measurement of tree traits, such as branching structure, branch diameters, branch lengths, and branch angles, is required for tasks such as robotic pruning of trees as well as structural phenotyping. We propose a robotic vision system called the Robotic System for Tree Shape Estimati...

  17. Advanced robot vision system for nuclear power plants

    International Nuclear Information System (INIS)

    Onoguchi, Kazunori; Kawamura, Atsuro; Nakayama, Ryoichi.

    1991-01-01

    We have developed a robot vision system for advanced robots used in nuclear power plants, under a contract with the Agency of Industrial Science and Technology of the Ministry of International Trade and Industry. This work is part of the large-scale 'advanced robot technology' project. The robot vision system consists of self-location measurement, obstacle detection, and object recognition subsystems, which are activated by a total control subsystem. This paper presents details of these subsystems and the experimental results obtained. (author)

  18. The autonomous vision system on TeamSat

    DEFF Research Database (Denmark)

    Betto, Maurizio; Jørgensen, John Leif; Riis, Troels

    1999-01-01

    The second qualification flight of Ariane 5 blasted off-the European Space Port in French Guiana on October 30, 1997, carrying on board a small technology demonstration satellite called TeamSat. Several experiments were proposed by various universities and research institutions in Europe and five...... of them were finally selected and integrated into TeamSat, namely FIPEX, VTS, YES, ODD and the Autonomous Vision System, AVS, a fully autonomous star tracker and vision system. This paper gives short overview of the TeamSat satellite; design, implementation and mission objectives. AVS is described in more...

  19. Machine-Vision Systems Selection for Agricultural Vehicles: A Guide

    Directory of Open Access Journals (Sweden)

    Gonzalo Pajares

    2016-11-01

    Full Text Available Machine vision systems are becoming increasingly common onboard agricultural vehicles (autonomous and non-autonomous for different tasks. This paper provides guidelines for selecting machine-vision systems for optimum performance, considering the adverse conditions on these outdoor environments with high variability on the illumination, irregular terrain conditions or different plant growth states, among others. In this regard, three main topics have been conveniently addressed for the best selection: (a spectral bands (visible and infrared; (b imaging sensors and optical systems (including intrinsic parameters and (c geometric visual system arrangement (considering extrinsic parameters and stereovision systems. A general overview, with detailed description and technical support, is provided for each topic with illustrative examples focused on specific applications in agriculture, although they could be applied in different contexts other than agricultural. A case study is provided as a result of research in the RHEA (Robot Fleets for Highly Effective Agriculture and Forestry Management project for effective weed control in maize fields (wide-rows crops, funded by the European Union, where the machine vision system onboard the autonomous vehicles was the most important part of the full perception system, where machine vision was the most relevant. Details and results about crop row detection, weed patches identification, autonomous vehicle guidance and obstacle detection are provided together with a review of methods and approaches on these topics.

  20. Full Wafer Redistribution and Wafer Embedding as Key Technologies for a Multi-Scale Neuromorphic Hardware Cluster

    OpenAIRE

    Zoschke, Kai; Güttler, Maurice; Böttcher, Lars; Grübl, Andreas; Husmann, Dan; Schemmel, Johannes; Meier, Karlheinz; Ehrmann, Oswin

    2018-01-01

    Together with the Kirchhoff-Institute for Physics(KIP) the Fraunhofer IZM has developed a full wafer redistribution and embedding technology as base for a large-scale neuromorphic hardware system. The paper will give an overview of the neuromorphic computing platform at the KIP and the associated hardware requirements which drove the described technological developments. In the first phase of the project standard redistribution technologies from wafer level packaging were adapted to enable a ...

  1. A lightweight, inexpensive robotic system for insect vision.

    Science.gov (United States)

    Sabo, Chelsea; Chisholm, Robert; Petterson, Adam; Cope, Alex

    2017-09-01

    Designing hardware for miniaturized robotics which mimics the capabilities of flying insects is of interest, because they share similar constraints (i.e. small size, low weight, and low energy consumption). Research in this area aims to enable robots with similarly efficient flight and cognitive abilities. Visual processing is important to flying insects' impressive flight capabilities, but currently, embodiment of insect-like visual systems is limited by the hardware systems available. Suitable hardware is either prohibitively expensive, difficult to reproduce, cannot accurately simulate insect vision characteristics, and/or is too heavy for small robotic platforms. These limitations hamper the development of platforms for embodiment which in turn hampers the progress on understanding of how biological systems fundamentally work. To address this gap, this paper proposes an inexpensive, lightweight robotic system for modelling insect vision. The system is mounted and tested on a robotic platform for mobile applications, and then the camera and insect vision models are evaluated. We analyse the potential of the system for use in embodiment of higher-level visual processes (i.e. motion detection) and also for development of navigation based on vision for robotics in general. Optic flow from sample camera data is calculated and compared to a perfect, simulated bee world showing an excellent resemblance. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Neuromorphic Configurable Architecture for Robust Motion Estimation

    Directory of Open Access Journals (Sweden)

    Guillermo Botella

    2008-01-01

    Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

  3. Multivariate Analysis Techniques for Optimal Vision System Design

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara

    The present thesis considers optimization of the spectral vision systems used for quality inspection of food items. The relationship between food quality, vision based techniques and spectral signature are described. The vision instruments for food analysis as well as datasets of the food items...... used in this thesis are described. The methodological strategies are outlined including sparse regression and pre-processing based on feature selection and extraction methods, supervised versus unsupervised analysis and linear versus non-linear approaches. One supervised feature selection algorithm...... (SSPCA) and DCT based characterization of the spectral diffused reflectance images for wavelength selection and discrimination. These methods together with some other state-of-the-art statistical and mathematical analysis techniques are applied on datasets of different food items; meat, diaries, fruits...

  4. Computer Vision Systems for Hardwood Logs and Lumber

    Science.gov (United States)

    Philip A. Araman; Tai-Hoon Cho; D. Zhu; R. Conners

    1991-01-01

    Computer vision systems being developed at Virginia Tech University with the support and cooperation from the U.S. Forest Service are presented. Researchers at Michigan State University, West Virginia University, and Mississippi State University are also members of the research team working on various parts of this research. Our goals are to help U.S. hardwood...

  5. Vision Aided State Estimation for Helicopter Slung Load System

    DEFF Research Database (Denmark)

    Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders

    2007-01-01

    This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4...

  6. A vision based row detection system for sugar beet

    NARCIS (Netherlands)

    Bakker, T.; Wouters, H.; Asselt, van C.J.; Bontsema, J.; Tang, L.; Müller, J.; Straten, van G.

    2008-01-01

    One way of guiding autonomous vehicles through the field is using a vision based row detection system. A new approach for row recognition is presented which is based on grey-scale Hough transform on intelligently merged images resulting in a considerable improvement of the speed of image processing.

  7. Robot path planning using expert systems and machine vision

    Science.gov (United States)

    Malone, Denis E.; Friedrich, Werner E.

    1992-02-01

    This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.

  8. Utilizing Robot Operating System (ROS) in Robot Vision and Control

    Science.gov (United States)

    2015-09-01

    Palmer, “Development of a navigation system for semi-autonomous operation of wheelchairs,” in Proc. of the 8th IEEE/ASME Int. Conf. on Mechatronic ...and Embedded Systems and Applications, Suzhou, China, 2012, pp. 257-262. [30] G. Grisetti, C. Stachniss, and W. Burgard, “Improving grid-based SLAM...OPERATING SYSTEM (ROS) IN ROBOT VISION AND CONTROL by Joshua S. Lum September 2015 Thesis Advisor: Xiaoping Yun Co-Advisor: Zac Staples

  9. Computational intelligence and neuromorphic computing potential for cybersecurity applications

    Science.gov (United States)

    Pino, Robinson E.; Shevenell, Michael J.; Cam, Hasan; Mouallem, Pierre; Shumaker, Justin L.; Edwards, Arthur H.

    2013-05-01

    In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neurobiological processes and form the foundation for intelligent system architectures.

  10. Neuromorphic computing enabled by physics of electron spins: Prospects and perspectives

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2018-03-01

    “Spintronics” refers to the understanding of the physics of electron spin-related phenomena. While most of the significant advancements in this field has been driven primarily by memory, recent research has demonstrated that various facets of the underlying physics of spin transport and manipulation can directly mimic the functionalities of the computational primitives in neuromorphic computation, i.e., the neurons and synapses. Given the potential of these spintronic devices to implement bio-mimetic computations at very low terminal voltages, several spin-device structures have been proposed as the core building blocks of neuromorphic circuits and systems to implement brain-inspired computing. Such an approach is expected to play a key role in circumventing the problems of ever-increasing power dissipation and hardware requirements for implementing neuro-inspired algorithms in conventional digital CMOS technology. Perspectives on spin-enabled neuromorphic computing, its status, and challenges and future prospects are outlined in this review article.

  11. Accurate Localization of Communicant Vehicles using GPS and Vision Systems

    Directory of Open Access Journals (Sweden)

    Georges CHALLITA

    2009-07-01

    Full Text Available The new generation of ADAS systems based on cooperation between vehicles can offer serious perspectives to the road security. The inter-vehicle cooperation is made possible thanks to the revolution in the wireless mobile ad hoc network. In this paper, we will develop a system that will minimize the imprecision of the GPS used to car tracking, based on the data given by the GPS which means the coordinates and speed in addition to the use of the vision data that will be collected from the loading system in the vehicle (camera and processor. Localization information can be exchanged between the vehicles through a wireless communication device. The creation of the system must adopt the Monte Carlo Method or what we call a particle filter for the treatment of the GPS data and vision data. An experimental study of this system is performed on our fleet of experimental communicating vehicles.

  12. Monitoring system of multiple fire fighting based on computer vision

    Science.gov (United States)

    Li, Jinlong; Wang, Li; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

    2010-10-01

    With the high demand of fire control in spacious buildings, computer vision is playing a more and more important role. This paper presents a new monitoring system of multiple fire fighting based on computer vision and color detection. This system can adjust to the fire position and then extinguish the fire by itself. In this paper, the system structure, working principle, fire orientation, hydrant's angle adjusting and system calibration are described in detail; also the design of relevant hardware and software is introduced. At the same time, the principle and process of color detection and image processing are given as well. The system runs well in the test, and it has high reliability, low cost, and easy nodeexpanding, which has a bright prospect of application and popularization.

  13. Neuromorphic meets neuromechanics, part I: the methodology and implementation

    Science.gov (United States)

    Niu, Chuanxin M.; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence D.; Valero-Cuevas, Francisco J.

    2017-04-01

    Objective: One goal of neuromorphic engineering is to create ‘realistic’ robotic systems that interact with the physical world by adopting neuromechanical principles from biology. Critical to this is the methodology to implement the spinal circuitry responsible for the behavior of afferented muscles. At its core, muscle afferentation is the closed-loop behavior arising from the interactions among populations of muscle spindle afferents, alpha and gamma motoneurons, and muscle fibers to enable useful behaviors. Approach. We used programmable very- large-scale-circuit (VLSI) hardware to implement simple models of spiking neurons, skeletal muscles, muscle spindle proprioceptors, alpha-motoneuron recruitment, gamma motoneuron control of spindle sensitivity, and the monosynaptic circuitry connecting them. This multi-scale system of populations of spiking neurons emulated the physiological properties of a pair of antagonistic afferented mammalian muscles (each simulated by 1024 alpha- and gamma-motoneurones) acting on a joint via long tendons. Main results. This integrated system was able to maintain a joint angle, and reproduced stretch reflex responses even when driving the nonlinear biomechanics of an actual cadaveric finger. Moreover, this system allowed us to explore numerous values and combinations of gamma-static and gamma-dynamic gains when driving a robotic finger, some of which replicated some human pathological conditions. Lastly, we explored the behavioral consequences of adopting three alternative models of isometric muscle force production. We found that the dynamic responses to rate-coded spike trains produce force ramps that can be very sensitive to tendon elasticity, especially at high force output. Significance. Our methodology produced, to our knowledge, the first example of an autonomous, multi-scale, neuromorphic, neuromechanical system capable of creating realistic reflex behavior in cadaveric fingers. This research platform allows us to explore

  14. Intelligent vision system for autonomous vehicle operations

    Science.gov (United States)

    Scholl, Marija S.

    1991-01-01

    A complex optical system consisting of a 4f optical correlator with programmatic filters under the control of a digital on-board computer that operates at video rates for filter generation, storage, and management is described.

  15. Robust adaptive optics systems for vision science

    Science.gov (United States)

    Burns, S. A.; de Castro, A.; Sawides, L.; Luo, T.; Sapoznik, K.

    2018-02-01

    Adaptive Optics (AO) is of growing importance for understanding the impact of retinal and systemic diseases on the retina. While AO retinal imaging in healthy eyes is now routine, AO imaging in older eyes and eyes with optical changes to the anterior eye can be difficult and requires a control and an imaging system that is resilient when there is scattering and occlusion from the cornea and lens, as well as in the presence of irregular and small pupils. Our AO retinal imaging system combines evaluation of local image quality of the pupil, with spatially programmable detection. The wavefront control system uses a woofer tweeter approach, combining an electromagnetic mirror and a MEMS mirror and a single Shack Hartmann sensor. The SH sensor samples an 8 mm exit pupil and the subject is aligned to a region within this larger system pupil using a chin and forehead rest. A spot quality metric is calculated in real time for each lenslet. Individual lenslets that do not meet the quality metric are eliminated from the processing. Mirror shapes are smoothed outside the region of wavefront control when pupils are small. The system allows imaging even with smaller irregular pupils, however because the depth of field increases under these conditions, sectioning performance decreases. A retinal conjugate micromirror array selectively directs mid-range scatter to additional detectors. This improves detection of retinal capillaries even when the confocal image has poorer image quality that includes both photoreceptors and blood vessels.

  16. Fiber optic coherent laser radar 3D vision system

    International Nuclear Information System (INIS)

    Clark, R.B.; Gallman, P.G.; Slotwinski, A.R.; Wagner, K.; Weaver, S.; Xu, Jieping

    1996-01-01

    This CLVS will provide a substantial advance in high speed computer vision performance to support robotic Environmental Management (EM) operations. This 3D system employs a compact fiber optic based scanner and operator at a 128 x 128 pixel frame at one frame per second with a range resolution of 1 mm over its 1.5 meter working range. Using acousto-optic deflectors, the scanner is completely randomly addressable. This can provide live 3D monitoring for situations where it is necessary to update once per second. This can be used for decontamination and decommissioning operations in which robotic systems are altering the scene such as in waste removal, surface scarafacing, or equipment disassembly and removal. The fiber- optic coherent laser radar based system is immune to variations in lighting, color, or surface shading, which have plagued the reliability of existing 3D vision systems, while providing substantially superior range resolution

  17. A machine vision system for the calibration of digital thermometers

    International Nuclear Information System (INIS)

    Vázquez-Fernández, Esteban; Dacal-Nieto, Angel; González-Jorge, Higinio; Alvarez-Valado, Victor; Martín, Fernando; Formella, Arno

    2009-01-01

    Automation is a key point in many industrial tasks such as calibration and metrology. In this context, machine vision has shown to be a useful tool for automation support, especially when there is no other option available. A system for the calibration of portable measurement devices has been developed. The system uses machine vision to obtain the numerical values shown by displays. A new approach based on human perception of digits, which works in parallel with other more classical classifiers, has been created. The results show the benefits of the system in terms of its usability and robustness, obtaining a success rate higher than 99% in display recognition. The system saves time and effort, and offers the possibility of scheduling calibration tasks without excessive attention by the laboratory technicians

  18. Machine vision system for remote inspection in hazardous environments

    International Nuclear Information System (INIS)

    Mukherjee, J.K.; Krishna, K.Y.V.; Wadnerkar, A.

    2011-01-01

    Visual Inspection of radioactive components need remote inspection systems for human safety and equipment (CCD imagers) protection from radiation. Elaborate view transport optics is required to deliver images at safe areas while maintaining fidelity of image data. Automation of the system requires robots to operate such equipment. A robotized periscope has been developed to meet the challenge of remote safe viewing and vision based inspection. (author)

  19. Integration and coordination in a cognitive vision system

    OpenAIRE

    Wrede, Sebastian; Hanheide, Marc; Wachsmuth, Sven; Sagerer, Gerhard

    2006-01-01

    In this paper, we present a case study that exemplifies general ideas of system integration and coordination. The application field of assistant technology provides an ideal test bed for complex computer vision systems including real-time components, human-computer interaction, dynamic 3-d environments, and information retrieval aspects. In our scenario the user is wearing an augmented reality device that supports her/him in everyday tasks by presenting information tha...

  20. Nanomedical device and systems design challenges, possibilities, visions

    CERN Document Server

    2014-01-01

    Nanomedical Device and Systems Design: Challenges, Possibilities, Visions serves as a preliminary guide toward the inspiration of specific investigative pathways that may lead to meaningful discourse and significant advances in nanomedicine/nanotechnology. This volume considers the potential of future innovations that will involve nanomedical devices and systems. It endeavors to explore remarkable possibilities spanning medical diagnostics, therapeutics, and other advancements that may be enabled within this discipline. In particular, this book investigates just how nanomedical diagnostic and

  1. The Systemic Vision of the Educational Learning

    Science.gov (United States)

    Lima, Nilton Cesar; Penedo, Antonio Sergio Torres; de Oliveira, Marcio Mattos Borges; de Oliveira, Sonia Valle Walter Borges; Queiroz, Jamerson Viegas

    2012-01-01

    As the sophistication of technology is increasing, also increased the demand for quality in education. The expectation for quality has promoted broad range of products and systems, including in education. These factors include the increased diversity in the student body, which requires greater emphasis that allows a simple and dynamic model in the…

  2. Flexible Metal Oxide/Graphene Oxide Hybrid Neuromorphic Devices on Flexible Conducting Graphene Substrates

    OpenAIRE

    Wan, Chang Jin; Wang, Wei; Zhu, Li Qiang; Liu, Yang Hui; Feng, Ping; Liu, Zhao Ping; Shi, Yi; Wan, Qing

    2016-01-01

    Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated logics were obtained. A proof-of-principle visual system model for emulating lobula giant motion detector neuron was investigated. Our results are of great interest for flexible neuromorphic cognitive systems.

  3. Low Cost Night Vision System for Intruder Detection

    Science.gov (United States)

    Ng, Liang S.; Yusoff, Wan Azhar Wan; R, Dhinesh; Sak, J. S.

    2016-02-01

    The growth in production of Android devices has resulted in greater functionalities as well as lower costs. This has made previously more expensive systems such as night vision affordable for more businesses and end users. We designed and implemented robust and low cost night vision systems based on red-green-blue (RGB) colour histogram for a static camera as well as a camera on an unmanned aerial vehicle (UAV), using OpenCV library on Intel compatible notebook computers, running Ubuntu Linux operating system, with less than 8GB of RAM. They were tested against human intruders under low light conditions (indoor, outdoor, night time) and were shown to have successfully detected the intruders.

  4. A vision fusion treatment system based on ATtiny26L

    Science.gov (United States)

    Zhang, Xiaoqing; Zhang, Chunxi; Wang, Jiqiang

    2006-11-01

    Vision fusion treatment is an important and effective project to strabismus children. The vision fusion treatment system based on the principle for eyeballs to follow the moving visual survey pole is put forward first. In this system the original position of visual survey pole is about 35 centimeters far from patient's face before its moving to the middle position between the two eyeballs. The eyeballs of patient will follow the movement of the visual survey pole. When they can't follow, one or two eyeballs will turn to other position other than the visual survey pole. This displacement is recorded every time. A popular single chip microcomputer ATtiny26L is used in this system, which has a PWM output signal to control visual survey pole to move with continuously variable speed. The movement of visual survey pole accords to the modulating law of eyeballs to follow visual survey pole.

  5. Computer Vision for Artificially Intelligent Robotic Systems

    Science.gov (United States)

    Ma, Chialo; Ma, Yung-Lung

    1987-04-01

    In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main

  6. A vision system for a Mars rover

    Science.gov (United States)

    Wilcox, Brian H.; Gennery, Donald B.; Mishkin, Andrew H.; Cooper, Brian K.; Lawton, Teri B.; Lay, N. Keith; Katzmann, Steven P.

    1988-01-01

    A Mars rover must be able to sense its local environment with sufficient resolution and accuracy to avoid local obstacles and hazards while moving a significant distance each day. Power efficiency and reliability are extremely important considerations, making stereo correlation an attractive method of range sensing compared to laser scanning, if the computational load and correspondence errors can be handled. Techniques for treatment of these problems, including the use of more than two cameras to reduce correspondence errors and possibly to limit the computational burden of stereo processing, have been tested at JPL. Once a reliable range map is obtained, it must be transformed to a plan view and compared to a stored terrain database, in order to refine the estimated position of the rover and to improve the database. The slope and roughness of each terrain region are computed, which form the basis for a traversability map allowing local path planning. Ongoing research and field testing of such a system is described.

  7. Embedded active vision system based on an FPGA architecture

    OpenAIRE

    Chalimbaud , Pierre; Berry , François

    2006-01-01

    International audience; In computer vision and more particularly in vision processing, the impressive evolution of algorithms and the emergence of new techniques dramatically increase algorithm complexity. In this paper, a novel FPGA-based architecture dedicated to active vision (and more precisely early vision) is proposed. Active vision appears as an alternative approach to deal with artificial vision problems. The central idea is to take into account the perceptual aspects of visual tasks,...

  8. A smart sensor-based vision system: implementation and evaluation

    International Nuclear Information System (INIS)

    Elouardi, A; Bouaziz, S; Dupret, A; Lacassagne, L; Klein, J O; Reynaud, R

    2006-01-01

    One of the methods of solving the computational complexity of image-processing is to perform some low-level computations on the sensor focal plane. This paper presents a vision system based on a smart sensor. PARIS1 (Programmable Analog Retina-like Image Sensor1) is the first prototype used to evaluate the architecture of an on-chip vision system based on such a sensor coupled with a microcontroller. The smart sensor integrates a set of analog and digital computing units. This architecture paves the way for a more compact vision system and increases the performances reducing the data flow exchanges with a microprocessor in control. A system has been implemented as a proof-of-concept and has enabled us to evaluate the performance requirements for a possible integration of a microcontroller on the same chip. The used approach is compared with two architectures implementing CMOS active pixel sensors (APS) and interfaced to the same microcontroller. The comparison is related to image processing computation time, processing reliability, programmability, precision, bandwidth and subsequent stages of computations

  9. A smart sensor-based vision system: implementation and evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Elouardi, A; Bouaziz, S; Dupret, A; Lacassagne, L; Klein, J O; Reynaud, R [Institute of Fundamental Electronics, Bat. 220, Paris XI University, 91405 Orsay (France)

    2006-04-21

    One of the methods of solving the computational complexity of image-processing is to perform some low-level computations on the sensor focal plane. This paper presents a vision system based on a smart sensor. PARIS1 (Programmable Analog Retina-like Image Sensor1) is the first prototype used to evaluate the architecture of an on-chip vision system based on such a sensor coupled with a microcontroller. The smart sensor integrates a set of analog and digital computing units. This architecture paves the way for a more compact vision system and increases the performances reducing the data flow exchanges with a microprocessor in control. A system has been implemented as a proof-of-concept and has enabled us to evaluate the performance requirements for a possible integration of a microcontroller on the same chip. The used approach is compared with two architectures implementing CMOS active pixel sensors (APS) and interfaced to the same microcontroller. The comparison is related to image processing computation time, processing reliability, programmability, precision, bandwidth and subsequent stages of computations.

  10. Sensory systems II senses other than vision

    CERN Document Server

    Wolfe, Jeremy M

    1988-01-01

    This series of books, "Readings from the Encyclopedia of Neuroscience." consists of collections of subject-clustered articles taken from the Encyclopedia of Neuroscience. The Encyclopedia of Neuroscience is a reference source and compendium of more than 700 articles written by world authorities and covering all of neuroscience. We define neuroscience broadly as including all those fields that have as a primary goal the under­ standing of how the brain and nervous system work to mediate/control behavior, including the mental behavior of humans. Those interested in specific aspects of the neurosciences, particular subject areas or specialties, can of course browse through the alphabetically arranged articles of the En­ cyclopedia or use its index to find the topics they wish to read. However. for those readers-students, specialists, or others-who will find it useful to have collections of subject-clustered articles from the Encyclopedia, we issue this series of "Readings" in paperback. Students in neuroscienc...

  11. Machine vision system for automated detection of stained pistachio nuts

    Science.gov (United States)

    Pearson, Tom C.

    1995-01-01

    A machine vision system was developed to separate stained pistachio nuts, which comprise of about 5% of the California crop, from unstained nuts. The system may be used to reduce labor involved with manual grading or to remove aflatoxin contaminated product from low grade process streams. The system was tested on two different pistachio process streams: the bi- chromatic color sorter reject stream and the small nut shelling stock stream. The system had a minimum overall error rate of 14% for the bi-chromatic sorter reject stream and 15% for the small shelling stock stream.

  12. Vision-based pedestrian protection systems for intelligent vehicles

    CERN Document Server

    Geronimo, David

    2013-01-01

    Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human's appearance, not only in

  13. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  14. International Border Management Systems (IBMS) Program : visions and strategies.

    Energy Technology Data Exchange (ETDEWEB)

    McDaniel, Michael; Mohagheghi, Amir Hossein

    2011-02-01

    Sandia National Laboratories (SNL), International Border Management Systems (IBMS) Program is working to establish a long-term border security strategy with United States Central Command (CENTCOM). Efforts are being made to synthesize border security capabilities and technologies maintained at the Laboratories, and coordinate with subject matter expertise from both the New Mexico and California offices. The vision for SNL is to provide science and technology support for international projects and engagements on border security.

  15. A robust embedded vision system feasible white balance algorithm

    Science.gov (United States)

    Wang, Yuan; Yu, Feihong

    2018-01-01

    White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

  16. Vector disparity sensor with vergence control for active vision systems.

    Science.gov (United States)

    Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P; Ros, Eduardo

    2012-01-01

    This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.

  17. Autonomous navigation of the vehicle with vision system. Vision system wo motsu sharyo no jiritsu soko seigyo

    Energy Technology Data Exchange (ETDEWEB)

    Yatabe, T.; Hirose, T.; Tsugawa, S. (Mechanical Engineering Laboratory, Tsukuba (Japan))

    1991-11-10

    As part of the automatic driving system researches, a pilot driverless automobile was built and discussed, which is equipped with obstacle detection and automatic navigating functions without depending on ground facilities including guiding cables. A small car was mounted with a vision system to recognize obstacles three-dimensionally by means of two TV cameras, and a dead reckoning system to calculate the car position and direction from speeds of the rear wheels on a real time basis. The control algorithm, which recognizes obstacles and road range on the vision and drives the car automatically, uses a table-look-up method that retrieves a table stored with the necessary driving amount based on data from the vision system. The steering uses the target point following method algorithm provided that the has a map. As a result of driving tests, useful knowledges were obtained that the system meets the basic functions, but needs a few improvements because of it being an open loop. 36 refs., 22 figs., 2 tabs.

  18. Dense range map reconstruction from a versatile robotic sensor system with an active trinocular vision and a passive binocular vision.

    Science.gov (United States)

    Kim, Min Young; Lee, Hyunkee; Cho, Hyungsuck

    2008-04-10

    One major research issue associated with 3D perception by robotic systems is the creation of efficient sensor systems that can generate dense range maps reliably. A visual sensor system for robotic applications is developed that is inherently equipped with two types of sensor, an active trinocular vision and a passive stereo vision. Unlike in conventional active vision systems that use a large number of images with variations of projected patterns for dense range map acquisition or from conventional passive vision systems that work well on specific environments with sufficient feature information, a cooperative bidirectional sensor fusion method for this visual sensor system enables us to acquire a reliable dense range map using active and passive information simultaneously. The fusion algorithms are composed of two parts, one in which the passive stereo vision helps active vision and the other in which the active trinocular vision helps the passive one. The first part matches the laser patterns in stereo laser images with the help of intensity images; the second part utilizes an information fusion technique using the dynamic programming method in which image regions between laser patterns are matched pixel-by-pixel with help of the fusion results obtained in the first part. To determine how the proposed sensor system and fusion algorithms can work in real applications, the sensor system is implemented on a robotic system, and the proposed algorithms are applied. A series of experimental tests is performed for a variety of configurations of robot and environments. The performance of the sensor system is discussed in detail.

  19. A Ship Cargo Hold Inspection Approach Using Laser Vision Systems

    OpenAIRE

    SHEN Yang; ZHAO Ning; LIU Haiwei; MI Chao

    2013-01-01

    Our paper represents a vision system based on the laser measurement system (LMS) for bulk ship inspection. The LMS scanner with 2-axis servo system is installed on the ship loader to build the shape of the ship. Then, a group of real-time image processing algorithms are implemented to compute the shape of the cargo hold, the inclination angle of the ship and the relative position between the ship loader and the cargo hold. Based on those computed inspection data of the ship, the ship loader c...

  20. Fiber optic coherent laser radar 3d vision system

    International Nuclear Information System (INIS)

    Sebastian, R.L.; Clark, R.B.; Simonson, D.L.

    1994-01-01

    Recent advances in fiber optic component technology and digital processing components have enabled the development of a new 3D vision system based upon a fiber optic FMCW coherent laser radar. The approach includes a compact scanner with no moving parts capable of randomly addressing all pixels. The system maintains the immunity to lighting and surface shading conditions which is characteristic of coherent laser radar. The random pixel addressability allows concentration of scanning and processing on the active areas of a scene, as is done by the human eye-brain system

  1. Development of machine vision system for PHWR fuel pellet inspection

    Energy Technology Data Exchange (ETDEWEB)

    Kamalesh Kumar, B.; Reddy, K.S.; Lakshminarayana, A.; Sastry, V.S.; Ramana Rao, A.V. [Nuclear Fuel Complex, Hyderabad, Andhra Pradesh (India); Joshi, M.; Deshpande, P.; Navathe, C.P.; Jayaraj, R.N. [Raja Ramanna Centre for Advanced Technology, Indore, Madhya Pradesh (India)

    2008-07-01

    Nuclear Fuel Complex, a constituent of Department of Atomic Energy; India is responsible for manufacturing nuclear fuel in India . Over a million Uranium-di-oxide pellets fabricated per annum need visual inspection . In order to overcome the limitations of human based visual inspection, NFC has undertaken the development of machine vision system. The development involved designing various subsystems viz. mechanical and control subsystem for handling and rotation of fuel pellets, lighting subsystem for illumination, image acquisition system, and image processing system and integration. This paper brings out details of various subsystems and results obtained from the trials conducted. (author)

  2. Computer vision in roadway transportation systems: a survey

    Science.gov (United States)

    Loce, Robert P.; Bernal, Edgar A.; Wu, Wencheng; Bala, Raja

    2013-10-01

    There is a worldwide effort to apply 21st century intelligence to evolving our transportation networks. The goals of smart transportation networks are quite noble and manifold, including safety, efficiency, law enforcement, energy conservation, and emission reduction. Computer vision is playing a key role in this transportation evolution. Video imaging scientists are providing intelligent sensing and processing technologies for a wide variety of applications and services. There are many interesting technical challenges including imaging under a variety of environmental and illumination conditions, data overload, recognition and tracking of objects at high speed, distributed network sensing and processing, energy sources, as well as legal concerns. This paper presents a survey of computer vision techniques related to three key problems in the transportation domain: safety, efficiency, and security and law enforcement. A broad review of the literature is complemented by detailed treatment of a few selected algorithms and systems that the authors believe represent the state-of-the-art.

  3. Intelligent Vision System for Door Sensing Mobile Robot

    Directory of Open Access Journals (Sweden)

    Jharna Majumdar

    2012-08-01

    Full Text Available Wheeled Mobile Robots find numerous applications in the Indoor man made structured environments. In order to operate effectively, the robots must be capable of sensing its surroundings. Computer Vision is one of the prime research areas directed towards achieving these sensing capabilities. In this paper, we present a Door Sensing Mobile Robot capable of navigating in the indoor environment. A robust and inexpensive approach for recognition and classification of the door, based on monocular vision system helps the mobile robot in decision making. To prove the efficacy of the algorithm we have designed and developed a ‘Differentially’ Driven Mobile Robot. A wall following behavior using Ultra Sonic range sensors is employed by the mobile robot for navigation in the corridors.  Field Programmable Gate Arrays (FPGA have been used for the implementation of PD Controller for wall following and PID Controller to control the speed of the Geared DC Motor.

  4. A stereo vision-based obstacle detection system in vehicles

    Science.gov (United States)

    Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

    2008-02-01

    Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

  5. Control system for solar tracking based on artificial vision; Sistema de control para seguimiento solar basado en vision artificial

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco Ramirez, Jesus Horacio; Anaya Perez, Maria Elena; Benitez Baltazar, Victor Hugo [Universidad de onora, Hermosillo, Sonora (Mexico)]. E-mail: jpacheco@industrial.uson.mx; meanaya@industrial.uson.mx; vbenitez@industrial.uson.mx

    2010-11-15

    This work shows how artificial vision feedback can be applied to control systems. The control is applied to a solar panel in order to track the sun position. The algorithms to calculate the position of the sun and the image processing are developed in LabView. The responses obtained from the control show that it is possible to use vision for a control scheme in closed loop. [Spanish] El presente trabajo muestra la manera en la cual un sistema de control puede ser retroalimentado mediante vision artificial. El control es aplicado en un panel solar para realizar el seguimiento del sol a lo largo del dia. Los algoritmos para calcular la posicion del sol y para el tratamiento de la imagen fueron desarrollados en LabView. Las respuestas obtenidas del control muestran que es posible utilizar vision para un esquema de control en lazo cerrado.

  6. Machine vision system for measuring conifer seedling morphology

    Science.gov (United States)

    Rigney, Michael P.; Kranzler, Glenn A.

    1995-01-01

    A PC-based machine vision system providing rapid measurement of bare-root tree seedling morphological features has been designed. The system uses backlighting and a 2048-pixel line- scan camera to acquire images with transverse resolutions as high as 0.05 mm for precise measurement of stem diameter. Individual seedlings are manually loaded on a conveyor belt and inspected by the vision system in less than 0.25 seconds. Designed for quality control and morphological data acquisition by nursery personnel, the system provides a user-friendly, menu-driven graphical interface. The system automatically locates the seedling root collar and measures stem diameter, shoot height, sturdiness ratio, root mass length, projected shoot and root area, shoot-root area ratio, and percent fine roots. Sample statistics are computed for each measured feature. Measurements for each seedling may be stored for later analysis. Feature measurements may be compared with multi-class quality criteria to determine sample quality or to perform multi-class sorting. Statistical summary and classification reports may be printed to facilitate the communication of quality concerns with grading personnel. Tests were conducted at a commercial forest nursery to evaluate measurement precision. Four quality control personnel measured root collar diameter, stem height, and root mass length on each of 200 conifer seedlings. The same seedlings were inspected four times by the machine vision system. Machine stem diameter measurement precision was four times greater than that of manual measurements. Machine and manual measurements had comparable precision for shoot height and root mass length.

  7. A robust sound perception model suitable for neuromorphic implementation.

    Science.gov (United States)

    Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

    2013-01-01

    We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  8. A Robust Sound Perception Model Suitable for Neuromorphic Implementation

    Directory of Open Access Journals (Sweden)

    Martin eCoath

    2014-01-01

    Full Text Available We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analogue/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity.Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems.We analyse the variability of the response of the network to `noisy' stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  9. On Multiple AER Handshaking Channels Over High-Speed Bit-Serial Bidirectional LVDS Links With Flow-Control and Clock-Correction on Commercial FPGAs for Scalable Neuromorphic Systems.

    Science.gov (United States)

    Yousefzadeh, Amirreza; Jablonski, Miroslaw; Iakymchuk, Taras; Linares-Barranco, Alejandro; Rosado, Alfredo; Plana, Luis A; Temple, Steve; Serrano-Gotarredona, Teresa; Furber, Steve B; Linares-Barranco, Bernabe

    2017-10-01

    Address event representation (AER) is a widely employed asynchronous technique for interchanging "neural spikes" between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), which is typically communicated through a high-speed digital bus, thus time-multiplexing a high number of neural connections. Conventional AER links use parallel physical wires together with a pair of handshaking signals (request and acknowledge). In this paper, we present a fully serial implementation using bidirectional SATA connectors with a pair of low-voltage differential signaling (LVDS) wires for each direction. The proposed implementation can multiplex a number of conventional parallel AER links for each physical LVDS connection. It uses flow control, clock correction, and byte alignment techniques to transmit 32-bit address events reliably over multiplexed serial connections. The setup has been tested using commercial Spartan6 FPGAs attaining a maximum event transmission speed of 75 Meps (Mega events per second) for 32-bit events at a line rate of 3.0 Gbps. Full HDL codes (vhdl/verilog) and example demonstration codes for the SpiNNaker platform will be made available.

  10. Low Cost Vision Based Personal Mobile Mapping System

    Directory of Open Access Journals (Sweden)

    M. M. Amami

    2014-03-01

    Full Text Available Mobile mapping systems (MMS can be used for several purposes, such as transportation, highway infrastructure mapping and GIS data collecting. However, the acceptance of these systems is not wide spread and their use is still limited due the high cost and dependency on the Global Navigation Satellite System (GNSS. A low cost vision based personal MMS has been produced with an aim to overcome these limitations. The system has been designed to depend mainly on cameras and use of low cost GNSS and inertial sensors to provide a bundle adjustment solution with initial values. The system has the potential to be used indoor and outdoor. The system has been tested indoors and outdoors with different GPS coverage, surrounded features, and narrow and curvy paths. Tests show that the system is able to work in such environments providing 3D coordinates of better than 10 cm accuracy.

  11. Low Cost Vision Based Personal Mobile Mapping System

    Science.gov (United States)

    Amami, M. M.; Smith, M. J.; Kokkas, N.

    2014-03-01

    Mobile mapping systems (MMS) can be used for several purposes, such as transportation, highway infrastructure mapping and GIS data collecting. However, the acceptance of these systems is not wide spread and their use is still limited due the high cost and dependency on the Global Navigation Satellite System (GNSS). A low cost vision based personal MMS has been produced with an aim to overcome these limitations. The system has been designed to depend mainly on cameras and use of low cost GNSS and inertial sensors to provide a bundle adjustment solution with initial values. The system has the potential to be used indoor and outdoor. The system has been tested indoors and outdoors with different GPS coverage, surrounded features, and narrow and curvy paths. Tests show that the system is able to work in such environments providing 3D coordinates of better than 10 cm accuracy.

  12. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator.

    Science.gov (United States)

    Wang, Runchun M; Thakur, Chetan S; van Schaik, André

    2018-01-01

    This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  13. 3D vision system for intelligent milking robot automation

    Science.gov (United States)

    Akhloufi, M. A.

    2013-12-01

    In a milking robot, the correct localization and positioning of milking teat cups is of very high importance. The milking robots technology has not changed since a decade and is based primarily on laser profiles for teats approximate positions estimation. This technology has reached its limit and does not allow optimal positioning of the milking cups. Also, in the presence of occlusions, the milking robot fails to milk the cow. These problems, have economic consequences for producers and animal health (e.g. development of mastitis). To overcome the limitations of current robots, we have developed a new system based on 3D vision, capable of efficiently positioning the milking cups. A prototype of an intelligent robot system based on 3D vision for real-time positioning of a milking robot has been built and tested under various conditions on a synthetic udder model (in static and moving scenarios). Experimental tests, were performed using 3D Time-Of-Flight (TOF) and RGBD cameras. The proposed algorithms permit the online segmentation of teats by combing 2D and 3D visual information. The obtained results permit the teat 3D position computation. This information is then sent to the milking robot for teat cups positioning. The vision system has a real-time performance and monitors the optimal positioning of the cups even in the presence of motion. The obtained results, with both TOF and RGBD cameras, show the good performance of the proposed system. The best performance was obtained with RGBD cameras. This latter technology will be used in future real life experimental tests.

  14. IMPROVING CAR NAVIGATION WITH A VISION-BASED SYSTEM

    Directory of Open Access Journals (Sweden)

    H. Kim

    2015-08-01

    Full Text Available The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.

  15. Improving Car Navigation with a Vision-Based System

    Science.gov (United States)

    Kim, H.; Choi, K.; Lee, I.

    2015-08-01

    The real-time acquisition of the accurate positions is very important for the proper operations of driver assistance systems or autonomous vehicles. Since the current systems mostly depend on a GPS and map-matching technique, they show poor and unreliable performance in blockage and weak areas of GPS signals. In this study, we propose a vision oriented car navigation method based on sensor fusion with a GPS and in-vehicle sensors. We employed a single photo resection process to derive the position and attitude of the camera and thus those of the car. This image georeferencing results are combined with other sensory data under the sensor fusion framework for more accurate estimation of the positions using an extended Kalman filter. The proposed system estimated the positions with an accuracy of 15 m although GPS signals are not available at all during the entire test drive of 15 minutes. The proposed vision based system can be effectively utilized for the low-cost but high-accurate and reliable navigation systems required for intelligent or autonomous vehicles.

  16. Programming time-multiplexed reconfigurable hardware using a scalable neuromorphic compiler.

    Science.gov (United States)

    Minkovich, Kirill; Srinivasa, Narayan; Cruz-Albrecht, Jose M; Cho, Youngkwan; Nogin, Aleksey

    2012-06-01

    Scalability and connectivity are two key challenges in designing neuromorphic hardware that can match biological levels. In this paper, we describe a neuromorphic system architecture design that addresses an approach to meet these challenges using traditional complementary metal-oxide-semiconductor (CMOS) hardware. A key requirement in realizing such neural architectures in hardware is the ability to automatically configure the hardware to emulate any neural architecture or model. The focus for this paper is to describe the details of such a programmable front-end. This programmable front-end is composed of a neuromorphic compiler and a digital memory, and is designed based on the concept of synaptic time-multiplexing (STM). The neuromorphic compiler automatically translates any given neural architecture to hardware switch states and these states are stored in digital memory to enable desired neural architectures. STM enables our proposed architecture to address scalability and connectivity using traditional CMOS hardware. We describe the details of the proposed design and the programmable front-end, and provide examples to illustrate its capabilities. We also provide perspectives for future extensions and potential applications.

  17. Vision and dual IMU integrated attitude measurement system

    Science.gov (United States)

    Guo, Xiaoting; Sun, Changku; Wang, Peng; Lu, Huang

    2018-01-01

    To determination relative attitude between two space objects on a rocking base, an integrated system based on vision and dual IMU (inertial determination unit) is built up. The determination system fuses the attitude information of vision with the angular determinations of dual IMU by extended Kalman filter (EKF) to obtain the relative attitude. One IMU (master) is attached to the measured motion object and the other (slave) to the rocking base. As the determination output of inertial sensor is relative to inertial frame, thus angular rate of the master IMU includes not only motion of the measured object relative to inertial frame but also the rocking base relative to inertial frame, where the latter can be seen as redundant harmful movement information for relative attitude determination between the measured object and the rocking base. The slave IMU here assists to remove the motion information of rocking base relative to inertial frame from the master IMU. The proposed integrated attitude determination system is tested on practical experimental platform. And experiment results with superior precision and reliability show the feasibility and effectiveness of the proposed attitude determination system.

  18. VISION: a Versatile and Innovative SIlicOn tracking system

    CERN Document Server

    Lietti, Daniela; Vallazza, Erik

    This thesis work focuses on the study of the performance of different tracking and profilometry systems (the so-called INSULAB, INSUbria LABoratory, and VISION, Versatile and Innovative SIlicON, Telescopes) used in the last years by the NTA-HCCC, the COHERENT (COHERENT effects in crystals for the physics of accelerators), ICE-RAD (Interaction in Crystals for Emission of RADiation) and CHANEL (CHAnneling of NEgative Leptons) experiments, four collaborations of the INFN (Istituto Nazionale di Fisica Nucleare) dedicated to the research in the crystals physics field.

  19. Vision system for measuring wagon buffers’ lateral movements

    Directory of Open Access Journals (Sweden)

    Barjaktarović Marko

    2013-01-01

    Full Text Available This paper presents a vision system designed for measuring horizontal and vertical displacements of a railway wagon body. The model comprises a commercial webcam and a cooperative target of an appropriate shape. The lateral buffer movement is determined by calculating target displacement in real time by processing the camera image in a LabVIEW platform using free OpenCV library. Laboratory experiments demonstrate an accuracy which is better than ±0.5 mm within a 50 mm measuring range.

  20. System of technical vision for autonomous unmanned aerial vehicles

    Science.gov (United States)

    Bondarchuk, A. S.

    2018-05-01

    This paper is devoted to the implementation of image recognition algorithm using the LabVIEW software. The created virtual instrument is designed to detect the objects on the frames from the camera mounted on the UAV. The trained classifier is invariant to changes in rotation, as well as to small changes in the camera's viewing angle. Finding objects in the image using particle analysis, allows you to classify regions of different sizes. This method allows the system of technical vision to more accurately determine the location of the objects of interest and their movement relative to the camera.

  1. Noise-exploitation and adaptation in neuromorphic sensors

    Science.gov (United States)

    Hindo, Thamira; Chakrabartty, Shantanu

    2012-04-01

    Even though current micro-nano fabrication technology has reached integration levels where ultra-sensitive sensors can be fabricated, the sensing performance (resolution per joule) of synthetic systems are still orders of magnitude inferior to those observed in neurobiology. For example, the filiform hairs in crickets operate at fundamental limits of noise; auditory sensors in a parasitoid fly can overcome fundamental limitations to precisely localize ultra-faint acoustic signatures. Even though many of these biological marvels have served as inspiration for different types of neuromorphic sensors, the main focus these designs have been to faithfully replicate the biological functionalities, without considering the constructive role of "noise". In man-made sensors device and sensor noise are typically considered as a nuisance, where as in neurobiology "noise" has been shown to be a computational aid that enables biology to sense and operate at fundamental limits of energy efficiency and performance. In this paper, we describe some of the important noise-exploitation and adaptation principles observed in neurobiology and how they can be systematically used for designing neuromorphic sensors. Our focus will be on two types of noise-exploitation principles, namely, (a) stochastic resonance; and (b) noise-shaping, which are unified within our previously reported framework called Σ▵ learning. As a case-study, we describe the application of Σ▵ learning for the design of a miniature acoustic source localizer whose performance matches that of its biological counterpart(Ormia Ochracea).

  2. Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures

    Directory of Open Access Journals (Sweden)

    Yulia eSandamirskaya

    2014-01-01

    Full Text Available Dynamic Field Theory (DFT is an established framework for modelling embodied cognition. In DFT, elementary cognitive functions such as memory formation, formation of grounded representations, attentional processes, decision making, adaptation, and learning emerge from neuronal dynamics. The basic computational element of this framework is a Dynamic Neural Field (DNF. Under constraints on the time-scale of the dynamics, the DNF is computationally equivalent to a soft winner-take-all (WTA network, which is considered one of the basic computational units in neuronal processing. Recently, it has been shown how a WTA network may be implemented in neuromorphic hardware, such as analogue Very Large Scale Integration (VLSI device. This paper leverages the relationship between DFT and soft WTA networks to systematically revise and integrate established DFT mechanisms that have previously been spread among different architectures. In addition, I also identify some novel computational and architectural mechanisms of DFT which may be implemented in neuromorphic VLSI devices using WTA networks as an intermediate computational layer. These specific mechanisms include the stabilization of working memory, the coupling of sensory systems to motor dynamics, intentionality, and autonomous learning. I further demonstrate how all these elements may be integrated into a unified architecture to generate behavior and autonomous learning.

  3. Research into the Architecture of CAD Based Robot Vision Systems

    Science.gov (United States)

    1988-02-09

    Vision 󈨚 and "Automatic Generation of Recognition Features for Com- puter Vision," Mudge, Turney and Volz, published in Robotica (1987). All of the...Occluded Parts," (T.N. Mudge, J.L. Turney, and R.A. Volz), Robotica , vol. 5, 1987, pp. 117-127. 5. "Vision Algorithms for Hypercube Machines," (T.N. Mudge

  4. Early Cognitive Vision as a Frontend for Cognitive Systems

    DEFF Research Database (Denmark)

    Krüger, Norbert; Pugeault, Nicolas; Baseski, Emre

    We discuss the need of an elaborated in-between stage bridging early vision and cognitive vision which we call `Early Cognitive Vision' (ECV). This stage provides semantically rich, disambiguated and largely task independent scene representations which can be used in many contexts. In addition...

  5. Enhanced/Synthetic Vision Systems - Human factors research and implications for future systems

    Science.gov (United States)

    Foyle, David C.; Ahumada, Albert J.; Larimer, James; Sweet, Barbara T.

    1992-01-01

    This paper reviews recent human factors research studies conducted in the Aerospace Human Factors Research Division at NASA Ames Research Center related to the development and usage of Enhanced or Synthetic Vision Systems. Research discussed includes studies of field of view (FOV), representational differences of infrared (IR) imagery, head-up display (HUD) symbology, HUD advanced concept designs, sensor fusion, and sensor/database fusion and evaluation. Implications for the design and usage of Enhanced or Synthetic Vision Systems are discussed.

  6. Automatic Parking Based on a Bird's Eye View Vision System

    Directory of Open Access Journals (Sweden)

    Chunxiang Wang

    2014-03-01

    Full Text Available This paper aims at realizing an automatic parking method through a bird's eye view vision system. With this method, vehicles can make robust and real-time detection and recognition of parking spaces. During parking process, the omnidirectional information of the environment can be obtained by using four on-board fisheye cameras around the vehicle, which are the main part of the bird's eye view vision system. In order to achieve this purpose, a polynomial fisheye distortion model is firstly used for camera calibration. An image mosaicking method based on the Levenberg-Marquardt algorithm is used to combine four individual images from fisheye cameras into one omnidirectional bird's eye view image. Secondly, features of the parking spaces are extracted with a Radon transform based method. Finally, double circular trajectory planning and a preview control strategy are utilized to realize autonomous parking. Through experimental analysis, we can see that the proposed method can get effective and robust real-time results in both parking space recognition and automatic parking.

  7. Vision-Based SLAM System for Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Rodrigo Munguía

    2016-03-01

    Full Text Available The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs. The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i an orientation sensor (AHRS; (ii a position sensor (GPS; and (iii a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

  8. Vision-Based SLAM System for Unmanned Aerial Vehicles.

    Science.gov (United States)

    Munguía, Rodrigo; Urzua, Sarquis; Bolea, Yolanda; Grau, Antoni

    2016-03-15

    The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

  9. Nonvolatile Memory Materials for Neuromorphic Intelligent Machines.

    Science.gov (United States)

    Jeong, Doo Seok; Hwang, Cheol Seong

    2018-04-18

    Recent progress in deep learning extends the capability of artificial intelligence to various practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis. While such DNN is virtually built on contemporary data centers of the von Neumann architecture, physical (in part) DNN of non-von Neumann architecture, also known as neuromorphic computing, can remarkably improve learning and inference efficiency. Particularly, resistance-based nonvolatile random access memory (NVRAM) highlights its handy and efficient application to the multiply-accumulate (MAC) operation in an analog manner. Here, an overview is given of the available types of resistance-based NVRAMs and their technological maturity from the material- and device-points of view. Examples within the strategy are subsequently addressed in comparison with their benchmarks (virtual DNN in deep learning). A spiking neural network (SNN) is another type of neural network that is more biologically plausible than the DNN. The successful incorporation of resistance-based NVRAM in SNN-based neuromorphic computing offers an efficient solution to the MAC operation and spike timing-based learning in nature. This strategy is exemplified from a material perspective. Intelligent machines are categorized according to their architecture and learning type. Also, the functionality and usefulness of NVRAM-based neuromorphic computing are addressed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Vision-aided inertial navigation system for robotic mobile mapping

    Science.gov (United States)

    Bayoud, Fadi; Skaloud, Jan

    2008-04-01

    A mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable. In this framework, a methodology on the integration of vision and inertial sensors is presented, analysed and tested. The system employs the method of “SLAM: Simultaneous Localisation And Mapping” where the only external input available to the system at the beginning of the mapping mission is a number of features with known coordinates. SLAM is a term used in the robotics community to describe the problem of mapping the environment and at the same time using this map to determine the location of the mapping device. Differing from the robotics approach, the presented development stems from the frameworks of photogrammetry and kinematic geodesy that are merged in two filters that run in parallel: the Least-Squares Adjustment (LSA) for features coordinates determination and the Kalman filter (KF) for navigation correction. To test this approach, a mapping system-prototype comprising two CCD cameras and one Inertial Measurement Unit (IMU) is introduced. Conceptually, the outputs of the LSA photogrammetric resection are used as the external measurements for the KF that corrects the inertial navigation. The filtered position and orientation are subsequently employed in the photogrammetric intersection to map the surrounding features that are used as control points for the resection in the next epoch. We confirm empirically the dependency of navigation performance on the quality of the images and the number of tracked features, as well as on the geometry of the stereo-pair. Due to its autonomous nature, the SLAM's performance is further affected by the quality of IMU initialisation and the a-priory assumptions on error distribution. Using the example of the presented system we show that centimetre accuracy can be achieved in both navigation and mapping when the image geometry is optimal.

  11. Creating photorealistic virtual model with polarization-based vision system

    Science.gov (United States)

    Shibata, Takushi; Takahashi, Toru; Miyazaki, Daisuke; Sato, Yoichi; Ikeuchi, Katsushi

    2005-08-01

    Recently, 3D models are used in many fields such as education, medical services, entertainment, art, digital archive, etc., because of the progress of computational time and demand for creating photorealistic virtual model is increasing for higher reality. In computer vision field, a number of techniques have been developed for creating the virtual model by observing the real object in computer vision field. In this paper, we propose the method for creating photorealistic virtual model by using laser range sensor and polarization based image capture system. We capture the range and color images of the object which is rotated on the rotary table. By using the reconstructed object shape and sequence of color images of the object, parameter of a reflection model are estimated in a robust manner. As a result, then, we can make photorealistic 3D model in consideration of surface reflection. The key point of the proposed method is that, first, the diffuse and specular reflection components are separated from the color image sequence, and then, reflectance parameters of each reflection component are estimated separately. In separation of reflection components, we use polarization filter. This approach enables estimation of reflectance properties of real objects whose surfaces show specularity as well as diffusely reflected lights. The recovered object shape and reflectance properties are then used for synthesizing object images with realistic shading effects under arbitrary illumination conditions.

  12. Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2015-01-01

    Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

  13. Stereoscopic Machine-Vision System Using Projected Circles

    Science.gov (United States)

    Mackey, Jeffrey R.

    2010-01-01

    A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a

  14. An FPGA Implementation of a Robot Control System with an Integrated 3D Vision System

    Directory of Open Access Journals (Sweden)

    Yi-Ting Chen

    2015-05-01

    Full Text Available Robot decision making and motion control are commonly based on visual information in various applications. Position-based visual servo is a technique for vision-based robot control, which operates in the 3D workspace, uses real-time image processing to perform tasks of feature extraction, and returns the pose of the object for positioning control. In order to handle the computational burden at the vision sensor feedback, we design a FPGA-based motion-vision integrated system that employs dedicated hardware circuits for processing vision processing and motion control functions. This research conducts a preliminary study to explore the integration of 3D vision and robot motion control system design based on a single field programmable gate array (FPGA chip. The implemented motion-vision embedded system performs the following functions: filtering, image statistics, binary morphology, binary object analysis, object 3D position calculation, robot inverse kinematics, velocity profile generation, feedback counting, and multiple-axes position feedback control.

  15. Vision system for precision alignment of coolant channels

    International Nuclear Information System (INIS)

    Kar, S.; Rao, Y.V.; Valli Kumar; Joshi, D.G.; Chadda, V.K.; Nigam, R.K.; Kayal, J.N.; Panwar, S.; Sinha, R.K.

    1997-01-01

    This paper describes a vision system which has been developed for precision alignment of Coolant Channel Replacement Machine (CCRM) with respect to the front face of the coolant channel under repair/replacement. It has provisions for automatic as well as semi-automatic alignment. A special lighting scheme has been developed for providing illumination to the front face of the channel opening. This facilitates automatic segmentation of the digitized image. The segmented image is analysed to obtain the centre of the front face of the channel opening and thus the extent of misalignment i.e. offset of the camera with respect to the front face of the channel opening. The offset information is then communicated to the PLC to generate an output signal to drive the DC servo motors for precise positioning of the co-ordinate table. 2 refs., 5 figs

  16. A Vision-Based Wireless Charging System for Robot Trophallaxis

    Directory of Open Access Journals (Sweden)

    Jae-O Kim

    2015-12-01

    Full Text Available The need to recharge the batteries of a mobile robot has presented an important challenge for a long time. In this paper, a vision-based wireless charging method for robot energy trophallaxis between two robots is presented. Even though wireless power transmission allows more positional error between receiver-transmitter coils than with a contact-type charging system, both coils have to be aligned as accurately as possible for efficient power transfer. To align the coils, a transmitter robot recognizes the coarse pose of a receiver robot via a camera image and the ambiguity of the estimated pose is removed with a Bayesian estimator. The precise pose of the receiver coil is calculated using a marker image attached to a receiver robot. Experiments with several types of receiver robots have been conducted to verify the proposed method.

  17. THE PHENOMENON OF EUROPEAN MUSICAL ROMANTICISM IN SYSTEMIC RESEARCH VISION

    Directory of Open Access Journals (Sweden)

    FLOREA AUGUSTINA

    2015-09-01

    Full Text Available The Romanticism – European cultural-artistic phenomenon of the 20th century, developed in various fields of philosophy, literature, arts, and in terms of its amplitude and universality marked the respective century as a Romantic Era – is promoted in the most pointed manner in musical art. The Research of musical Romanticism – in the conceptual, aesthetic, musical aspect – can be achieved only on the basis of a systemic vision, which inputs the necessity of a study of synthesis. The respective study will integrate in a single process the investigation of all the above – mentioned aspects and will take place at the intersection of different scientific domains: aesthetics and musical aesthetics, historical and theoretical musicology, history and theory of interpretative art.

  18. Automatic Calibration and Reconstruction for Active Vision Systems

    CERN Document Server

    Zhang, Beiwei

    2012-01-01

    In this book, the design of two new planar patterns for camera calibration of intrinsic parameters is addressed and a line-based method for distortion correction is suggested. The dynamic calibration of structured light systems, which consist of a camera and a projector is also treated. Also, the 3D Euclidean reconstruction by using the image-to-world transformation is investigated. Lastly, linear calibration algorithms for the catadioptric camera are considered, and the homographic matrix and fundamental matrix are extensively studied. In these methods, analytic solutions are provided for the computational efficiency and redundancy in the data can be easily incorporated to improve reliability of the estimations. This volume will therefore prove valuable and practical tool for researchers and practioners working in image processing and computer vision and related subjects.

  19. A survey of camera error sources in machine vision systems

    Science.gov (United States)

    Jatko, W. B.

    In machine vision applications, such as an automated inspection line, television cameras are commonly used to record scene intensity in a computer memory or frame buffer. Scene data from the image sensor can then be analyzed with a wide variety of feature-detection techniques. Many algorithms found in textbooks on image processing make the implicit simplifying assumption of an ideal input image with clearly defined edges and uniform illumination. The ideal image model is helpful to aid the student in understanding the principles of operation, but when these algorithms are blindly applied to real-world images the results can be unsatisfactory. This paper examines some common measurement errors found in camera sensors and their underlying causes, and possible methods of error compensation. The role of the camera in a typical image-processing system is discussed, with emphasis on the origination of signal distortions. The effects of such things as lighting, optics, and sensor characteristics are considered.

  20. 2020 Vision for Tank Waste Cleanup (One System Integration) - 12506

    Energy Technology Data Exchange (ETDEWEB)

    Harp, Benton; Charboneau, Stacy; Olds, Erik [US DOE (United States)

    2012-07-01

    The mission of the Department of Energy's Office of River Protection (ORP) is to safely retrieve and treat the 56 million gallons of Hanford's tank waste and close the Tank Farms to protect the Columbia River. The millions of gallons of waste are a by-product of decades of plutonium production. After irradiated fuel rods were taken from the nuclear reactors to the processing facilities at Hanford they were exposed to a series of chemicals designed to dissolve away the rod, which enabled workers to retrieve the plutonium. Once those chemicals were exposed to the fuel rods they became radioactive and extremely hot. They also couldn't be used in this process more than once. Because the chemicals are caustic and extremely hazardous to humans and the environment, underground storage tanks were built to hold these chemicals until a more permanent solution could be found. The Cleanup of Hanford's 56 million gallons of radioactive and chemical waste stored in 177 large underground tanks represents the Department's largest and most complex environmental remediation project. Sixty percent by volume of the nation's high-level radioactive waste is stored in the underground tanks grouped into 18 'tank farms' on Hanford's central plateau. Hanford's mission to safely remove, treat and dispose of this waste includes the construction of a first-of-its-kind Waste Treatment Plant (WTP), ongoing retrieval of waste from single-shell tanks, and building or upgrading the waste feed delivery infrastructure that will deliver the waste to and support operations of the WTP beginning in 2019. Our discussion of the 2020 Vision for Hanford tank waste cleanup will address the significant progress made to date and ongoing activities to manage the operations of the tank farms and WTP as a single system capable of retrieving, delivering, treating and disposing Hanford's tank waste. The initiation of hot operations and subsequent full operations

  1. Theoretical Limits of Lunar Vision Aided Navigation with Inertial Navigation System

    Science.gov (United States)

    2015-03-26

    THEORETICAL LIMITS OF LUNAR VISION AIDED NAVIGATION WITH INERTIAL NAVIGATION SYSTEM THESIS David W. Jones, Capt, USAF AFIT-ENG-MS-15-M-020 DEPARTMENT...Government and is not subject to copyright protection in the United States. AFIT-ENG-MS-15-M-020 THEORETICAL LIMITS OF LUNAR VISION AIDED NAVIGATION WITH...DISTRIBUTION UNLIMITED. AFIT-ENG-MS-15-M-020 THEORETICAL LIMITS OF LUNAR VISION AIDED NAVIGATION WITH INERTIAL NAVIGATION SYSTEM THESIS David W. Jones

  2. Expert System Architecture for Rocket Engine Numerical Simulators: A Vision

    Science.gov (United States)

    Mitra, D.; Babu, U.; Earla, A. K.; Hemminger, Joseph A.

    1998-01-01

    Simulation of any complex physical system like rocket engines involves modeling the behavior of their different components using mostly numerical equations. Typically a simulation package would contain a set of subroutines for these modeling purposes and some other ones for supporting jobs. A user would create an input file configuring a system (part or whole of a rocket engine to be simulated) in appropriate format understandable by the package and run it to create an executable module corresponding to the simulated system. This module would then be run on a given set of input parameters in another file. Simulation jobs are mostly done for performance measurements of a designed system, but could be utilized for failure analysis or a design job such as inverse problems. In order to use any such package the user needs to understand and learn a lot about the software architecture of the package, apart from being knowledgeable in the target domain. We are currently involved in a project in designing an intelligent executive module for the rocket engine simulation packages, which would free any user from this burden of acquiring knowledge on a particular software system. The extended abstract presented here will describe the vision, methodology and the problems encountered in the project. We are employing object-oriented technology in designing the executive module. The problem is connected to the areas like the reverse engineering of any simulation software, and the intelligent systems for simulation.

  3. A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

    Science.gov (United States)

    Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

    1992-01-01

    Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

  4. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  5. Computing with networks of spiking neurons on a biophysically motivated floating-gate based neuromorphic integrated circuit.

    Science.gov (United States)

    Brink, S; Nease, S; Hasler, P

    2013-09-01

    Results are presented from several spiking network experiments performed on a novel neuromorphic integrated circuit. The networks are discussed in terms of their computational significance, which includes applications such as arbitrary spatiotemporal pattern generation and recognition, winner-take-all competition, stable generation of rhythmic outputs, and volatile memory. Analogies to the behavior of real biological neural systems are also noted. The alternatives for implementing the same computations are discussed and compared from a computational efficiency standpoint, with the conclusion that implementing neural networks on neuromorphic hardware is significantly more power efficient than numerical integration of model equations on traditional digital hardware. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Vision for an Open, Global Greenhouse Gas Information System (GHGIS)

    Science.gov (United States)

    Duren, R. M.; Butler, J. H.; Rotman, D.; Ciais, P.; Greenhouse Gas Information System Team

    2010-12-01

    Over the next few years, an increasing number of entities ranging from international, national, and regional governments, to businesses and private land-owners, are likely to become more involved in efforts to limit atmospheric concentrations of greenhouse gases. In such a world, geospatially resolved information about the location, amount, and rate of greenhouse gas (GHG) emissions will be needed, as well as the stocks and flows of all forms of carbon through the earth system. The ability to implement policies that limit GHG concentrations would be enhanced by a global, open, and transparent greenhouse gas information system (GHGIS). An operational and scientifically robust GHGIS would combine ground-based and space-based observations, carbon-cycle modeling, GHG inventories, synthesis analysis, and an extensive data integration and distribution system, to provide information about anthropogenic and natural sources, sinks, and fluxes of greenhouse gases at temporal and spatial scales relevant to decision making. The GHGIS effort was initiated in 2008 as a grassroots inter-agency collaboration intended to identify the needs for such a system, assess the capabilities of current assets, and suggest priorities for future research and development. We will present a vision for an open, global GHGIS including latest analysis of system requirements, critical gaps, and relationship to related efforts at various agencies, the Group on Earth Observations, and the Intergovernmental Panel on Climate Change.

  7. An analog VLSI chip emulating polarization vision of Octopus retina.

    Science.gov (United States)

    Momeni, Massoud; Titus, Albert H

    2006-01-01

    Biological systems provide a wealth of information which form the basis for human-made artificial systems. In this work, the visual system of Octopus is investigated and its polarization sensitivity mimicked. While in actual Octopus retina, polarization vision is mainly based on the orthogonal arrangement of its photoreceptors, our implementation uses a birefringent micropolarizer made of YVO4 and mounted on a CMOS chip with neuromorphic circuitry to process linearly polarized light. Arranged in an 8 x 5 array with two photodiodes per pixel, each consuming typically 10 microW, this circuitry mimics both the functionality of individual Octopus retina cells by computing the state of polarization and the interconnection of these cells through a bias-controllable resistive network.

  8. A future vision of nuclear material information systems

    International Nuclear Information System (INIS)

    Suski, N.; Wimple, C.

    1999-01-01

    To address the current and future needs for nuclear materials management and safeguards information, Lawrence Livermore National Laboratory envisions an integrated nuclear information system that will support several functions. The vision is to link distributed information systems via a common communications infrastructure designed to address the information interdependencies between two major elements: Domestic, with information about specific nuclear materials and their properties, and International, with information pertaining to foreign nuclear materials, facility design and operations. The communication infrastructure will enable data consistency, validation and reconciliation, as well as provide a common access point and user interface for a broad range of nuclear materials information. Information may be transmitted to, from, and within the system by a variety of linkage mechanisms, including the Internet. Strict access control will be employed as well as data encryption and user authentication to provide the necessary information assurance. The system can provide a mechanism not only for data storage and retrieval, but will eventually provide the analytical tools necessary to support the U.S. government's nuclear materials management needs and non-proliferation policy goals

  9. Microfluidic Neurons, a New Way in Neuromorphic Engineering?

    Directory of Open Access Journals (Sweden)

    Timothée Levi

    2016-08-01

    Full Text Available This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.

  10. Advances in neuromorphic hardware exploiting emerging nanoscale devices

    CERN Document Server

    2017-01-01

    This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

  11. Stochastic learning in oxide binary synaptic device for neuromorphic computing.

    Science.gov (United States)

    Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

    2013-01-01

    Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

  12. A Real-Time Embedded System for Stereo Vision Preprocessing Using an FPGA

    DEFF Research Database (Denmark)

    Kjær-Nielsen, Anders; Jensen, Lars Baunegaard With; Sørensen, Anders Stengaard

    2008-01-01

    In this paper a low level vision processing node for use in existing IEEE 1394 camera setups is presented. The processing node is a small embedded system, that utilizes an FPGA to perform stereo vision preprocessing at rates limited by the bandwidth of IEEE 1394a (400Mbit). The system is used...

  13. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

    Directory of Open Access Journals (Sweden)

    Runchun M. Wang

    2018-04-01

    Full Text Available This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons. This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  14. New vision solar system mission study. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Mondt, J.F.; Zubrin, R.M.

    1996-03-01

    The vision for the future of the planetary exploration program includes the capability to deliver {open_quotes}constellations{close_quotes} or {open_quotes}fleets{close_quotes} of microspacecraft to a planetary destination. These fleets will act in a coordinated manner to gather science data from a variety of locations on or around the target body, thus providing detailed, global coverage without requiring development of a single large, complex and costly spacecraft. Such constellations of spacecraft, coupled with advanced information processing and visualization techniques and high-rate communications, could provide the basis for development of a {open_quotes}virtual{close_quotes} {open_quotes}presence{close_quotes} in the solar system. A goal could be the near real-time delivery of planetary images and video to a wide variety of users in the general public and the science community. This will be a major step in making the solar system accessible to the public and will help make solar system exploration a part of the human experience on Earth.

  15. An Adaptable Neuromorphic Model of Orientation Selectivity Based On Floating Gate Dynamics

    Directory of Open Access Journals (Sweden)

    Priti eGupta

    2014-04-01

    Full Text Available The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps

  16. Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model

    Directory of Open Access Journals (Sweden)

    Lorenzo Vannucci

    2017-06-01

    Full Text Available Connecting biologically inspired neural simulations to physical or simulated embodiments can be useful both in robotics, for the development of a new kind of bio-inspired controllers, and in neuroscience, to test detailed brain models in complete action-perception loops. The aim of this work is to develop a fully spike-based, biologically inspired mechanism for the translation of proprioceptive feedback. The translation is achieved by implementing a computational model of neural activity of type Ia and type II afferent fibers of muscle spindles, the primary source of proprioceptive information, which, in mammals is regulated through fusimotor activation and provides necessary adjustments during voluntary muscle contractions. As such, both static and dynamic γ-motoneurons activities are taken into account in the proposed model. Information from the actual proprioceptive sensors (i.e., motor encoders is then used to simulate the spindle contraction and relaxation, and therefore drive the neural activity. To assess the feasibility of this approach, the model is implemented on the NEST spiking neural network simulator and on the SpiNNaker neuromorphic hardware platform and tested on simulated and physical robotic platforms. The results demonstrate that the model can be used in both simulated and real-time robotic applications to translate encoder values into a biologically plausible neural activity. Thus, this model provides a completely spike-based building block, suitable for neuromorphic platforms, that will enable the development of sensory-motor closed loops which could include neural simulations of areas of the central nervous system or of low-level reflexes.

  17. KNOWLEDGE-BASED ROBOT VISION SYSTEM FOR AUTOMATED PART HANDLING

    Directory of Open Access Journals (Sweden)

    J. Wang

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper discusses an algorithm incorporating a knowledge-based vision system into an industrial robot system for handling parts intelligently. A continuous fuzzy controller was employed to extract boundary information in a computationally efficient way. The developed algorithm for on-line part recognition using fuzzy logic is shown to be an effective solution to extract the geometric features of objects. The proposed edge vector representation method provides enough geometric information and facilitates the object geometric reconstruction for gripping planning. Furthermore, a part-handling model was created by extracting the grasp features from the geometric features.

    AFRIKAANSE OPSOMMING: Hierdie artikel beskryf ‘n kennis-gebaseerde visiesisteemalgoritme wat in ’n industriёle robotsisteem ingesluit word om sodoende intelligente komponenthantering te bewerkstellig. ’n Kontinue wasige beheerder is gebruik om allerlei objekinligting deur middel van ’n effektiewe berekeningsmetode te bepaal. Die ontwikkelde algoritme vir aan-lyn komponentherkenning maak gebruik van wasige logika en word bewys as ’n effektiewe metode om geometriese inligting van objekte te bepaal. Die voorgestelde grensvektormetode verskaf voldoende inligting en maak geometriese rekonstruksie van die objek moontlik om greepbeplanning te kan doen. Voorts is ’n komponenthanteringsmodel ontwikkel deur die grypkenmerke af te lei uit die geometriese eienskappe.

  18. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  19. [Functional state of vision system under chronic mercury intoxication].

    Science.gov (United States)

    Iablonskaia, D A; Mishchenko, T S; Lakhman, O L; Rukavishnikov, V S; Malyshev, V V

    2010-01-01

    Examination of chronic mercury intoxication patients in distant (post-contact) period revealed marked vision disorders and inhibited neuro-conductivity--inhibited neuronal structures of retina and optic nerve.

  20. Memristive and neuromorphic behavior in a LixCoO2 nanobattery

    Science.gov (United States)

    Mai, V. H.; Moradpour, A.; Senzier, P. Auban; Pasquier, C.; Wang, K.; Rozenberg, M. J.; Giapintzakis, J.; Mihailescu, C. N.; Orfanidou, C. M.; Svoukis, E.; Breza, A.; Lioutas, Ch B.; Franger, S.; Revcolevschi, A.; Maroutian, T.; Lecoeur, P.; Aubert, P.; Agnus, G.; Salot, R.; Albouy, P. A.; Weil, R.; Alamarguy, D.; March, K.; Jomard, F.; Chrétien, P.; Schneegans, O.

    2015-01-01

    The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of LixCoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.

  1. FPGA implementation of a configurable neuromorphic CPG-based locomotion controller.

    Science.gov (United States)

    Barron-Zambrano, Jose Hugo; Torres-Huitzil, Cesar

    2013-09-01

    Neuromorphic engineering is a discipline devoted to the design and development of computational hardware that mimics the characteristics and capabilities of neuro-biological systems. In recent years, neuromorphic hardware systems have been implemented using a hybrid approach incorporating digital hardware so as to provide flexibility and scalability at the cost of power efficiency and some biological realism. This paper proposes an FPGA-based neuromorphic-like embedded system on a chip to generate locomotion patterns of periodic rhythmic movements inspired by Central Pattern Generators (CPGs). The proposed implementation follows a top-down approach where modularity and hierarchy are two desirable features. The locomotion controller is based on CPG models to produce rhythmic locomotion patterns or gaits for legged robots such as quadrupeds and hexapods. The architecture is configurable and scalable for robots with either different morphologies or different degrees of freedom (DOFs). Experiments performed on a real robot are presented and discussed. The obtained results demonstrate that the CPG-based controller provides the necessary flexibility to generate different rhythmic patterns at run-time suitable for adaptable locomotion. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Neuromorphic computing with nanoscale spintronic oscillators.

    Science.gov (United States)

    Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, Mark D; Grollier, Julie

    2017-07-26

    Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10 8 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

  3. ARM-based visual processing system for prosthetic vision.

    Science.gov (United States)

    Matteucci, Paul B; Byrnes-Preston, Philip; Chen, Spencer C; Lovell, Nigel H; Suaning, Gregg J

    2011-01-01

    A growing number of prosthetic devices have been shown to provide visual perception to the profoundly blind through electrical neural stimulation. These first-generation devices offer promising outcomes to those affected by degenerative disorders such as retinitis pigmentosa. Although prosthetic approaches vary in their placement of the stimulating array (visual cortex, optic-nerve, epi-retinal surface, sub-retinal surface, supra-choroidal space, etc.), most of the solutions incorporate an externally-worn device to acquire and process video to provide the implant with instructions on how to deliver electrical stimulation to the patient, in order to elicit phosphenized vision. With the significant increase in availability and performance of low power-consumption smart phone and personal device processors, the authors investigated the use of a commercially available ARM (Advanced RISC Machine) device as an externally-worn processing unit for a prosthetic neural stimulator for the retina. A 400 MHz Samsung S3C2440A ARM920T single-board computer was programmed to extract 98 values from a 1.3 Megapixel OV9650 CMOS camera using impulse, regional averaging and Gaussian sampling algorithms. Power consumption and speed of video processing were compared to results obtained to similar reported devices. The results show that by using code optimization, the system is capable of driving a 98 channel implantable device for the restoration of visual percepts to the blind.

  4. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2017-12-01

    Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

  5. Range-Image Acquisition for Discriminated Objects in a Range-gated Robot Vision System

    Energy Technology Data Exchange (ETDEWEB)

    Park, Seung-Kyu; Ahn, Yong-Jin; Park, Nak-Kyu; Baik, Sung-Hoon; Choi, Young-Soo; Jeong, Kyung-Min [KAERI, Daejeon (Korea, Republic of)

    2015-05-15

    The imaging capability of a surveillance vision system from harsh low-visibility environments such as in fire and detonation areas is a key function to monitor the safety of the facilities. 2D and range image data acquired from low-visibility environment are important data to assess the safety and prepare appropriate countermeasures. Passive vision systems, such as conventional camera and binocular stereo vision systems usually cannot acquire image information when the reflected light is highly scattered and absorbed by airborne particles such as fog. In addition, the image resolution captured through low-density airborne particles is decreased because the image is blurred and dimmed by the scattering, emission and absorption. Active vision systems, such as structured light vision and projected stereo vision are usually more robust for harsh environment than passive vision systems. However, the performance is considerably decreased in proportion to the density of the particles. The RGI system provides 2D and range image data from several RGI images and it moreover provides clear images from low-visibility fog and smoke environment by using the sum of time-sliced images. Nowadays, the Range-gated (RG) imaging is an emerging technology in the field of surveillance for security applications, especially in the visualization of invisible night and fog environment. Although RGI viewing was discovered in the 1960's, this technology is, nowadays becoming more applicable by virtue of the rapid development of optical and sensor technologies. Especially, this system can be adopted in robot-vision system by virtue of its compact portable configuration. In contrast to passive vision systems, this technology enables operation even in harsh environments like fog and smoke. During the past decades, several applications of this technology have been applied in target recognition and in harsh environments, such as fog, underwater vision. Also, this technology has been

  6. Range-Image Acquisition for Discriminated Objects in a Range-gated Robot Vision System

    International Nuclear Information System (INIS)

    Park, Seung-Kyu; Ahn, Yong-Jin; Park, Nak-Kyu; Baik, Sung-Hoon; Choi, Young-Soo; Jeong, Kyung-Min

    2015-01-01

    The imaging capability of a surveillance vision system from harsh low-visibility environments such as in fire and detonation areas is a key function to monitor the safety of the facilities. 2D and range image data acquired from low-visibility environment are important data to assess the safety and prepare appropriate countermeasures. Passive vision systems, such as conventional camera and binocular stereo vision systems usually cannot acquire image information when the reflected light is highly scattered and absorbed by airborne particles such as fog. In addition, the image resolution captured through low-density airborne particles is decreased because the image is blurred and dimmed by the scattering, emission and absorption. Active vision systems, such as structured light vision and projected stereo vision are usually more robust for harsh environment than passive vision systems. However, the performance is considerably decreased in proportion to the density of the particles. The RGI system provides 2D and range image data from several RGI images and it moreover provides clear images from low-visibility fog and smoke environment by using the sum of time-sliced images. Nowadays, the Range-gated (RG) imaging is an emerging technology in the field of surveillance for security applications, especially in the visualization of invisible night and fog environment. Although RGI viewing was discovered in the 1960's, this technology is, nowadays becoming more applicable by virtue of the rapid development of optical and sensor technologies. Especially, this system can be adopted in robot-vision system by virtue of its compact portable configuration. In contrast to passive vision systems, this technology enables operation even in harsh environments like fog and smoke. During the past decades, several applications of this technology have been applied in target recognition and in harsh environments, such as fog, underwater vision. Also, this technology has been

  7. Robot vision system R and D for ITER blanket remote-handling system

    International Nuclear Information System (INIS)

    Maruyama, Takahito; Aburadani, Atsushi; Takeda, Nobukazu; Kakudate, Satoshi; Nakahira, Masataka; Tesini, Alessandro

    2014-01-01

    For regular maintenance of the International Thermonuclear Experimental Reactor (ITER), a system called the ITER blanket remote-handling system is necessary to remotely handle the blanket modules because of the high levels of gamma radiation. Modules will be handled by robotic power manipulators and they must have a non-contact-sensing system for installing and grasping to avoid contact with other modules. A robot vision system that uses cameras was adopted for this non-contact-sensing system. Experiments for grasping modules were carried out in a dark room to simulate the environment inside the vacuum vessel and the robot vision system's measurement errors were studied. As a result, the accuracy of the manipulator's movements was within 2.01 mm and 0.31°, which satisfies the system requirements. Therefore, it was concluded that this robot vision system is suitable for the non-contact-sensing system of the ITER blanket remote-handling system

  8. Robot vision system R and D for ITER blanket remote-handling system

    Energy Technology Data Exchange (ETDEWEB)

    Maruyama, Takahito, E-mail: maruyama.takahito@jaea.go.jp [Japan Atomic Energy Agency, Fusion Research and Development Directorate, Naka, Ibaraki-ken 311-0193 (Japan); Aburadani, Atsushi; Takeda, Nobukazu; Kakudate, Satoshi; Nakahira, Masataka [Japan Atomic Energy Agency, Fusion Research and Development Directorate, Naka, Ibaraki-ken 311-0193 (Japan); Tesini, Alessandro [ITER Organization, Route de Vinon sur Verdon, 13115 St Paul Lez Durance (France)

    2014-10-15

    For regular maintenance of the International Thermonuclear Experimental Reactor (ITER), a system called the ITER blanket remote-handling system is necessary to remotely handle the blanket modules because of the high levels of gamma radiation. Modules will be handled by robotic power manipulators and they must have a non-contact-sensing system for installing and grasping to avoid contact with other modules. A robot vision system that uses cameras was adopted for this non-contact-sensing system. Experiments for grasping modules were carried out in a dark room to simulate the environment inside the vacuum vessel and the robot vision system's measurement errors were studied. As a result, the accuracy of the manipulator's movements was within 2.01 mm and 0.31°, which satisfies the system requirements. Therefore, it was concluded that this robot vision system is suitable for the non-contact-sensing system of the ITER blanket remote-handling system.

  9. Vision and laterality: does occlusion disclose a feedback processing advantage for the right hand system?

    Science.gov (United States)

    Buekers, M J; Helsen, W F

    2000-09-01

    The main purpose of this study was to examine whether manual asymmetries could be related to the superiority of the left hemisphere/right hand system in processing visual feedback. Subjects were tested when performing single (Experiment 1) and reciprocal (Experiment 2) aiming movements under different vision conditions (full vision, 20 ms on/180 ms off, 10/90, 40/160, 20/80, 60/120, 20/40). Although in both experiments right hand advantages were found, manual asymmetries did not interact with intermittent vision conditions. Similar patterns of results were found across vision conditions for both hands. These data do not support the visual feedback processing hypothesis of manual asymmetry. Motor performance is affected to the same extent for both hand systems when vision is degraded.

  10. Neuromorphic Kalman filter implementation in IBM’s TrueNorth

    Science.gov (United States)

    Carney, R.; Bouchard, K.; Calafiura, P.; Clark, D.; Donofrio, D.; Garcia-Sciveres, M.; Livezey, J.

    2017-10-01

    Following the advent of a post-Moore’s law field of computation, novel architectures continue to emerge. With composite, multi-million connection neuromorphic chips like IBM’s TrueNorth, neural engineering has now become a feasible technology in this novel computing paradigm. High Energy Physics experiments are continuously exploring new methods of computation and data handling, including neuromorphic, to support the growing challenges of the field and be prepared for future commodity computing trends. This work details the first instance of a Kalman filter implementation in IBM’s neuromorphic architecture, TrueNorth, for both parallel and serial spike trains. The implementation is tested on multiple simulated systems and its performance is evaluated with respect to an equivalent non-spiking Kalman filter. The limits of the implementation are explored whilst varying the size of weight and threshold registers, the number of spikes used to encode a state, size of neuron block for spatial encoding, and neuron potential reset schemes.

  11. Ping-Pong Robotics with High-Speed Vision System

    DEFF Research Database (Denmark)

    Li, Hailing; Wu, Haiyan; Lou, Lei

    2012-01-01

    The performance of vision-based control is usually limited by the low sampling rate of the visual feedback. We address Ping-Pong robotics as a widely studied example which requires high-speed vision for highly dynamic motion control. In order to detect a flying ball accurately and robustly...... of the manipulator are updated iteratively with decreasing error. Experiments are conducted on a 7 degrees of freedom humanoid robot arm. A successful Ping-Pong playing between the robot arm and human is achieved with a high successful rate of 88%....

  12. Computer vision and imaging in intelligent transportation systems

    CERN Document Server

    Bala, Raja; Trivedi, Mohan

    2017-01-01

    Acts as a single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation. This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within these problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art.

  13. Measurement of meat color using a computer vision system.

    Science.gov (United States)

    Girolami, Antonio; Napolitano, Fabio; Faraone, Daniela; Braghieri, Ada

    2013-01-01

    The limits of the colorimeter and a technique of image analysis in evaluating the color of beef, pork, and chicken were investigated. The Minolta CR-400 colorimeter and a computer vision system (CVS) were employed to measure colorimetric characteristics. To evaluate the chromatic fidelity of the image of the sample displayed on the monitor, a similarity test was carried out using a trained panel. The panelists found the digital images of the samples visualized on the monitor very similar to the actual ones (Pmeat sample and the sample image on the monitor in order to evaluate the similarity between them (test A). Moreover, the panelists were asked to evaluate the similarity between two colors, both generated by the software Adobe Photoshop CS3 one using the L, a and b values read by the colorimeter and the other obtained using the CVS (test B); which of the two colors was more similar to the sample visualized on the monitor was also assessed (test C). The panelists found the digital images very similar to the actual samples (Pcolors the panelists found significant differences between them (Pcolor of the sample on the monitor was more similar to the CVS generated color than to the colorimeter generated color. The differences between the values of the L, a, b, hue angle and chroma obtained with the CVS and the colorimeter were statistically significant (Pcolor of meat. Instead, the CVS method seemed to give valid measurements that reproduced a color very similar to the real one. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Using Vision Metrology System for Quality Control in Automotive Industries

    Science.gov (United States)

    Mostofi, N.; Samadzadegan, F.; Roohy, Sh.; Nozari, M.

    2012-07-01

    The need of more accurate measurements in different stages of industrial applications, such as designing, producing, installation, and etc., is the main reason of encouraging the industry deputy in using of industrial Photogrammetry (Vision Metrology System). With respect to the main advantages of Photogrammetric methods, such as greater economy, high level of automation, capability of noncontact measurement, more flexibility and high accuracy, a good competition occurred between this method and other industrial traditional methods. With respect to the industries that make objects using a main reference model without having any mathematical model of it, main problem of producers is the evaluation of the production line. This problem will be so complicated when both reference and product object just as a physical object is available and comparison of them will be possible with direct measurement. In such case, producers make fixtures fitting reference with limited accuracy. In practical reports sometimes available precision is not better than millimetres. We used a non-metric high resolution digital camera for this investigation and the case study that studied in this paper is a chassis of automobile. In this research, a stable photogrammetric network designed for measuring the industrial object (Both Reference and Product) and then by using the Bundle Adjustment and Self-Calibration methods, differences between the Reference and Product object achieved. These differences will be useful for the producer to improve the production work flow and bringing more accurate products. Results of this research, demonstrate the high potential of proposed method in industrial fields. Presented results prove high efficiency and reliability of this method using RMSE criteria. Achieved RMSE for this case study is smaller than 200 microns that shows the fact of high capability of implemented approach.

  15. USING VISION METROLOGY SYSTEM FOR QUALITY CONTROL IN AUTOMOTIVE INDUSTRIES

    Directory of Open Access Journals (Sweden)

    N. Mostofi

    2012-07-01

    Full Text Available The need of more accurate measurements in different stages of industrial applications, such as designing, producing, installation, and etc., is the main reason of encouraging the industry deputy in using of industrial Photogrammetry (Vision Metrology System. With respect to the main advantages of Photogrammetric methods, such as greater economy, high level of automation, capability of noncontact measurement, more flexibility and high accuracy, a good competition occurred between this method and other industrial traditional methods. With respect to the industries that make objects using a main reference model without having any mathematical model of it, main problem of producers is the evaluation of the production line. This problem will be so complicated when both reference and product object just as a physical object is available and comparison of them will be possible with direct measurement. In such case, producers make fixtures fitting reference with limited accuracy. In practical reports sometimes available precision is not better than millimetres. We used a non-metric high resolution digital camera for this investigation and the case study that studied in this paper is a chassis of automobile. In this research, a stable photogrammetric network designed for measuring the industrial object (Both Reference and Product and then by using the Bundle Adjustment and Self-Calibration methods, differences between the Reference and Product object achieved. These differences will be useful for the producer to improve the production work flow and bringing more accurate products. Results of this research, demonstrate the high potential of proposed method in industrial fields. Presented results prove high efficiency and reliability of this method using RMSE criteria. Achieved RMSE for this case study is smaller than 200 microns that shows the fact of high capability of implemented approach.

  16. PENGEMBANGAN COMPUTER VISION SYSTEM SEDERHANA UNTUK MENENTUKAN KUALITAS TOMAT Development of a simple Computer Vision System to determine tomato quality

    Directory of Open Access Journals (Sweden)

    Rudiati Evi Masithoh

    2012-05-01

    Full Text Available The purpose of this research was to develop a simple computer vision system (CVS to non-destructively measure tomato quality based on its Red Gren Blue (RGB color parameter. Tomato quality parameters measured were Brix, citric acid, vitamin C, and total sugar. This system consisted of a box to place object, a webcam to capture images, a computer to process images, illumination system, and an image analysis software which was equipped with artificial neural networks technique for determining tomato quality. Network architecture was formed with 3 layers consisting of1 input layer with 3 input neurons, 1 hidden layer with 14 neurons using logsig activation function, and 5 output layers using purelin activation function by using backpropagation training algorithm. CVS developed was able to predict the quality parameters of a Brix value, vitamin C, citric acid, and total sugar. To obtain the predicted values which were equal or close to the actual values, a calibration model was required. For Brix value, the actual value obtained from the equation y = 12,16x – 26,46, with x was Brix predicted. The actual values of vitamin C, citric acid, and total sugar were obtained from y = 1,09x - 3.13, y = 7,35x – 19,44,  and  y = 1.58x – 0,18,, with x was the value of vitamin C, citric acid, and total sugar, respectively. ABSTRAK Tujuan penelitian adalah mengembangkan computer vision system (CVS sederhana untuk menentukan kualitas tomat secara non­destruktif berdasarkan parameter warna Red Green Blue (RGB. Parameter kualitas tomat yang diukur ada­ lah Brix, asam sitrat, vitamin C, dan gula total. Sistem ini terdiri peralatan utama yaitu kotak untuk meletakkan obyek, webcam untuk menangkap citra, komputer untuk mengolah data, sistem penerangan, dan perangkat lunak analisis citra yang dilengkapi dengan jaringan syaraf tiruan untuk menentukan kualitas tomat. Arsitektur jaringan dibentuk dengan3 lapisan yang terdiri dari 1 lapisan masukan dengan 3 sel

  17. Closed-loop neuromorphic benchmarks

    CSIR Research Space (South Africa)

    Stewart, TC

    2015-11-01

    Full Text Available Benchmarks   Terrence C. Stewart 1* , Travis DeWolf 1 , Ashley Kleinhans 2 , Chris Eliasmith 1   1 University of Waterloo, Canada, 2 Council for Scientific and Industrial Research, South Africa   Submitted to Journal:   Frontiers in Neuroscience   Specialty... Eliasmith 1 1Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada 2Mobile Intelligent Autonomous Systems group, Council for Scientific and Industrial Research, Pretoria, South Africa Correspondence*: Terrence C. Stewart Centre...

  18. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-01-01

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

  19. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-08-11

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  20. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Directory of Open Access Journals (Sweden)

    Lucas Antón Pastur-Romay

    2016-08-01

    Full Text Available Over the past decade, Deep Artificial Neural Networks (DNNs have become the state-of-the-art algorithms in Machine Learning (ML, speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs. All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS, Quantitative Structure–Activity Relationship (QSAR research, protein structure prediction and genomics (and other omics data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  1. Development of Vision System for Dimensional Measurement for Irradiated Fuel Assembly

    International Nuclear Information System (INIS)

    Shin, Jungcheol; Kwon, Yongbock; Park, Jongyoul; Woo, Sangkyun; Kim, Yonghwan; Jang, Youngki; Choi, Joonhyung; Lee, Kyuseog

    2006-01-01

    In order to develop an advanced nuclear fuel, a series of pool side examination (PSE) is performed to confirm in-pile behavior of the fuel for commercial production. For this purpose, a vision system was developed to measure for mechanical integrity, such as assembly bowing, twist and growth, of the loaded lead test assembly. Using this vision system, three(3) times of PSE were carried out at Uljin Unit 3 and Kori Unit 2 for the advanced fuels, PLUS7 TM and 16ACE7 TM , developed by KNFC. Among the main characteristics of the vision system is very simple structure and measuring principal. This feature enables the equipment installation and inspection time to reduce largely, and leads the PSE can be finished without disturbance on the fuel loading and unloading activities during utility overhaul periods. And another feature is high accuracy and repeatability achieved by this vision system

  2. Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey

    OpenAIRE

    Velez, Gorka; Otaegui, Oihana

    2015-01-01

    Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Further...

  3. System and method for controlling a vision guided robot assembly

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Yhu-Tin; Daro, Timothy; Abell, Jeffrey A.; Turner, III, Raymond D.; Casoli, Daniel J.

    2017-03-07

    A method includes the following steps: actuating a robotic arm to perform an action at a start position; moving the robotic arm from the start position toward a first position; determining from a vision process method if a first part from the first position will be ready to be subjected to a first action by the robotic arm once the robotic arm reaches the first position; commencing the execution of the visual processing method for determining the position deviation of the second part from the second position and the readiness of the second part to be subjected to a second action by the robotic arm once the robotic arm reaches the second position; and performing a first action on the first part using the robotic arm with the position deviation of the first part from the first position predetermined by the vision process method.

  4. Smartphones as image processing systems for prosthetic vision.

    Science.gov (United States)

    Zapf, Marc P; Matteucci, Paul B; Lovell, Nigel H; Suaning, Gregg J

    2013-01-01

    The feasibility of implants for prosthetic vision has been demonstrated by research and commercial organizations. In most devices, an essential forerunner to the internal stimulation circuit is an external electronics solution for capturing, processing and relaying image information as well as extracting useful features from the scene surrounding the patient. The capabilities and multitude of image processing algorithms that can be performed by the device in real-time plays a major part in the final quality of the prosthetic vision. It is therefore optimal to use powerful hardware yet to avoid bulky, straining solutions. Recent publications have reported of portable single-board computers fast enough for computationally intensive image processing. Following the rapid evolution of commercial, ultra-portable ARM (Advanced RISC machine) mobile devices, the authors investigated the feasibility of modern smartphones running complex face detection as external processing devices for vision implants. The role of dedicated graphics processors in speeding up computation was evaluated while performing a demanding noise reduction algorithm (image denoising). The time required for face detection was found to decrease by 95% from 2.5 year old to recent devices. In denoising, graphics acceleration played a major role, speeding up denoising by a factor of 18. These results demonstrate that the technology has matured sufficiently to be considered as a valid external electronics platform for visual prosthetic research.

  5. Image Acquisition of Robust Vision Systems to Monitor Blurred Objects in Hazy Smoking Environments

    International Nuclear Information System (INIS)

    Ahn, Yongjin; Park, Seungkyu; Baik, Sunghoon; Kim, Donglyul; Nam, Sungmo; Jeong, Kyungmin

    2014-01-01

    Image information in disaster area or radiation area of nuclear industry is an important data for safety inspection and preparing appropriate damage control plans. So, robust vision system for structures and facilities in blurred smoking environments, such as the places of a fire and detonation, is essential in remote monitoring. Vision systems can't acquire an image when the illumination light is blocked by disturbance materials, such as smoke, fog, dust. The vision system based on wavefront correction can be applied to blurred imaging environments and the range-gated imaging system can be applied to both of blurred imaging and darken light environments. Wavefront control is a widely used technique to improve the performance of optical systems by actively correcting wavefront distortions, such as atmospheric turbulence, thermally-induced distortions, and laser or laser device aberrations, which can reduce the peak intensity and smear an acquired image. The principal applications of wavefront control are for improving the image quality in optical imaging systems such as infrared astronomical telescopes, in imaging and tracking rapidly moving space objects, and in compensating for laser beam distortion through the atmosphere. A conventional wavefront correction system consists of a wavefront sensor, a deformable mirror and a control computer. The control computer measures the wavefront distortions using a wavefront sensor and corrects it using a deformable mirror in a closed-loop. Range-gated imaging (RGI) is a direct active visualization technique using a highly sensitive image sensor and a high intensity illuminant. Currently, the range-gated imaging technique providing 2D and 3D images is one of emerging active vision technologies. The range-gated imaging system gets vision information by summing time sliced vision images. In the RGI system, a high intensity illuminant illuminates for ultra-short time and a highly sensitive image sensor is gated by ultra

  6. Image Acquisition of Robust Vision Systems to Monitor Blurred Objects in Hazy Smoking Environments

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Yongjin; Park, Seungkyu; Baik, Sunghoon; Kim, Donglyul; Nam, Sungmo; Jeong, Kyungmin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-05-15

    Image information in disaster area or radiation area of nuclear industry is an important data for safety inspection and preparing appropriate damage control plans. So, robust vision system for structures and facilities in blurred smoking environments, such as the places of a fire and detonation, is essential in remote monitoring. Vision systems can't acquire an image when the illumination light is blocked by disturbance materials, such as smoke, fog, dust. The vision system based on wavefront correction can be applied to blurred imaging environments and the range-gated imaging system can be applied to both of blurred imaging and darken light environments. Wavefront control is a widely used technique to improve the performance of optical systems by actively correcting wavefront distortions, such as atmospheric turbulence, thermally-induced distortions, and laser or laser device aberrations, which can reduce the peak intensity and smear an acquired image. The principal applications of wavefront control are for improving the image quality in optical imaging systems such as infrared astronomical telescopes, in imaging and tracking rapidly moving space objects, and in compensating for laser beam distortion through the atmosphere. A conventional wavefront correction system consists of a wavefront sensor, a deformable mirror and a control computer. The control computer measures the wavefront distortions using a wavefront sensor and corrects it using a deformable mirror in a closed-loop. Range-gated imaging (RGI) is a direct active visualization technique using a highly sensitive image sensor and a high intensity illuminant. Currently, the range-gated imaging technique providing 2D and 3D images is one of emerging active vision technologies. The range-gated imaging system gets vision information by summing time sliced vision images. In the RGI system, a high intensity illuminant illuminates for ultra-short time and a highly sensitive image sensor is gated by ultra

  7. Vision-based markerless registration using stereo vision and an augmented reality surgical navigation system: a pilot study

    International Nuclear Information System (INIS)

    Suenaga, Hideyuki; Tran, Huy Hoang; Liao, Hongen; Masamune, Ken; Dohi, Takeyoshi; Hoshi, Kazuto; Takato, Tsuyoshi

    2015-01-01

    This study evaluated the use of an augmented reality navigation system that provides a markerless registration system using stereo vision in oral and maxillofacial surgery. A feasibility study was performed on a subject, wherein a stereo camera was used for tracking and markerless registration. The computed tomography data obtained from the volunteer was used to create an integral videography image and a 3-dimensional rapid prototype model of the jaw. The overlay of the subject’s anatomic site and its 3D-IV image were displayed in real space using a 3D-AR display. Extraction of characteristic points and teeth matching were done using parallax images from two stereo cameras for patient-image registration. Accurate registration of the volunteer’s anatomy with IV stereoscopic images via image matching was done using the fully automated markerless system, which recognized the incisal edges of the teeth and captured information pertaining to their position with an average target registration error of < 1 mm. These 3D-CT images were then displayed in real space with high accuracy using AR. Even when the viewing position was changed, the 3D images could be observed as if they were floating in real space without using special glasses. Teeth were successfully used for registration via 3D image (contour) matching. This system, without using references or fiducial markers, displayed 3D-CT images in real space with high accuracy. The system provided real-time markerless registration and 3D image matching via stereo vision, which, combined with AR, could have significant clinical applications. The online version of this article (doi:10.1186/s12880-015-0089-5) contains supplementary material, which is available to authorized users

  8. Robotic vision system for random bin picking with dual-arm robots

    Directory of Open Access Journals (Sweden)

    Kang Sangseung

    2016-01-01

    Full Text Available Random bin picking is one of the most challenging industrial robotics applications available. It constitutes a complicated interaction between the vision system, robot, and control system. For a packaging operation requiring a pick-and-place task, the robot system utilized should be able to perform certain functions for recognizing the applicable target object from randomized objects in a bin. In this paper, we introduce a robotic vision system for bin picking using industrial dual-arm robots. The proposed system recognizes the best object from randomized target candidates based on stereo vision, and estimates the position and orientation of the object. It then sends the result to the robot control system. The system was developed for use in the packaging process of cell phone accessories using dual-arm robots.

  9. Vision-based obstacle recognition system for automated lawn mower robot development

    Science.gov (United States)

    Mohd Zin, Zalhan; Ibrahim, Ratnawati

    2011-06-01

    Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

  10. Using Vision System Technologies for Offset Approaches in Low Visibility Operations

    Science.gov (United States)

    Kramer, Lynda J.; Bailey, Randall E.; Ellis, Kyle K.

    2015-01-01

    Flight deck-based vision systems, such as Synthetic Vision Systems (SVS) and Enhanced Flight Vision Systems (EFVS), have the potential to provide additional margins of safety for aircrew performance and enable the implementation of operational improvements for low visibility surface, arrival, and departure operations in the terminal environment with equivalent efficiency to visual operations. Twelve air transport-rated crews participated in a motion-base simulation experiment to evaluate the use of SVS/EFVS in Next Generation Air Transportation System low visibility approach and landing operations at Chicago O'Hare airport. Three monochromatic, collimated head-up display (HUD) concepts (conventional HUD, SVS HUD, and EFVS HUD) and three instrument approach types (straight-in, 3-degree offset, 15-degree offset) were experimentally varied to test the efficacy of the SVS/EFVS HUD concepts for offset approach operations. The findings suggest making offset approaches in low visibility conditions with an EFVS HUD or SVS HUD appear feasible. Regardless of offset approach angle or HUD concept being flown, all approaches had comparable ILS tracking during the instrument segment and were within the lateral confines of the runway with acceptable sink rates during the visual segment of the approach. Keywords: Enhanced Flight Vision Systems; Synthetic Vision Systems; Head-up Display; NextGen

  11. Improvement of the image quality of a high-temperature vision system

    International Nuclear Information System (INIS)

    Fabijańska, Anna; Sankowski, Dominik

    2009-01-01

    In this paper, the issues of controlling and improving the image quality of a high-temperature vision system are considered. The image quality improvement is needed to measure the surface properties of metals and alloys. Two levels of image quality control and improvement are defined in the system. The first level in hardware aims at adjusting the system configuration to obtain the highest contrast and weakest aura images. When optimal configuration is obtained, the second level in software is applied. In this stage, image enhancement algorithms are applied which have been developed with consideration of distortions arising from the vision system components and specificity of images acquired during the measurement process. The developed algorithms have been applied in the vision system to images. The influence on the accuracy of wetting angles and surface tension determination are considered

  12. Modelling and Analysis of Vibrations in a UAV Helicopter with a Vision System

    Directory of Open Access Journals (Sweden)

    G. Nicolás Marichal Plasencia

    2012-11-01

    Full Text Available The analysis of the nature and damping of unwanted vibrations on Unmanned Aerial Vehicle (UAV helicopters are important tasks when images from on-board vision systems are to be obtained. In this article, the authors model a UAV system, generate a range of vibrations originating in the main rotor and design a control methodology in order to damp these vibrations. The UAV is modelled using VehicleSim, the vibrations that appear on the fuselage are analysed to study their effects on the on-board vision system by using Simmechanics software. Following this, the authors present a control method based on an Adaptive Neuro-Fuzzy Inference System (ANFIS to achieve satisfactory damping results over the vision system on board.

  13. A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

    Science.gov (United States)

    D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

    1993-01-01

    A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

  14. Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

    Science.gov (United States)

    Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

    2017-12-01

    Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

  15. Large-scale simulations of plastic neural networks on neuromorphic hardware

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-04-01

    Full Text Available SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 20000 neurons and 51200000 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

  16. Color Calibration for Colorized Vision System with Digital Sensor and LED Array Illuminator

    Directory of Open Access Journals (Sweden)

    Zhenmin Zhu

    2016-01-01

    Full Text Available Color measurement by the colorized vision system is a superior method to achieve the evaluation of color objectively and continuously. However, the accuracy of color measurement is influenced by the spectral responses of digital sensor and the spectral mismatch of illumination. In this paper, two-color vision system illuminated by digital sensor and LED array, respectively, is presented. The Polynomial-Based Regression method is applied to solve the problem of color calibration in the sRGB and CIE  L⁎a⁎b⁎ color spaces. By mapping the tristimulus values from RGB to sRGB color space, color difference between the estimated values and the reference values is less than 3ΔE. Additionally, the mapping matrix ΦRGB→sRGB has proved a better performance in reducing the color difference, and it is introduced subsequently into the colorized vision system proposed for a better color measurement. Necessarily, the printed matter of clothes and the colored ceramic tile are chosen as the application experiment samples of our colorized vision system. As shown in the experimental data, the average color difference of images is less than 6ΔE. It indicates that a better performance of color measurement is obtained via the colorized vision system proposed.

  17. Computer Vision System For Locating And Identifying Defects In Hardwood Lumber

    Science.gov (United States)

    Conners, Richard W.; Ng, Chong T.; Cho, Tai-Hoon; McMillin, Charles W.

    1989-03-01

    This paper describes research aimed at developing an automatic cutup system for use in the rough mills of the hardwood furniture and fixture industry. In particular, this paper describes attempts to create the vision system that will power this automatic cutup system. There are a number of factors that make the development of such a vision system a challenge. First there is the innate variability of the wood material itself. No two species look exactly the same, in fact, they can have a significant visual difference in appearance among species. Yet a truly robust vision system must be able to handle a variety of such species, preferably with no operator intervention required when changing from one species to another. Secondly, there is a good deal of variability in the definition of what constitutes a removable defect. The hardwood furniture and fixture industry is diverse in the nature of the products that it makes. The products range from hardwood flooring to fancy hardwood furniture, from simple mill work to kitchen cabinets. Thus depending on the manufacturer, the product, and the quality of the product the nature of what constitutes a removable defect can and does vary. The vision system must be such that it can be tailored to meet each of these unique needs, preferably without any additional program modifications. This paper will describe the vision system that has been developed. It will assess the current system capabilities, and it will discuss the directions for future research. It will be argued that artificial intelligence methods provide a natural mechanism for attacking this computer vision application.

  18. Comparison of a multispectral vision system and a colorimeter for the assessment of meat color

    DEFF Research Database (Denmark)

    Trinderup, Camilla Himmelstrup; Dahl, Anders Bjorholm; Jensen, Kirsten

    2015-01-01

    The color assessment ability of a multispectral vision system is investigated by a comparison study with color measurements from a traditional colorimeter. The experiment involves fresh and processed meat samples. Meat is a complex material; heterogeneous with varying scattering and reflectance...... are equally capable of measuring color. Moreover the vision system provides a more color rich assessment of fresh meat samples with a glossier surface, than the colorimeter. Careful studies of the different sources of variation enable an assessment of the order of magnitude of the variability between methods...... accounting for other sources of variation leading to the conclusion that color assessment using a multispectral vision system is superior to traditional colorimeter assessments. (C) 2014 Elsevier Ltd. All rights reserved....

  19. Using Weightless Neural Networks for Vergence Control in an Artificial Vision System

    Directory of Open Access Journals (Sweden)

    Karin S. Komati

    2003-01-01

    Full Text Available This paper presents a methodology we have developed and used to implement an artificial binocular vision system capable of emulating the vergence of eye movements. This methodology involves using weightless neural networks (WNNs as building blocks of artificial vision systems. Using the proposed methodology, we have designed several architectures of WNN-based artificial vision systems, in which images captured by virtual cameras are used for controlling the position of the ‘foveae’ of these cameras (high-resolution region of the images captured. Our best architecture is able to control the foveae vergence movements with average error of only 3.58 image pixels, which is equivalent to an angular error of approximately 0.629°.

  20. The effect of body bias of the metal-oxide-semiconductor field-effect transistor in the resistive network on spatial current distribution in a bio-inspired complementary metal-oxide-semiconductor vision chip

    Science.gov (United States)

    Kong, Jae-Sung; Hyun, Hyo-Young; Seo, Sang-Ho; Shin, Jang-Kyoo

    2008-11-01

    Complementary metal-oxide-semiconductor (CMOS) vision chips for edge detection based on a resistive circuit have recently been developed. These chips help in the creation of neuromorphic systems of a compact size, high speed of operation, and low power dissipation. The output of the vision chip depends predominantly upon the electrical characteristics of the resistive network which consists of a resistive circuit. In this paper, the body effect of the metal-oxide-semiconductor field-effect transistor for current distribution in a resistive circuit is discussed with a simple model. In order to evaluate the model, two 160 × 120 CMOS vision chips have been fabricated using a standard CMOS technology. The experimental results nicely match our prediction.

  1. A Novel Bioinspired Vision System: A Step toward Real-Time Human-Robot Interactions

    Directory of Open Access Journals (Sweden)

    Abdul Rahman Hafiz

    2011-01-01

    Full Text Available Building a human-like robot that could be involved in our daily lives is a dream of many scientists. Achieving a sophisticated robot's vision system, which can enhance the robot's real-time interaction ability with the human, is one of the main keys toward realizing such an autonomous robot. In this work, we are suggesting a bioinspired vision system that helps to develop an advanced human-robot interaction in an autonomous humanoid robot. First, we enhance the robot's vision accuracy online by applying a novel dynamic edge detection algorithm abstracted from the rules that the horizontal cells play in the mammalian retina. Second, in order to support the first algorithm, we improve the robot's tracking ability by designing a variant photoreceptors distribution corresponding to what exists in the human vision system. The experimental results verified the validity of the model. The robot could have a clear vision in real time and build a mental map that assisted it to be aware of the frontal users and to develop a positive interaction with them.

  2. Synapse-centric mapping of cortical models to the SpiNNaker neuromorphic architecture

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-09-01

    Full Text Available While the adult human brain has approximately 8.8x10^10 neurons, this number is dwarfed by its 1x10^15 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously.

  3. Implementation of Automatic Focusing Algorithms for a Computer Vision System with Camera Control.

    Science.gov (United States)

    1983-08-15

    obtainable from real data, rather than relying on a stock database. Often, computer vision and image processing algorithms become subconsciously tuned to...two coils on the same mount structure. Since it was not possible to reprogram the binary system, we turned to the POPEYE system for both its grey

  4. The research of binocular vision ranging system based on LabVIEW

    Science.gov (United States)

    Li, Shikuan; Yang, Xu

    2017-10-01

    Based on the study of the principle of binocular parallax ranging, a binocular vision ranging system is designed and built. The stereo matching algorithm is realized by LabVIEW software. The camera calibration and distance measurement are completed. The error analysis shows that the system fast, effective, can be used in the corresponding industrial occasions.

  5. Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2013-01-01

    Full Text Available With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activity, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation towards the performance of human activity recognition.

  6. A real time tracking vision system and its application to robotics

    International Nuclear Information System (INIS)

    Inoue, Hirochika

    1994-01-01

    Among various sensing channels the vision is most important for making robot intelligent. If provided with a high speed visual tracking capability, the robot-environment interaction becomes dynamic instead of static, and thus the potential repertoire of robot behavior becomes very rich. For this purpose we developed a real-time tracking vision system. The fundamental operation on which our system based is the calculation of correlation between local images. Use of special chip for correlation and the multi-processor configuration enable the robot to track more than hundreds cues in full video rate. In addition to the fundamental visual performance, applications for robot behavior control are also introduced. (author)

  7. The human brain on a computer, the design neuromorphic chips aims to process information as does the mind

    International Nuclear Information System (INIS)

    Pajuelo, L.

    2015-01-01

    Develop chips that mimic the brain processes It will help create computers capable of interpreting information from image, sound and touch so that it may offer answers intelligent-not programmed before- according to these sensory data. chips neuromorphic may mimic the electrical activity neurons and brain synapses, and will be key to intelligence systems artificial (ia) that require interaction with the environment being able to extract information cognitive of what surrounds them. (Author)

  8. An assembly system based on industrial robot with binocular stereo vision

    Science.gov (United States)

    Tang, Hong; Xiao, Nanfeng

    2017-01-01

    This paper proposes an electronic part and component assembly system based on an industrial robot with binocular stereo vision. Firstly, binocular stereo vision with a visual attention mechanism model is used to get quickly the image regions which contain the electronic parts and components. Secondly, a deep neural network is adopted to recognize the features of the electronic parts and components. Thirdly, in order to control the end-effector of the industrial robot to grasp the electronic parts and components, a genetic algorithm (GA) is proposed to compute the transition matrix and the inverse kinematics of the industrial robot (end-effector), which plays a key role in bridging the binocular stereo vision and the industrial robot. Finally, the proposed assembly system is tested in LED component assembly experiments, and the results denote that it has high efficiency and good applicability.

  9. Data-Fusion for a Vision-Aided Radiological Detection System: Sensor dependence and Source Tracking

    Science.gov (United States)

    Stadnikia, Kelsey; Martin, Allan; Henderson, Kristofer; Koppal, Sanjeev; Enqvist, Andreas

    2018-01-01

    The University of Florida is taking a multidisciplinary approach to fuse the data between 3D vision sensors and radiological sensors in hopes of creating a system capable of not only detecting the presence of a radiological threat, but also tracking it. The key to developing such a vision-aided radiological detection system, lies in the count rate being inversely dependent on the square of the distance. Presented in this paper are the results of the calibration algorithm used to predict the location of the radiological detectors based on 3D distance from the source to the detector (vision data) and the detectors count rate (radiological data). Also presented are the results of two correlation methods used to explore source tracking.

  10. Computer vision system in real-time for color determination on flat surface food

    Directory of Open Access Journals (Sweden)

    Erick Saldaña

    2013-03-01

    Full Text Available Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS in real-time for the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware, which consisted of two phases: a image acquisition and b image processing and analysis. Both the algorithm and the graphical interface (GUI were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*, where were estimated the errors of the color parameters: eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector.

  11. A bio-inspired apposition compound eye machine vision sensor system

    International Nuclear Information System (INIS)

    Davis, J D; Barrett, S F; Wright, C H G; Wilcox, M

    2009-01-01

    The Wyoming Information, Signal Processing, and Robotics Laboratory is developing a wide variety of bio-inspired vision sensors. We are interested in exploring the vision system of various insects and adapting some of their features toward the development of specialized vision sensors. We do not attempt to supplant traditional digital imaging techniques but rather develop sensor systems tailor made for the application at hand. We envision that many applications may require a hybrid approach using conventional digital imaging techniques enhanced with bio-inspired analogue sensors. In this specific project, we investigated the apposition compound eye and its characteristics commonly found in diurnal insects and certain species of arthropods. We developed and characterized an array of apposition compound eye-type sensors and tested them on an autonomous robotic vehicle. The robot exhibits the ability to follow a pre-defined target and avoid specified obstacles using a simple control algorithm.

  12. Computer vision system in real-time for color determination on flat surface food

    Directory of Open Access Journals (Sweden)

    Erick Saldaña

    2013-01-01

    Full Text Available Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS in real - time f or the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware, which consisted of two phases: a image acquisition and b image processing and analysis. Both th e algorithm and the graphical interface (GUI were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*, where were estimated the errors of the color parameters: e L* = 5.001%, and e a* = 2.287%, and e b* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector.

  13. Development of a Compact Range-gated Vision System to Monitor Structures in Low-visibility Environments

    International Nuclear Information System (INIS)

    Ahn, Yong-Jin; Park, Seung-Kyu; Baik, Sung-Hoon; Kim, Dong-Lyul; Choi, Young-Soo; Jeong, Kyung-Min

    2015-01-01

    Image acquisition in disaster area or radiation area of nuclear industry is an important function for safety inspection and preparing appropriate damage control plans. So, automatic vision system to monitor structures and facilities in blurred smoking environments such as the places of a fire and detonation is essential. Vision systems can't acquire an image when the illumination light is blocked by disturbance materials, such as smoke, fog and dust. To overcome the imaging distortion caused by obstacle materials, robust vision systems should have extra-functions, such as active illumination through disturbance materials. One of active vision system is a range-gated imaging system. The vision system based on the range-gated imaging system can acquire image data from the blurred and darken light environments. Range-gated imaging (RGI) is a direct active visualization technique using a highly sensitive image sensor and a high intensity illuminant. Currently, the range-gated imaging technique providing 2D and range image data is one of emerging active vision technologies. The range-gated imaging system gets vision information by summing time sliced vision images. In the RGI system, a high intensity illuminant illuminates for ultra-short time and a highly sensitive image sensor is gated by ultra-short exposure time to only get the illumination light. Here, the illuminant illuminates objects by flashing strong light through disturbance materials, such as smoke particles and dust particles. In contrast to passive conventional vision systems, the RGI active vision technology enables operation even in harsh environments like low-visibility smoky environment. In this paper, a compact range-gated vision system is developed to monitor structures in low-visibility environment. The system consists of illumination light, a range-gating camera and a control computer. Visualization experiments are carried out in low-visibility foggy environment to see imaging capability

  14. Development of a Compact Range-gated Vision System to Monitor Structures in Low-visibility Environments

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Yong-Jin; Park, Seung-Kyu; Baik, Sung-Hoon; Kim, Dong-Lyul; Choi, Young-Soo; Jeong, Kyung-Min [KAERI, Daejeon (Korea, Republic of)

    2015-05-15

    Image acquisition in disaster area or radiation area of nuclear industry is an important function for safety inspection and preparing appropriate damage control plans. So, automatic vision system to monitor structures and facilities in blurred smoking environments such as the places of a fire and detonation is essential. Vision systems can't acquire an image when the illumination light is blocked by disturbance materials, such as smoke, fog and dust. To overcome the imaging distortion caused by obstacle materials, robust vision systems should have extra-functions, such as active illumination through disturbance materials. One of active vision system is a range-gated imaging system. The vision system based on the range-gated imaging system can acquire image data from the blurred and darken light environments. Range-gated imaging (RGI) is a direct active visualization technique using a highly sensitive image sensor and a high intensity illuminant. Currently, the range-gated imaging technique providing 2D and range image data is one of emerging active vision technologies. The range-gated imaging system gets vision information by summing time sliced vision images. In the RGI system, a high intensity illuminant illuminates for ultra-short time and a highly sensitive image sensor is gated by ultra-short exposure time to only get the illumination light. Here, the illuminant illuminates objects by flashing strong light through disturbance materials, such as smoke particles and dust particles. In contrast to passive conventional vision systems, the RGI active vision technology enables operation even in harsh environments like low-visibility smoky environment. In this paper, a compact range-gated vision system is developed to monitor structures in low-visibility environment. The system consists of illumination light, a range-gating camera and a control computer. Visualization experiments are carried out in low-visibility foggy environment to see imaging capability.

  15. Navigation integrity monitoring and obstacle detection for enhanced-vision systems

    Science.gov (United States)

    Korn, Bernd; Doehler, Hans-Ullrich; Hecker, Peter

    2001-08-01

    Typically, Enhanced Vision (EV) systems consist of two main parts, sensor vision and synthetic vision. Synthetic vision usually generates a virtual out-the-window view using databases and accurate navigation data, e. g. provided by differential GPS (DGPS). The reliability of the synthetic vision highly depends on both, the accuracy of the used database and the integrity of the navigation data. But especially in GPS based systems, the integrity of the navigation can't be guaranteed. Furthermore, only objects that are stored in the database can be displayed to the pilot. Consequently, unexpected obstacles are invisible and this might cause severe problems. Therefore, additional information has to be extracted from sensor data to overcome these problems. In particular, the sensor data analysis has to identify obstacles and has to monitor the integrity of databases and navigation. Furthermore, if a lack of integrity arises, navigation data, e.g. the relative position of runway and aircraft, has to be extracted directly from the sensor data. The main contribution of this paper is about the realization of these three sensor data analysis tasks within our EV system, which uses the HiVision 35 GHz MMW radar of EADS, Ulm as the primary EV sensor. For the integrity monitoring, objects extracted from radar images are registered with both database objects and objects (e. g. other aircrafts) transmitted via data link. This results in a classification into known and unknown radar image objects and consequently, in a validation of the integrity of database and navigation. Furthermore, special runway structures are searched for in the radar image where they should appear. The outcome of this runway check contributes to the integrity analysis, too. Concurrent to this investigation a radar image based navigation is performed without using neither precision navigation nor detailed database information to determine the aircraft's position relative to the runway. The performance of our

  16. A remote assessment system with a vision robot and wearable sensors.

    Science.gov (United States)

    Zhang, Tong; Wang, Jue; Ren, Yumiao; Li, Jianjun

    2004-01-01

    This paper describes an ongoing researched remote rehabilitation assessment system that has a 6-freedom double-eyes vision robot to catch vision information, and a group of wearable sensors to acquire biomechanical signals. A server computer is fixed on the robot, to provide services to the robot's controller and all the sensors. The robot is connected to Internet by wireless channel, and so do the sensors to the robot. Rehabilitation professionals can semi-automatically practise an assessment program via Internet. The preliminary results show that the smart device, including the robot and the sensors, can improve the quality of remote assessment, and reduce the complexity of operation at a distance.

  17. Miniaturisation of Pressure-Sensitive Paint Measurement Systems Using Low-Cost, Miniaturised Machine Vision Cameras

    Directory of Open Access Journals (Sweden)

    Mark Kenneth Quinn

    2017-07-01

    Full Text Available Measurements of pressure-sensitive paint (PSP have been performed using new or non-scientific imaging technology based on machine vision tools. Machine vision camera systems are typically used for automated inspection or process monitoring. Such devices offer the benefits of lower cost and reduced size compared with typically scientific-grade cameras; however, their optical qualities and suitability have yet to be determined. This research intends to show relevant imaging characteristics and also show the applicability of such imaging technology for PSP. Details of camera performance are benchmarked and compared to standard scientific imaging equipment and subsequent PSP tests are conducted using a static calibration chamber. The findings demonstrate that machine vision technology can be used for PSP measurements, opening up the possibility of performing measurements on-board small-scale model such as those used for wind tunnel testing or measurements in confined spaces with limited optical access.

  18. Miniaturisation of Pressure-Sensitive Paint Measurement Systems Using Low-Cost, Miniaturised Machine Vision Cameras.

    Science.gov (United States)

    Quinn, Mark Kenneth; Spinosa, Emanuele; Roberts, David A

    2017-07-25

    Measurements of pressure-sensitive paint (PSP) have been performed using new or non-scientific imaging technology based on machine vision tools. Machine vision camera systems are typically used for automated inspection or process monitoring. Such devices offer the benefits of lower cost and reduced size compared with typically scientific-grade cameras; however, their optical qualities and suitability have yet to be determined. This research intends to show relevant imaging characteristics and also show the applicability of such imaging technology for PSP. Details of camera performance are benchmarked and compared to standard scientific imaging equipment and subsequent PSP tests are conducted using a static calibration chamber. The findings demonstrate that machine vision technology can be used for PSP measurements, opening up the possibility of performing measurements on-board small-scale model such as those used for wind tunnel testing or measurements in confined spaces with limited optical access.

  19. Distance based control system for machine vision-based selective spraying

    NARCIS (Netherlands)

    Steward, B.L.; Tian, L.F.; Tang, L.

    2002-01-01

    For effective operation of a selective sprayer with real-time local weed sensing, herbicides must be delivered, accurately to weed targets in the field. With a machine vision-based selective spraying system, acquiring sequential images and switching nozzles on and off at the correct locations are

  20. Performance of Color Camera Machine Vision in Automated Furniture Rough Mill Systems

    Science.gov (United States)

    D. Earl Kline; Agus Widoyoko; Janice K. Wiedenbeck; Philip A. Araman

    1998-01-01

    The objective of this study was to evaluate the performance of color camera machine vision for lumber processing in a furniture rough mill. The study used 134 red oak boards to compare the performance of automated gang-rip-first rough mill yield based on a prototype color camera lumber inspection system developed at Virginia Tech with both estimated optimum rough mill...

  1. Possible Computer Vision Systems and Automated or Computer-Aided Edging and Trimming

    Science.gov (United States)

    Philip A. Araman

    1990-01-01

    This paper discusses research which is underway to help our industry reduce costs, increase product volume and value recovery, and market more accurately graded and described products. The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or computer controlled processing. This paper...

  2. Novel compact panomorph lens based vision system for monitoring around a vehicle

    Science.gov (United States)

    Thibault, Simon

    2008-04-01

    Automotive applications are one of the largest vision-sensor market segments and one of the fastest growing ones. The trend to use increasingly more sensors in cars is driven both by legislation and consumer demands for higher safety and better driving experiences. Awareness of what directly surrounds a vehicle affects safe driving and manoeuvring of a vehicle. Consequently, panoramic 360° Field of View imaging can contributes most to the perception of the world around the driver than any other sensors. However, to obtain a complete vision around the car, several sensor systems are necessary. To solve this issue, a customized imaging system based on a panomorph lens will provide the maximum information for the drivers with a reduced number of sensors. A panomorph lens is a hemispheric wide angle anamorphic lens with enhanced resolution in predefined zone of interest. Because panomorph lenses are optimized to a custom angle-to-pixel relationship, vision systems provide ideal image coverage that reduces and optimizes the processing. We present various scenarios which may benefit from the use of a custom panoramic sensor. We also discuss the technical requirements of such vision system. Finally we demonstrate how the panomorph based visual sensor is probably one of the most promising ways to fuse many sensors in one. For example, a single panoramic sensor on the front of a vehicle could provide all necessary information for assistance in crash avoidance, lane tracking, early warning, park aids, road sign detection, and various video monitoring views.

  3. Surface Casting Defects Inspection Using Vision System and Neural Network Techniques

    Directory of Open Access Journals (Sweden)

    Świłło S.J.

    2013-12-01

    Full Text Available The paper presents a vision based approach and neural network techniques in surface defects inspection and categorization. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks and pores that greatly influence the material’s properties Since the human visual inspection for the surface is slow and expensive, a computer vision system is an alternative solution for the online inspection. The authors present the developed vision system uses an advanced image processing algorithm based on modified Laplacian of Gaussian edge detection method and advanced lighting system. The defect inspection algorithm consists of several parameters that allow the user to specify the sensitivity level at which he can accept the defects in the casting. In addition to the developed image processing algorithm and vision system apparatus, an advanced learning process has been developed, based on neural network techniques. Finally, as an example three groups of defects were investigated demonstrates automatic selection and categorization of the measured defects, such as blowholes, shrinkage porosity and shrinkage cavity.

  4. Demo : an embedded vision system for high frame rate visual servoing

    NARCIS (Netherlands)

    Ye, Z.; He, Y.; Pieters, R.S.; Mesman, B.; Corporaal, H.; Jonker, P.P.

    2011-01-01

    The frame rate of commercial off-the-shelf industrial cameras is breaking the threshold of 1000 frames-per-second, the sample rate required in high performance motion control systems. On the one hand, it enables computer vision as a cost-effective feedback source; On the other hand, it imposes

  5. THE SYSTEM OF TECHNICAL VISION IN THE ARCHITECTURE OF THE REMOTE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    S. V. Shavetov

    2014-03-01

    Full Text Available The paper deals with the development of video broadcasting system in view of controlling mobile robots over the Internet. A brief overview of the issues and their solutions, encountered in the real-time broadcasting video stream, is given. Affordable and versatile solutions of technical vision are considered. An approach for frame-accurate video rebroadcasting to unlimited number of end-users is proposed. The optimal performance parameters of network equipment for the final number of cameras are defined. System approbation on five IP cameras of different manufacturers is done. The average time delay for broadcasting in MJPEG format over the local network was 200 ms and 500 ms over the Internet.

  6. A low-cost machine vision system for the recognition and sorting of small parts

    Science.gov (United States)

    Barea, Gustavo; Surgenor, Brian W.; Chauhan, Vedang; Joshi, Keyur D.

    2018-04-01

    An automated machine vision-based system for the recognition and sorting of small parts was designed, assembled and tested. The system was developed to address a need to expose engineering students to the issues of machine vision and assembly automation technology, with readily available and relatively low-cost hardware and software. This paper outlines the design of the system and presents experimental performance results. Three different styles of plastic gears, together with three different styles of defective gears, were used to test the system. A pattern matching tool was used for part classification. Nine experiments were conducted to demonstrate the effects of changing various hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. It was found that the system could achieve a maximum system accuracy of 95% at a feed rate of 60 parts/min, for a given set of parameter settings. Future work will be looking at the effect of lighting.

  7. Development of a body motion interactive system with a weight voting mechanism and computer vision technology

    Science.gov (United States)

    Lin, Chern-Sheng; Chen, Chia-Tse; Shei, Hung-Jung; Lay, Yun-Long; Chiu, Chuang-Chien

    2012-09-01

    This study develops a body motion interactive system with computer vision technology. This application combines interactive games, art performing, and exercise training system. Multiple image processing and computer vision technologies are used in this study. The system can calculate the characteristics of an object color, and then perform color segmentation. When there is a wrong action judgment, the system will avoid the error with a weight voting mechanism, which can set the condition score and weight value for the action judgment, and choose the best action judgment from the weight voting mechanism. Finally, this study estimated the reliability of the system in order to make improvements. The results showed that, this method has good effect on accuracy and stability during operations of the human-machine interface of the sports training system.

  8. Using Vision System Technologies to Enable Operational Improvements for Low Visibility Approach and Landing Operations

    Science.gov (United States)

    Kramer, Lynda J.; Ellis, Kyle K. E.; Bailey, Randall E.; Williams, Steven P.; Severance, Kurt; Le Vie, Lisa R.; Comstock, James R.

    2014-01-01

    Flight deck-based vision systems, such as Synthetic and Enhanced Vision System (SEVS) technologies, have the potential to provide additional margins of safety for aircrew performance and enable the implementation of operational improvements for low visibility surface, arrival, and departure operations in the terminal environment with equivalent efficiency to visual operations. To achieve this potential, research is required for effective technology development and implementation based upon human factors design and regulatory guidance. This research supports the introduction and use of Synthetic Vision Systems and Enhanced Flight Vision Systems (SVS/EFVS) as advanced cockpit vision technologies in Next Generation Air Transportation System (NextGen) operations. Twelve air transport-rated crews participated in a motion-base simulation experiment to evaluate the use of SVS/EFVS in NextGen low visibility approach and landing operations. Three monochromatic, collimated head-up display (HUD) concepts (conventional HUD, SVS HUD, and EFVS HUD) and two color head-down primary flight display (PFD) concepts (conventional PFD, SVS PFD) were evaluated in a simulated NextGen Chicago O'Hare terminal environment. Additionally, the instrument approach type (no offset, 3 degree offset, 15 degree offset) was experimentally varied to test the efficacy of the HUD concepts for offset approach operations. The data showed that touchdown landing performance were excellent regardless of SEVS concept or type of offset instrument approach being flown. Subjective assessments of mental workload and situation awareness indicated that making offset approaches in low visibility conditions with an EFVS HUD or SVS HUD may be feasible.

  9. Pursuit, Avoidance, and Cohesion in Flight: Multi-Purpose Control Laws and Neuromorphic VLSI

    Science.gov (United States)

    2010-10-01

    spatial navigation in mammals. We have designed, fabricated, and are now testing a neuromorphic VLSI chip that implements a spike-based, attractor...Control Laws and Neuromorphic VLSI 5a. CONTRACT NUMBER 070402-7705 5b. GRANT NUMBER FA9550-07-1-0446 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...implementations (custom Neuromorphic VLSI and robotics) we will apply important practical constraints that can lead to deeper insight into how and why efficient

  10. Automatic behaviour analysis system for honeybees using computer vision

    DEFF Research Database (Denmark)

    Tu, Gang Jun; Hansen, Mikkel Kragh; Kryger, Per

    2016-01-01

    We present a fully automatic online video system, which is able to detect the behaviour of honeybees at the beehive entrance. Our monitoring system focuses on observing the honeybees as naturally as possible (i.e. without disturbing the honeybees). It is based on the Raspberry Pi that is a low...

  11. Vision-based robotic system for object agnostic placing operations

    DEFF Research Database (Denmark)

    Rofalis, Nikolaos; Nalpantidis, Lazaros; Andersen, Nils Axel

    2016-01-01

    Industrial robots are part of almost all modern factories. Even though, industrial robots nowadays manipulate objects of a huge variety in different environments, exact knowledge about both of them is generally assumed. The aim of this work is to investigate the ability of a robotic system to ope...... to the system, neither for the objects nor for the placing box. The experimental evaluation of the developed robotic system shows that a combination of seemingly simple modules and strategies can provide effective solution to the targeted problem....... to operate within an unknown environment manipulating unknown objects. The developed system detects objects, finds matching compartments in a placing box, and ultimately grasps and places the objects there. The developed system exploits 3D sensing and visual feature extraction. No prior knowledge is provided...

  12. A vision-based system for fast and accurate laser scanning in robot-assisted phonomicrosurgery.

    Science.gov (United States)

    Dagnino, Giulio; Mattos, Leonardo S; Caldwell, Darwin G

    2015-02-01

    Surgical quality in phonomicrosurgery can be improved by open-loop laser control (e.g., high-speed scanning capabilities) with a robust and accurate closed-loop visual servoing systems. A new vision-based system for laser scanning control during robot-assisted phonomicrosurgery was developed and tested. Laser scanning was accomplished with a dual control strategy, which adds a vision-based trajectory correction phase to a fast open-loop laser controller. The system is designed to eliminate open-loop aiming errors caused by system calibration limitations and by the unpredictable topology of real targets. Evaluation of the new system was performed using CO(2) laser cutting trials on artificial targets and ex-vivo tissue. This system produced accuracy values corresponding to pixel resolution even when smoke created by the laser-target interaction clutters the camera view. In realistic test scenarios, trajectory following RMS errors were reduced by almost 80 % with respect to open-loop system performances, reaching mean error values around 30 μ m and maximum observed errors in the order of 60 μ m. A new vision-based laser microsurgical control system was shown to be effective and promising with significant positive potential impact on the safety and quality of laser microsurgeries.

  13. Distributed Electrical Energy Systems: Needs, Concepts, Approaches and Vision

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Jun [University of Denver; Gao, Wenzhong [University of Denver; Zheng, Xinhu [University of Minnesota; Yang, Liuqing [Colorado State University; Hao, Jun [University of Denver; Dai, Xiaoxiao [University of Denver

    2017-09-01

    Intelligent distributed electrical energy systems (IDEES) are featured by vast system components, diversifled component types, and difficulties in operation and management, which results in that the traditional centralized power system management approach no longer flts the operation. Thus, it is believed that the blockchain technology is one of the important feasible technical paths for building future large-scale distributed electrical energy systems. An IDEES is inherently with both social and technical characteristics, as a result, a distributed electrical energy system needs to be divided into multiple layers, and at each layer, a blockchain is utilized to model and manage its logic and physical functionalities. The blockchains at difierent layers coordinate with each other and achieve successful operation of the IDEES. Speciflcally, the multi-layer blockchains, named 'blockchain group', consist of distributed data access and service blockchain, intelligent property management blockchain, power system analysis blockchain, intelligent contract operation blockchain, and intelligent electricity trading blockchain. It is expected that the blockchain group can be self-organized into a complex, autonomous and distributed IDEES. In this complex system, frequent and in-depth interactions and computing will derive intelligence, and it is expected that such intelligence can bring stable, reliable and efficient electrical energy production, transmission and consumption.

  14. Development of a model of machine hand eye coordination and program specifications for a topological machine vision system

    Science.gov (United States)

    1972-01-01

    A unified approach to computer vision and manipulation is developed which is called choreographic vision. In the model, objects to be viewed by a projected robot in the Viking missions to Mars are seen as objects to be manipulated within choreographic contexts controlled by a multimoded remote, supervisory control system on Earth. A new theory of context relations is introduced as a basis for choreographic programming languages. A topological vision model is developed for recognizing objects by shape and contour. This model is integrated with a projected vision system consisting of a multiaperture image dissector TV camera and a ranging laser system. System program specifications integrate eye-hand coordination and topological vision functions and an aerospace multiprocessor implementation is described.

  15. Utilization of the Space Vision System as an Augmented Reality System For Mission Operations

    Science.gov (United States)

    Maida, James C.; Bowen, Charles

    2003-01-01

    Augmented reality is a technique whereby computer generated images are superimposed on live images for visual enhancement. Augmented reality can also be characterized as dynamic overlays when computer generated images are registered with moving objects in a live image. This technique has been successfully implemented, with low to medium levels of registration precision, in an NRA funded project entitled, "Improving Human Task Performance with Luminance Images and Dynamic Overlays". Future research is already being planned to also utilize a laboratory-based system where more extensive subject testing can be performed. However successful this might be, the problem will still be whether such a technology can be used with flight hardware. To answer this question, the Canadian Space Vision System (SVS) will be tested as an augmented reality system capable of improving human performance where the operation requires indirect viewing. This system has already been certified for flight and is currently flown on each shuttle mission for station assembly. Successful development and utilization of this system in a ground-based experiment will expand its utilization for on-orbit mission operations. Current research and development regarding the use of augmented reality technology is being simulated using ground-based equipment. This is an appropriate approach for development of symbology (graphics and annotation) optimal for human performance and for development of optimal image registration techniques. It is anticipated that this technology will become more pervasive as it matures. Because we know what and where almost everything is on ISS, this reduces the registration problem and improves the computer model of that reality, making augmented reality an attractive tool, provided we know how to use it. This is the basis for current research in this area. However, there is a missing element to this process. It is the link from this research to the current ISS video system and to

  16. Experiments on mobile robot stereo vision system calibration under hardware imperfection

    Directory of Open Access Journals (Sweden)

    Safin Ramil

    2018-01-01

    Full Text Available Calibration is essential for any robot vision system for achieving high accuracy in deriving objects metric information. One of typical requirements for a stereo vison system in order to obtain better calibration results is to guarantee that both cameras keep the same vertical level. However, cameras may be displaced due to severe conditions of a robot operating or some other circumstances. This paper presents our experimental approach to the problem of a mobile robot stereo vision system calibration under a hardware imperfection. In our experiments, we used crawler-type mobile robot «Servosila Engineer». Stereo system cameras of the robot were displaced relative to each other, causing loss of surrounding environment information. We implemented and verified checkerboard and circle grid based calibration methods. The two methods comparison demonstrated that a circle grid based calibration should be preferred over a classical checkerboard calibration approach.

  17. Data Fusion for a Vision-Radiological System: a Statistical Calibration Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip [University of Florida, Gainesville, FL 32611 (United States)

    2015-07-01

    Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data. (authors)

  18. Data Fusion for a Vision-Radiological System: a Statistical Calibration Algorithm

    International Nuclear Information System (INIS)

    Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip

    2015-01-01

    Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data. (authors)

  19. Virtual vision system with actual flavor by olfactory display

    Science.gov (United States)

    Sakamoto, Kunio; Kanazawa, Fumihiro

    2010-11-01

    The authors have researched multimedia system and support system for nursing studies on and practices of reminiscence therapy and life review therapy. The concept of the life review is presented by Butler in 1963. The process of thinking back on one's life and communicating about one's life to another person is called life review. There is a famous episode concerning the memory. It is called as Proustian effects. This effect is mentioned on the Proust's novel as an episode that a story teller reminds his old memory when he dipped a madeleine in tea. So many scientists research why smells trigger the memory. The authors pay attention to the relation between smells and memory although the reason is not evident yet. Then we have tried to add an olfactory display to the multimedia system so that the smells become a trigger of reminding buried memories. An olfactory display is a device that delivers smells to the nose. It provides us with special effects, for example to emit smell as if you were there or to give a trigger for reminding us of memories. The authors have developed a tabletop display system connected with the olfactory display. For delivering a flavor to user's nose, the system needs to recognition and measure positions of user's face and nose. In this paper, the authors describe an olfactory display which enables to detect the nose position for an effective delivery.

  20. Development of Neuromorphic Sift Operator with Application to High Speed Image Matching

    Science.gov (United States)

    Shankayi, M.; Saadatseresht, M.; Bitetto, M. A. V.

    2015-12-01

    There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.

  1. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

    Directory of Open Access Journals (Sweden)

    Massimiliano eGiulioni

    2016-02-01

    Full Text Available We demonstrate robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission and follows the basic theoretical principles presented in (Benosman et al. 2014: the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. The same basic principle is embedded in the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina. Mimicking those cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. We built a 3x3 test grid of independent detectors, each observing a different portion of the scene, so that our final output is a spike train encoding a 3x3 optical flow vector field. In this work we focus on the architectural aspects, and we demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene.

  2. Vision Analysis System for Autonomous Landing of Micro Drone

    Directory of Open Access Journals (Sweden)

    Skoczylas Marcin

    2014-12-01

    Full Text Available This article describes a concept of an autonomous landing system of UAV (Unmanned Aerial Vehicle. This type of device is equipped with the functionality of FPV observation (First Person View and radio broadcasting of video or image data. The problem is performance of a system of autonomous drone landing in an area with dimensions of 1m × 1m, based on CCD camera coupled with an image transmission system connected to a base station. Captured images are scanned and landing marker is detected. For this purpose, image features detectors (such as SIFT, SURF or BRISK are utilized to create a database of keypoints of the landing marker and in a new image keypoints are found using the same feature detector. In this paper results of a framework that allows detection of defined marker for the purpose of drone landing field positioning will be presented.

  3. Vision-Based System for Human Detection and Tracking in Indoor Environment

    OpenAIRE

    Benezeth , Yannick; Emile , Bruno; Laurent , Hélène; Rosenberger , Christophe

    2010-01-01

    International audience; In this paper, we propose a vision-based system for human detection and tracking in indoor environment using a static camera. The proposed method is based on object recognition in still images combined with methods using temporal information from the video. Doing that, we improve the performance of the overall system and reduce the task complexity. We first use background subtraction to limit the search space of the classifier. The segmentation is realized by modeling ...

  4. Gestalt Principles for Attention and Segmentation in Natural and Artificial Vision Systems

    OpenAIRE

    Kootstra, Gert; Bergström, Niklas; Kragic, Danica

    2011-01-01

    Gestalt psychology studies how the human visual system organizes the complex visual input into unitary elements. In this paper we show how the Gestalt principles for perceptual grouping and for figure-ground segregation can be used in computer vision. A number of studies will be shown that demonstrate the applicability of Gestalt principles for the prediction of human visual attention and for the automatic detection and segmentation of unknown objects by a robotic system. QC 20111115 E...

  5. A Model Vision of Sorting System Application Using Robotic Manipulator

    Directory of Open Access Journals (Sweden)

    Maralo Sinaga

    2010-08-01

    Full Text Available Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system in the Moduler Processing System (MPS laboratory which consists of four integrated stations of distribution, testing, processing and handling with a new image processing feature. Existing sorting method uses a set of inductive, capacitive and optical sensors do differentiate object color. This paper presents a mechatronics color sorting system solution with the application of image processing. Supported by OpenCV, image processing procedure senses the circular objects in an image captured in realtime by a webcam and then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator (Mitsubishi Movemaster RV-M1 that does pick-and-place mechanism. Extensive testing proves that this color based object sorting system works 100% accurate under ideal condition in term of adequate illumination, circular objects’ shape and color. The circular objects tested for sorting are silver, red and black. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

  6. Enhanced 3D face processing using an active vision system

    DEFF Research Database (Denmark)

    Lidegaard, Morten; Larsen, Rasmus; Kraft, Dirk

    2014-01-01

    We present an active face processing system based on 3D shape information extracted by means of stereo information. We use two sets of stereo cameras with different field of views (FOV): One with a wide FOV is used for face tracking, while the other with a narrow FOV is used for face identification...

  7. CATEGORIZATION OF EXTRANEOUS MATTER IN COTTON USING MACHINE VISION SYSTEMS

    Science.gov (United States)

    The Cotton Trash Identification System (CTIS) was developed at the Southwestern Cotton Ginning Research Laboratory to identify and categorize extraneous matter in cotton. The CTIS bark/grass categorization was evaluated with USDA-Agricultural Marketing Service (AMS) extraneous matter calls assigned ...

  8. A Multiple Sensor Machine Vision System Technology for the Hardwood

    Science.gov (United States)

    Richard W. Conners; D.Earl Kline; Philip A. Araman

    1995-01-01

    For the last few years the authors have been extolling the virtues of a multiple sensor approach to hardwood defect detection. Since 1989 the authors have actively been trying to develop such a system. This paper details some of the successes and failures that have been experienced to date. It also discusses what remains to be done and gives time lines for the...

  9. Using Scenario Visioning and Participatory System Dynamics Modeling to Investigate the Future: Lessons from Minnesota 2050

    Directory of Open Access Journals (Sweden)

    Kathryn J. Draeger

    2010-08-01

    Full Text Available Both scenario visioning and participatory system dynamics modeling emphasize the dynamic and uncontrollable nature of complex socio-ecological systems, and the significance of multiple feedback mechanisms. These two methodologies complement one another, but are rarely used together. We partnered with regional organizations in Minnesota to design a future visioning process that incorporated both scenarios and participatory system dynamics modeling. The three purposes of this exercise were: first, to assist regional leaders in making strategic decisions that would make their communities sustainable; second, to identify research gaps that could impede the ability of regional and state groups to plan for the future; and finally, to introduce more systems thinking into planning and policy-making around environmental issues. We found that scenarios and modeling complemented one another, and that both techniques allowed regional groups to focus on the sustainability of fundamental support systems (energy, food, and water supply. The process introduced some creative tensions between imaginative scenario visioning and quantitative system dynamics modeling, and between creating desired futures (a strong cultural norm and inhabiting the future (a premise of the Minnesota 2050 exercise. We suggest that these tensions can stimulate more agile, strategic thinking about the future.

  10. Object Tracking Vision System for Mapping the UCN τ Apparatus Volume

    Science.gov (United States)

    Lumb, Rowan; UCNtau Collaboration

    2016-09-01

    The UCN τ collaboration has an immediate goal to measure the lifetime of the free neutron to within 0.1%, i.e. about 1 s. The UCN τ apparatus is a magneto-gravitational ``bottle'' system. This system holds low energy, or ultracold, neutrons in the apparatus with the constraint of gravity, and keeps these low energy neutrons from interacting with the bottle via a strong 1 T surface magnetic field created by a bowl-shaped array of permanent magnets. The apparatus is wrapped with energized coils to supply a magnetic field throughout the ''bottle'' volume to prevent depolarization of the neutrons. An object-tracking stereo-vision system will be presented that precisely tracks a Hall probe and allows a mapping of the magnetic field throughout the volume of the UCN τ bottle. The stereo-vision system utilizes two cameras and open source openCV software to track an object's 3-d position in space in real time. The desired resolution is +/-1 mm resolution along each axis. The vision system is being used as part of an even larger system to map the magnetic field of the UCN τ apparatus and expose any possible systematic effects due to field cancellation or low field points which could allow neutrons to depolarize and possibly escape from the apparatus undetected. Tennessee Technological University.

  11. Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

    Science.gov (United States)

    Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

    An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

  12. Development of Non-contact Respiratory Monitoring System for Newborn Using a FG Vision Sensor

    Science.gov (United States)

    Kurami, Yoshiyuki; Itoh, Yushi; Natori, Michiya; Ohzeki, Kazuo; Aoki, Yoshimitsu

    In recent years, development of neonatal care is strongly hoped, with increase of the low-birth-weight baby birth rate. Especially respiration of low-birth-weight baby is incertitude because central nerve and respiratory function is immature. Therefore, a low-birth-weight baby often causes a disease of respiration. In a NICU (Neonatal Intensive Care Unit), neonatal respiration is monitored using cardio-respiratory monitor and pulse oximeter at all times. These contact-type sensors can measure respiratory rate and SpO2 (Saturation of Peripheral Oxygen). However, because a contact-type sensor might damage the newborn's skin, it is a real burden to monitor neonatal respiration. Therefore, we developed the respiratory monitoring system for newborn using a FG (Fiber Grating) vision sensor. FG vision sensor is an active stereo vision sensor, it is possible for non-contact 3D measurement. A respiratory waveform is calculated by detecting the vertical motion of the thoracic and abdominal region with respiration. We attempted clinical experiment in the NICU, and confirmed the accuracy of the obtained respiratory waveform was high. Non-contact respiratory monitoring of newborn using a FG vision sensor enabled the minimally invasive procedure.

  13. Intelligent Machine Vision Based Modeling and Positioning System in Sand Casting Process

    Directory of Open Access Journals (Sweden)

    Shahid Ikramullah Butt

    2017-01-01

    Full Text Available Advanced vision solutions enable manufacturers in the technology sector to reconcile both competitive and regulatory concerns and address the need for immaculate fault detection and quality assurance. The modern manufacturing has completely shifted from the manual inspections to the machine assisted vision inspection methodology. Furthermore, the research outcomes in industrial automation have revolutionized the whole product development strategy. The purpose of this research paper is to introduce a new scheme of automation in the sand casting process by means of machine vision based technology for mold positioning. Automation has been achieved by developing a novel system in which casting molds of different sizes, having different pouring cup location and radius, position themselves in front of the induction furnace such that the center of pouring cup comes directly beneath the pouring point of furnace. The coordinates of the center of pouring cup are found by using computer vision algorithms. The output is then transferred to a microcontroller which controls the alignment mechanism on which the mold is placed at the optimum location.

  14. Design and Assessment of a Machine Vision System for Automatic Vehicle Wheel Alignment

    Directory of Open Access Journals (Sweden)

    Rocco Furferi

    2013-05-01

    Full Text Available Abstract Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturers' specifications, is a crucial task in the automotive field since it prevents irregular tyre wear and affects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels' characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision-based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems.

  15. Development of 3D online contact measurement system for intelligent manufacturing based on stereo vision

    Science.gov (United States)

    Li, Peng; Chong, Wenyan; Ma, Yongjun

    2017-10-01

    In order to avoid shortcomings of low efficiency and restricted measuring range exsited in traditional 3D on-line contact measurement method for workpiece size, the development of a novel 3D contact measurement system is introduced, which is designed for intelligent manufacturing based on stereo vision. The developed contact measurement system is characterized with an intergarted use of a handy probe, a binocular stereo vision system, and advanced measurement software.The handy probe consists of six track markers, a touch probe and the associated elcetronics. In the process of contact measurement, the hand probe can be located by the use of the stereo vision system and track markers, and 3D coordinates of a space point on the workpiece can be mearsured by calculating the tip position of a touch probe. With the flexibility of the hand probe, the orientation, range, density of the 3D contact measurenent can be adptable to different needs. Applications of the developed contact measurement system to high-precision measurement and rapid surface digitization are experimentally demonstrated.

  16. Cryogenics Vision Workshop for High-Temperature Superconducting Electric Power Systems Proceedings

    International Nuclear Information System (INIS)

    Energetics, Inc.

    2000-01-01

    The US Department of Energy's Superconductivity Program for Electric Systems sponsored the Cryogenics Vision Workshop, which was held on July 27, 1999 in Washington, D.C. This workshop was held in conjunction with the Program's Annual Peer Review meeting. Of the 175 people attending the peer review meeting, 31 were selected in advance to participate in the Cryogenics Vision Workshops discussions. The participants represented cryogenic equipment manufactures, industrial gas manufacturers and distributors, component suppliers, electric power equipment manufacturers (Superconductivity Partnership Initiative participants), electric utilities, federal agencies, national laboratories, and consulting firms. Critical factors were discussed that need to be considered in describing the successful future commercialization of cryogenic systems. Such systems will enable the widespread deployment of high-temperature superconducting (HTS) electric power equipment. Potential research, development, and demonstration (RD and D) activities and partnership opportunities for advancing suitable cryogenic systems were also discussed. The workshop agenda can be found in the following section of this report. Facilitated sessions were held to discuss the following specific focus topics: identifying Critical Factors that need to be included in a Cryogenics Vision for HTS Electric Power Systems (From the HTS equipment end-user perspective) identifying R and D Needs and Partnership Roles (From the cryogenic industry perspective) The findings of the facilitated Cryogenics Vision Workshop were then presented in a plenary session of the Annual Peer Review Meeting. Approximately 120 attendees participated in the afternoon plenary session. This large group heard summary reports from the workshop session leaders and then held a wrap-up session to discuss the findings, cross-cutting themes, and next steps. These summary reports are presented in this document. The ideas and suggestions raised during

  17. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors.

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-12-11

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

  18. A neuromorphic circuit mimicking biological short-term memory.

    Science.gov (United States)

    Barzegarjalali, Saeid; Parker, Alice C

    2016-08-01

    Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

  19. Towards neuromorphic electronics: Memristors on foldable silicon fabric

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-11-01

    The advantages associated with neuromorphic computation are rich areas of complex research. We address the fabrication challenge of building neuromorphic devices on structurally foldable platform with high integration density. We present a CMOS compatible fabrication process to demonstrate for the first time memristive devices fabricated on bulk monocrystalline silicon (100) which is next transformed into a flexible thin sheet of silicon fabric with all the pre-fabricated devices. This process preserves the ultra-high integration density advantage unachievable on other flexible substrates. In addition, the memristive devices are of the size of a motor neuron and the flexible/folded architectural form factor is critical to match brain cortex\\'s folded pattern for ultra-compact design.

  20. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-01-01

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption. PMID:26656113

  1. Qualitative Functional Decomposition Analysis of Evolved Neuromorphic Flight Controllers

    Directory of Open Access Journals (Sweden)

    Sanjay K. Boddhu

    2012-01-01

    Full Text Available In the previous work, it was demonstrated that one can effectively employ CTRNN-EH (a neuromorphic variant of EH method methodology to evolve neuromorphic flight controllers for a flapping wing robot. This paper describes a novel frequency grouping-based analysis technique, developed to qualitatively decompose the evolved controllers into explainable functional control blocks. A summary of the previous work related to evolving flight controllers for two categories of the controller types, called autonomous and nonautonomous controllers, is provided, and the applicability of the newly developed decomposition analysis for both controller categories is demonstrated. Further, the paper concludes with appropriate discussion of ongoing work and implications for possible future work related to employing the CTRNN-EH methodology and the decomposition analysis techniques presented in this paper.

  2. Vision systems for the inspection of resistance welding joints

    Science.gov (United States)

    Hildebrand, Lars; Fathi, Madjid

    2000-06-01

    Many automated quality inspection systems make use of brightness and contrast features of the objects being inspected. This reduces the complexity of the problem solving methods, as well as the demand for computational capacity. Nevertheless a lot of significant information is located in color features of the objects. This paper describes a method, that allows the evaluation of color information in a very compact and efficient way. The described method uses a combination of multi-valued logic and a special color model. We use fuzzy logic as multi-valued logic, and the HSI color model, but any multi-valued logic, that allows rule-based reasoning can be used. The HSI color model can also be exchanged with other color models, if special demands require this.

  3. HDR video synthesis for vision systems in dynamic scenes

    Science.gov (United States)

    Shopovska, Ivana; Jovanov, Ljubomir; Goossens, Bart; Philips, Wilfried

    2016-09-01

    High dynamic range (HDR) image generation from a number of differently exposed low dynamic range (LDR) images has been extensively explored in the past few decades, and as a result of these efforts a large number of HDR synthesis methods have been proposed. Since HDR images are synthesized by combining well-exposed regions of the input images, one of the main challenges is dealing with camera or object motion. In this paper we propose a method for the synthesis of HDR video from a single camera using multiple, differently exposed video frames, with circularly alternating exposure times. One of the potential applications of the system is in driver assistance systems and autonomous vehicles, involving significant camera and object movement, non- uniform and temporally varying illumination, and the requirement of real-time performance. To achieve these goals simultaneously, we propose a HDR synthesis approach based on weighted averaging of aligned radiance maps. The computational complexity of high-quality optical flow methods for motion compensation is still pro- hibitively high for real-time applications. Instead, we rely on more efficient global projective transformations to solve camera movement, while moving objects are detected by thresholding the differences between the trans- formed and brightness adapted images in the set. To attain temporal consistency of the camera motion in the consecutive HDR frames, the parameters of the perspective transformation are stabilized over time by means of computationally efficient temporal filtering. We evaluated our results on several reference HDR videos, on synthetic scenes, and using 14-bit raw images taken with a standard camera.

  4. Regenerative memory in time-delayed neuromorphic photonic resonators

    OpenAIRE

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the...

  5. Development and Application of the Stereo Vision Tracking System with Virtual Reality

    Directory of Open Access Journals (Sweden)

    Chia-Sui Wang

    2015-01-01

    Full Text Available A virtual reality (VR driver tracking verification system is created, of which the application to stereo image tracking and positioning accuracy is researched in depth. In the research, the feature that the stereo vision system has image depth is utilized to improve the error rate of image tracking and image measurement. In a VR scenario, the function collecting behavioral data of driver was tested. By means of VR, racing operation is simulated and environmental (special weathers such as raining and snowing and artificial (such as sudden crossing road by pedestrians, appearing of vehicles from dead angles, roadblock variables are added as the base for system implementation. In addition, the implementation is performed with human factors engineered according to sudden conditions that may happen easily in driving. From experimental results, it proves that the stereo vision system created by the research has an image depth recognition error rate within 0.011%. The image tracking error rate may be smaller than 2.5%. In the research, the image recognition function of stereo vision is utilized to accomplish the data collection of driver tracking detection. In addition, the environmental conditions of different simulated real scenarios may also be created through VR.

  6. Accuracy improvement in a calibration test bench for accelerometers by a vision system

    International Nuclear Information System (INIS)

    D’Emilia, Giulio; Di Gasbarro, David; Gaspari, Antonella; Natale, Emanuela

    2016-01-01

    A procedure is described in this paper for the accuracy improvement of calibration of low-cost accelerometers in a prototype rotary test bench, driven by a brushless servo-motor and operating in a low frequency range of vibrations (0 to 5 Hz). Vibration measurements by a vision system based on a low frequency camera have been carried out, in order to reduce the uncertainty of the real acceleration evaluation at the installation point of the sensor to be calibrated. A preliminary test device has been realized and operated in order to evaluate the metrological performances of the vision system, showing a satisfactory behavior if the uncertainty measurement is taken into account. A combination of suitable settings of the control parameters of the motion control system and of the information gained by the vision system allowed to fit the information about the reference acceleration at the installation point to the needs of the procedure for static and dynamic calibration of three-axis accelerometers.

  7. Accuracy improvement in a calibration test bench for accelerometers by a vision system

    Energy Technology Data Exchange (ETDEWEB)

    D’Emilia, Giulio, E-mail: giulio.demilia@univaq.it; Di Gasbarro, David, E-mail: david.digasbarro@graduate.univaq.it; Gaspari, Antonella, E-mail: antonella.gaspari@graduate.univaq.it; Natale, Emanuela, E-mail: emanuela.natale@univaq.it [University of L’Aquila, Department of Industrial and Information Engineering and Economics (DIIIE), via G. Gronchi, 18, 67100 L’Aquila (Italy)

    2016-06-28

    A procedure is described in this paper for the accuracy improvement of calibration of low-cost accelerometers in a prototype rotary test bench, driven by a brushless servo-motor and operating in a low frequency range of vibrations (0 to 5 Hz). Vibration measurements by a vision system based on a low frequency camera have been carried out, in order to reduce the uncertainty of the real acceleration evaluation at the installation point of the sensor to be calibrated. A preliminary test device has been realized and operated in order to evaluate the metrological performances of the vision system, showing a satisfactory behavior if the uncertainty measurement is taken into account. A combination of suitable settings of the control parameters of the motion control system and of the information gained by the vision system allowed to fit the information about the reference acceleration at the installation point to the needs of the procedure for static and dynamic calibration of three-axis accelerometers.

  8. An Automatic Assembling System for Sealing Rings Based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Mingyu Gao

    2017-01-01

    Full Text Available In order to grab and place the sealing rings of battery lid quickly and accurately, an automatic assembling system for sealing rings based on machine vision is developed in this paper. The whole system is composed of the light sources, cameras, industrial control units, and a 4-degree-of-freedom industrial robot. Specifically, the sealing rings are recognized and located automatically with the machine vision module. Then industrial robot is controlled for grabbing the sealing rings dynamically under the joint work of multiple control units and visual feedback. Furthermore, the coordinates of the fast-moving battery lid are tracked by the machine vision module. Finally the sealing rings are placed on the sealing ports of battery lid accurately and automatically. Experimental results demonstrate that the proposed system can grab the sealing rings and place them on the sealing port of the fast-moving battery lid successfully. More importantly, the proposed system can improve the efficiency of the battery production line obviously.

  9. Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.

    Science.gov (United States)

    Blasco, José; Munera, Sandra; Aleixos, Nuria; Cubero, Sergio; Molto, Enrique

    Individual items of any agricultural commodity are different from each other in terms of colour, shape or size. Furthermore, as they are living thing, they change their quality attributes over time, thereby making the development of accurate automatic inspection machines a challenging task. Machine vision-based systems and new optical technologies make it feasible to create non-destructive control and monitoring tools for quality assessment to ensure adequate accomplishment of food standards. Such systems are much faster than any manual non-destructive examination of fruit and vegetable quality, thus allowing the whole production to be inspected with objective and repeatable criteria. Moreover, current technology makes it possible to inspect the fruit in spectral ranges beyond the sensibility of the human eye, for instance in the ultraviolet and near-infrared regions. Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. This chapter summarises the current state of the art in these techniques, starting with systems based on colour images for the inspection of conventional colour, shape or external defects and then goes on to consider recent developments in spectral image analysis for internal quality assessment or contaminant detection.

  10. Estimation of Theaflavins (TF) and Thearubigins (TR) Ratio in Black Tea Liquor Using Electronic Vision System

    Science.gov (United States)

    Akuli, Amitava; Pal, Abhra; Ghosh, Arunangshu; Bhattacharyya, Nabarun; Bandhopadhyya, Rajib; Tamuly, Pradip; Gogoi, Nagen

    2011-09-01

    Quality of black tea is generally assessed using organoleptic tests by professional tea tasters. They determine the quality of black tea based on its appearance (in dry condition and during liquor formation), aroma and taste. Variation in the above parameters is actually contributed by a number of chemical compounds like, Theaflavins (TF), Thearubigins (TR), Caffeine, Linalool, Geraniol etc. Among the above, TF and TR are the most important chemical compounds, which actually contribute to the formation of taste, colour and brightness in tea liquor. Estimation of TF and TR in black tea is generally done using a spectrophotometer instrument. But, the analysis technique undergoes a rigorous and time consuming effort for sample preparation; also the operation of costly spectrophotometer requires expert manpower. To overcome above problems an Electronic Vision System based on digital image processing technique has been developed. The system is faster, low cost, repeatable and can estimate the amount of TF and TR ratio for black tea liquor with accuracy. The data analysis is done using Principal Component Analysis (PCA), Multiple Linear Regression (MLR) and Multiple Discriminate Analysis (MDA). A correlation has been established between colour of tea liquor images and TF, TR ratio. This paper describes the newly developed E-Vision system, experimental methods, data analysis algorithms and finally, the performance of the E-Vision System as compared to the results of traditional spectrophotometer.

  11. SailSpy: a vision system for yacht sail shape measurement

    Science.gov (United States)

    Olsson, Olof J.; Power, P. Wayne; Bowman, Chris C.; Palmer, G. Terry; Clist, Roger S.

    1992-11-01

    SailSpy is a real-time vision system which we have developed for automatically measuring sail shapes and masthead rotation on racing yachts. Versions have been used by the New Zealand team in two America's Cup challenges in 1988 and 1992. SailSpy uses four miniature video cameras mounted at the top of the mast to provide views of the headsail and mainsail on either tack. The cameras are connected to the SailSpy computer below deck using lightweight cables mounted inside the mast. Images received from the cameras are automatically analyzed by the SailSpy computer, and sail shape and mast rotation parameters are calculated. The sail shape parameters are calculated by recognizing sail markers (ellipses) that have been attached to the sails, and the mast rotation parameters by recognizing deck markers painted on the deck. This paper describes the SailSpy system and some of the vision algorithms used.

  12. Visions, Scenarios and Action Plans Towards Next Generation Tanzania Power System

    Directory of Open Access Journals (Sweden)

    Alex Kyaruzi

    2012-10-01

    Full Text Available This paper presents strategic visions, scenarios and action plans for enhancing Tanzania Power Systems towards next generation Smart Power Grid. It first introduces the present Tanzanian power grid and the challenges ahead in terms of generation capacity, financial aspect, technical and non-technical losses, revenue loss, high tariff, aging infrastructure, environmental impact and the interconnection with the neighboring countries. Then, the current initiatives undertaken by the Tanzania government in response to the present challenges and the expected roles of smart grid in overcoming these challenges in the future with respect to the scenarios presented are discussed. The developed scenarios along with visions and recommended action plans towards the future Tanzanian power system can be exploited at all governmental levels to achieve public policy goals and help develop business opportunities by motivating domestic and international investments in modernizing the nation’s electric power infrastructure. In return, it should help build the green energy economy.

  13. System of error detection in the manufacture of garments using artificial vision

    Science.gov (United States)

    Moreno, J. J.; Aguila, A.; Partida, E.; Martinez, C. L.; Morales, O.; Tejeida, R.

    2017-12-01

    A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.

  14. Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

    Science.gov (United States)

    Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

    1993-03-01

    The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

  15. Morphological features of the macerated cranial bones registered by the 3D vision system for potential use in forensic anthropology.

    Science.gov (United States)

    Skrzat, Janusz; Sioma, Andrzej; Kozerska, Magdalena

    2013-01-01

    In this paper we present potential usage of the 3D vision system for registering features of the macerated cranial bones. Applied 3D vision system collects height profiles of the object surface and from that data builds a three-dimensional image of the surface. This method appeared to be accurate enough to capture anatomical details of the macerated bones. With the aid of the 3D vision system we generated images of the surface of the human calvaria which was used for testing the system. Performed reconstruction visualized the imprints of the dural vascular system, cranial sutures, and the three-layer structure of the cranial bones observed in the cross-section. We figure out that the 3D vision system may deliver data which can enhance estimation of sex from the osteological material.

  16. Portable electronic vision enhancement systems in comparison with optical magnifiers for near vision activities: an economic evaluation alongside a randomized crossover trial.

    Science.gov (United States)

    Bray, Nathan; Brand, Andrew; Taylor, John; Hoare, Zoe; Dickinson, Christine; Edwards, Rhiannon T

    2017-08-01

    To determine the incremental cost-effectiveness of portable electronic vision enhancement system (p-EVES) devices compared with optical low vision aids (LVAs), for improving near vision visual function, quality of life and well-being of people with a visual impairment. An AB/BA randomized crossover trial design was used. Eighty-two participants completed the study. Participants were current users of optical LVAs who had not tried a p-EVES device before and had a stable visual impairment. The trial intervention was the addition of a p-EVES device to the participant's existing optical LVA(s) for 2 months, and the control intervention was optical LVA use only, for 2 months. Cost-effectiveness and cost-utility analyses were conducted from a societal perspective. The mean cost of the p-EVES intervention was £448. Carer costs were £30 (4.46 hr) less for the p-EVES intervention compared with the LVA only control. The mean difference in total costs was £417. Bootstrapping gave an incremental cost-effectiveness ratio (ICER) of £736 (95% CI £481 to £1525) for a 7% improvement in near vision visual function. Cost per quality-adjusted life year (QALY) ranged from £56 991 (lower 95% CI = £19 801) to £66 490 (lower 95% CI = £23 055). Sensitivity analysis varying the commercial price of the p-EVES device reduced ICERs by up to 75%, with cost per QALYs falling below £30 000. Portable electronic vision enhancement system (p-EVES) devices are likely to be a cost-effective use of healthcare resources for improving near vision visual function, but this does not translate into cost-effective improvements in quality of life, capability or well-being. © 2016 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation and European Association for Vision & Eye Research.

  17. Compensation for positioning error of industrial robot for flexible vision measuring system

    Science.gov (United States)

    Guo, Lei; Liang, Yajun; Song, Jincheng; Sun, Zengyu; Zhu, Jigui

    2013-01-01

    Positioning error of robot is a main factor of accuracy of flexible coordinate measuring system which consists of universal industrial robot and visual sensor. Present compensation methods for positioning error based on kinematic model of robot have a significant limitation that it isn't effective in the whole measuring space. A new compensation method for positioning error of robot based on vision measuring technique is presented. One approach is setting global control points in measured field and attaching an orientation camera to vision sensor. Then global control points are measured by orientation camera to calculate the transformation relation from the current position of sensor system to global coordinate system and positioning error of robot is compensated. Another approach is setting control points on vision sensor and two large field cameras behind the sensor. Then the three dimensional coordinates of control points are measured and the pose and position of sensor is calculated real-timely. Experiment result shows the RMS of spatial positioning is 3.422mm by single camera and 0.031mm by dual cameras. Conclusion is arithmetic of single camera method needs to be improved for higher accuracy and accuracy of dual cameras method is applicable.

  18. Comparison of a multispectral vision system and a colorimeter for the assessment of meat color.

    Science.gov (United States)

    Trinderup, Camilla H; Dahl, Anders; Jensen, Kirsten; Carstensen, Jens Michael; Conradsen, Knut

    2015-04-01

    The color assessment ability of a multispectral vision system is investigated by a comparison study with color measurements from a traditional colorimeter. The experiment involves fresh and processed meat samples. Meat is a complex material; heterogeneous with varying scattering and reflectance properties, so several factors can influence the instrumental assessment of meat color. In order to assess whether two methods are equivalent, the variation due to these factors must be taken into account. A statistical analysis was conducted and showed that on a calibration sheet the two instruments are equally capable of measuring color. Moreover the vision system provides a more color rich assessment of fresh meat samples with a glossier surface, than the colorimeter. Careful studies of the different sources of variation enable an assessment of the order of magnitude of the variability between methods accounting for other sources of variation leading to the conclusion that color assessment using a multispectral vision system is superior to traditional colorimeter assessments. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. The Light Plane Calibration Method of the Laser Welding Vision Monitoring System

    Science.gov (United States)

    Wang, B. G.; Wu, M. H.; Jia, W. P.

    2018-03-01

    According to the aerospace and automobile industry, the sheet steels are the very important parts. In the recent years, laser welding technique had been used to weld the sheet steel part. The seam width between the two parts is usually less than 0.1mm. Because the error of the fixture fixed can’t be eliminated, the welding parts quality can be greatly affected. In order to improve the welding quality, the line structured light is employed in the vision monitoring system to plan the welding path before welding. In order to improve the weld precision, the vision system is located on Z axis of the computer numerical control (CNC) tool. The planar pattern is placed on the X-Y plane of the CNC tool, and the structured light is projected on the planar pattern. The vision system stay at three different positions along the Z axis of the CNC tool, and the camera shoot the image of the planar pattern at every position. Using the calculated the sub-pixel center line of the structure light, the world coordinate of the center light line can be calculated. Thus, the structured light plane can be calculated by fitting the structured light line. Experiment result shows the effective of the proposed method.

  20. A Flexible Fringe Projection Vision System with Extended Mathematical Model for Accurate Three-Dimensional Measurement

    Directory of Open Access Journals (Sweden)

    Suzhi Xiao

    2016-04-01

    Full Text Available In order to acquire an accurate three-dimensional (3D measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the ’phase to 3D coordinates transformation’ are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement.

  1. A Flexible Fringe Projection Vision System with Extended Mathematical Model for Accurate Three-Dimensional Measurement.

    Science.gov (United States)

    Xiao, Suzhi; Tao, Wei; Zhao, Hui

    2016-04-28

    In order to acquire an accurate three-dimensional (3D) measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the 'phase to 3D coordinates transformation' are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement.

  2. Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems.

    Science.gov (United States)

    Ehsan, Shoaib; Clark, Adrian F; Naveed ur Rehman; McDonald-Maier, Klaus D

    2015-07-10

    The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems.

  3. Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems

    Directory of Open Access Journals (Sweden)

    Shoaib Ehsan

    2015-07-01

    Full Text Available The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF, allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video. Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44% in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems.

  4. Micro-vision servo control of a multi-axis alignment system for optical fiber assembly

    International Nuclear Information System (INIS)

    Chen, Weihai; Yu, Fei; Qu, Jianliang; Chen, Wenjie; Zhang, Jianbin

    2017-01-01

    This paper describes a novel optical fiber assembly system featuring a multi-axis alignment function based on micro-vision feedback control. It consists of an active parallel alignment mechanism, a passive compensation mechanism, a micro-gripper and a micro-vision servo control system. The active parallel alignment part is a parallelogram-based design with remote-center-of-motion (RCM) function to achieve precise rotation without fatal lateral motion. The passive mechanism, with five degrees of freedom (5-DOF), is used to implement passive compensation for multi-axis errors. A specially designed 1-DOF micro-gripper mounted onto the active parallel alignment platform is adopted to grasp and rotate the optical fiber. A micro-vision system equipped with two charge-coupled device (CCD) cameras is introduced to observe the small field of view and obtain multi-axis errors for servo feedback control. The two CCD cameras are installed in an orthogonal arrangement—thus the errors can be easily measured via the captured images. Meanwhile, a series of tracking and measurement algorithms based on specific features of the target objects are developed. Details of the force and displacement sensor information acquisition in the assembly experiment are also provided. An experiment demonstrates the validity of the proposed visual algorithm by achieving the task of eliminating errors and inserting an optical fiber to the U-groove accurately. (paper)

  5. Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

    Science.gov (United States)

    Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

    2007-01-01

    Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

  6. Virtual neurorobotics (VNR to accelerate development of plausible neuromorphic brain architectures

    Directory of Open Access Journals (Sweden)

    Philip H Goodman

    2007-11-01

    Full Text Available Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly “intelligent” systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain’s interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products. We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental

  7. Design and Implementation of a Fully Autonomous UAV's Navigator Based on Omni-directional Vision System

    Directory of Open Access Journals (Sweden)

    Seyed Mohammadreza Kasaei

    2011-12-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are the subject of an increasing interest in many applications . UAVs are seeing more widespread use in military, scenic, and civilian sectors in recent years. Autonomy is one of the major advantages of these vehicles. It is then necessary to develop particular sensor in order to provide efficient navigation functions. The helicopter has been stabilized with visual information through the control loop. Omni directional vision can be a useful sensor for this propose. It can be used as the only sensor or as complementary sensor. In this paper , we propose a novel method for path planning on an UAV based on electrical potential .We are using an omni directional vision system for navigating and path planning.

  8. FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

    Science.gov (United States)

    Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

    2011-01-01

    Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

  9. Infrared machine vision system for the automatic detection of olive fruit quality.

    Science.gov (United States)

    Guzmán, Elena; Baeten, Vincent; Pierna, Juan Antonio Fernández; García-Mesa, José A

    2013-11-15

    External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.

  10. Embedded Vehicle Speed Estimation System Using an Asynchronous Temporal Contrast Vision Sensor

    Directory of Open Access Journals (Sweden)

    D. Bauer

    2007-01-01

    Full Text Available This article presents an embedded multilane traffic data acquisition system based on an asynchronous temporal contrast vision sensor, and algorithms for vehicle speed estimation developed to make efficient use of the asynchronous high-precision timing information delivered by this sensor. The vision sensor features high temporal resolution with a latency of less than 100 μs, wide dynamic range of 120 dB of illumination, and zero-redundancy, asynchronous data output. For data collection, processing and interfacing, a low-cost digital signal processor is used. The speed of the detected vehicles is calculated from the vision sensor's asynchronous temporal contrast event data. We present three different algorithms for velocity estimation and evaluate their accuracy by means of calibrated reference measurements. The error of the speed estimation of all algorithms is near zero mean and has a standard deviation better than 3% for both traffic flow directions. The results and the accuracy limitations as well as the combined use of the algorithms in the system are discussed.

  11. Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System

    Directory of Open Access Journals (Sweden)

    Miguel Gavilán

    2012-01-01

    Full Text Available This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM. A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  12. Complete vision-based traffic sign recognition supported by an I2V communication system.

    Science.gov (United States)

    García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel

    2012-01-01

    This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

  13. Present and future of vision systems technologies in commercial flight operations

    Science.gov (United States)

    Ward, Jim

    2016-05-01

    The development of systems to enable pilots of all types of aircraft to see through fog, clouds, and sandstorms and land in low visibility has been widely discussed and researched across aviation. For military applications, the goal has been to operate in a Degraded Visual Environment (DVE), using sensors to enable flight crews to see and operate without concern to weather that limits human visibility. These military DVE goals are mainly oriented to the off-field landing environment. For commercial aviation, the Federal Aviation Agency (FAA) implemented operational regulations in 2004 that allow the flight crew to see the runway environment using an Enhanced Flight Vision Systems (EFVS) and continue the approach below the normal landing decision height. The FAA is expanding the current use and economic benefit of EFVS technology and will soon permit landing without any natural vision using real-time weather-penetrating sensors. The operational goals of both of these efforts, DVE and EFVS, have been the stimulus for development of new sensors and vision displays to create the modern flight deck.

  14. SAD-Based Stereo Vision Machine on a System-on-Programmable-Chip (SoPC)

    Science.gov (United States)

    Zhang, Xiang; Chen, Zhangwei

    2013-01-01

    This paper, proposes a novel solution for a stereo vision machine based on the System-on-Programmable-Chip (SoPC) architecture. The SOPC technology provides great convenience for accessing many hardware devices such as DDRII, SSRAM, Flash, etc., by IP reuse. The system hardware is implemented in a single FPGA chip involving a 32-bit Nios II microprocessor, which is a configurable soft IP core in charge of managing the image buffer and users' configuration data. The Sum of Absolute Differences (SAD) algorithm is used for dense disparity map computation. The circuits of the algorithmic module are modeled by the Matlab-based DSP Builder. With a set of configuration interfaces, the machine can process many different sizes of stereo pair images. The maximum image size is up to 512 K pixels. This machine is designed to focus on real time stereo vision applications. The stereo vision machine offers good performance and high efficiency in real time. Considering a hardware FPGA clock of 90 MHz, 23 frames of 640 × 480 disparity maps can be obtained in one second with 5 × 5 matching window and maximum 64 disparity pixels. PMID:23459385

  15. Comparison of Three Smart Camera Architectures for Real-Time Machine Vision System

    Directory of Open Access Journals (Sweden)

    Abdul Waheed Malik

    2013-12-01

    Full Text Available This paper presents a machine vision system for real-time computation of distance and angle of a camera from a set of reference points located on a target board. Three different smart camera architectures were explored to compare performance parameters such as power consumption, frame speed and latency. Architecture 1 consists of hardware machine vision modules modeled at Register Transfer (RT level and a soft-core processor on a single FPGA chip. Architecture 2 is commercially available software based smart camera, Matrox Iris GT. Architecture 3 is a two-chip solution composed of hardware machine vision modules on FPGA and an external microcontroller. Results from a performance comparison show that Architecture 2 has higher latency and consumes much more power than Architecture 1 and 3. However, Architecture 2 benefits from an easy programming model. Smart camera system with FPGA and external microcontroller has lower latency and consumes less power as compared to single FPGA chip having hardware modules and soft-core processor.

  16. Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

    Science.gov (United States)

    Liu, Xuan; Furrer, David; Kosters, Jared; Holmes, Jack

    2018-01-01

    Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost

  17. Principles of image processing in machine vision systems for the color analysis of minerals

    Science.gov (United States)

    Petukhova, Daria B.; Gorbunova, Elena V.; Chertov, Aleksandr N.; Korotaev, Valery V.

    2014-09-01

    At the moment color sorting method is one of promising methods of mineral raw materials enrichment. This method is based on registration of color differences between images of analyzed objects. As is generally known the problem with delimitation of close color tints when sorting low-contrast minerals is one of the main disadvantages of color sorting method. It is can be related with wrong choice of a color model and incomplete image processing in machine vision system for realizing color sorting algorithm. Another problem is a necessity of image processing features reconfiguration when changing the type of analyzed minerals. This is due to the fact that optical properties of mineral samples vary from one mineral deposit to another. Therefore searching for values of image processing features is non-trivial task. And this task doesn't always have an acceptable solution. In addition there are no uniform guidelines for determining criteria of mineral samples separation. It is assumed that the process of image processing features reconfiguration had to be made by machine learning. But in practice it's carried out by adjusting the operating parameters which are satisfactory for one specific enrichment task. This approach usually leads to the fact that machine vision system unable to estimate rapidly the concentration rate of analyzed mineral ore by using color sorting method. This paper presents the results of research aimed at addressing mentioned shortcomings in image processing organization for machine vision systems which are used to color sorting of mineral samples. The principles of color analysis for low-contrast minerals by using machine vision systems are also studied. In addition, a special processing algorithm for color images of mineral samples is developed. Mentioned algorithm allows you to determine automatically the criteria of mineral samples separation based on an analysis of representative mineral samples. Experimental studies of the proposed algorithm

  18. Vision-Inspection System for Residue Monitoring of Ready-Mixed Concrete Trucks

    Directory of Open Access Journals (Sweden)

    Deok-Seok Seo

    2015-01-01

    Full Text Available The objective of this study is to propose a vision-inspection system that improves the quality management for ready-mixed concrete (RMC. The proposed system can serve as an alternative to the current visual inspection method for the detection of residues in agitator drum of RMC truck. To propose the system, concept development and the system-level design should be executed. The design considerations of the system are derived from the hardware properties of RMC truck and the conditions of RMC factory, and then 6 major components of the system are selected in the stage of system level design. The prototype of system was applied to a real RMC plant and tested for verification of its utility and efficiency. It is expected that the proposed system can be employed as a practical means to increase the efficiency of quality management for RMC.

  19. Neural Summation in the Hawkmoth Visual System Extends the Limits of Vision in Dim Light.

    Science.gov (United States)

    Stöckl, Anna Lisa; O'Carroll, David Charles; Warrant, Eric James

    2016-03-21

    Most of the world's animals are active in dim light and depend on good vision for the tasks of daily life. Many have evolved visual adaptations that permit a performance superior to that of manmade imaging devices [1]. In insects, a major model visual system, nocturnal species show impressive visual abilities ranging from flight control [2, 3], to color discrimination [4, 5], to navigation using visual landmarks [6-8] or dim celestial compass cues [9, 10]. In addition to optical adaptations that improve their sensitivity in dim light [11], neural summation of light in space and time-which enhances the coarser and slower features of the scene at the expense of noisier finer and faster features-has been suggested to improve sensitivity in theoretical [12-14], anatomical [15-17], and behavioral [18-20] studies. How these summation strategies function neurally is, however, presently unknown. Here, we quantified spatial and temporal summation in the motion vision pathway of a nocturnal hawkmoth. We show that spatial and temporal summation combine supralinearly to substantially increase contrast sensitivity and visual information rate over four decades of light intensity, enabling hawkmoths to see at light levels 100 times dimmer than without summation. Our results reveal how visual motion is calculated neurally in dim light and how spatial and temporal summation improve sensitivity while simultaneously maximizing spatial and temporal resolution, thus extending models of insect motion vision derived predominantly from diurnal flies. Moreover, the summation strategies we have revealed may benefit manmade vision systems optimized for variable light levels [21]. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Usability of light-emitting diodes in precision approach path indicator systems by individuals with marginal color vision.

    Science.gov (United States)

    2014-05-01

    To save energy, the FAA is planning to convert from incandescent lights to light-emitting diodes (LEDs) in : precision approach path indicator (PAPI) systems. Preliminary work on the usability of LEDs by color vision-waivered pilots (Bullough, Skinne...

  1. Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

    Science.gov (United States)

    La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien

    2016-12-01

    Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.

  2. EAST-AIA deployment under vacuum: Calibration of laser diagnostic system using computer vision

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Yang, E-mail: yangyang@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, 350 Shushanhu Rd, Hefei, Anhui (China); Song, Yuntao; Cheng, Yong; Feng, Hansheng; Wu, Zhenwei; Li, Yingying; Sun, Yongjun; Zheng, Lei [Institute of Plasma Physics, Chinese Academy of Sciences, 350 Shushanhu Rd, Hefei, Anhui (China); Bruno, Vincent; Eric, Villedieu [CEA-IRFM, F-13108 Saint-Paul-Lez-Durance (France)

    2016-11-15

    Highlights: • The first deployment of the EAST articulated inspection arm robot under vacuum is presented. • A computer vision based approach to measure the laser spot displacement is proposed. • An experiment on the real EAST tokamak is performed to validate the proposed measure approach, and the results shows that the measurement accuracy satisfies the requirement. - Abstract: For the operation of EAST tokamak, it is crucial to ensure that all the diagnostic systems are in the good condition in order to reflect the plasma status properly. However, most of the diagnostic systems are mounted inside the tokamak vacuum vessel, which makes them extremely difficult to maintain under high vacuum condition during the tokamak operation. Thanks to a system called EAST articulated inspection arm robot (EAST-AIA), the examination of these in-vessel diagnostic systems can be performed by an embedded camera carried by the robot. In this paper, a computer vision algorithm has been developed to calibrate a laser diagnostic system with the help of a monocular camera at the robot end. In order to estimate the displacement of the laser diagnostic system with respect to the vacuum vessel, several visual markers were attached to the inner wall. This experiment was conducted both on the EAST vacuum vessel mock-up and the real EAST tokamak under vacuum condition. As a result, the accuracy of the displacement measurement was within 3 mm under the current camera resolution, which satisfied the laser diagnostic system calibration.

  3. System for synthetic vision and augmented reality in future flight decks

    Science.gov (United States)

    Behringer, Reinhold; Tam, Clement K.; McGee, Joshua H.; Sundareswaran, Venkataraman; Vassiliou, Marius S.

    2000-06-01

    Rockwell Science Center is investigating novel human-computer interface techniques for enhancing the situational awareness in future flight decks. One aspect is to provide intuitive displays which provide the vital information and the spatial awareness by augmenting the real world with an overlay of relevant information registered to the real world. Such Augmented Reality (AR) techniques can be employed during bad weather scenarios to permit flying in Visual Flight Rules (VFR) in conditions which would normally require Instrumental Flight Rules (IFR). These systems could easily be implemented on heads-up displays (HUD). The advantage of AR systems vs. purely synthetic vision (SV) systems is that the pilot can relate the information overlay to real objects in the world, whereas SV systems provide a constant virtual view, where inconsistencies can hardly be detected. The development of components for such a system led to a demonstrator implemented on a PC. A camera grabs video images which are overlaid with registered information, Orientation of the camera is obtained from an inclinometer and a magnetometer, position is acquired from GPS. In a possible implementation in an airplane, the on-board attitude information can be used for obtaining correct registration. If visibility is sufficient, computer vision modules can be used to fine-tune the registration by matching visual clues with database features. Such technology would be especially useful for landing approaches. The current demonstrator provides a frame-rate of 15 fps, using a live video feed as background and an overlay of avionics symbology in the foreground. In addition, terrain rendering from a 1 arc sec. digital elevation model database can be overlaid to provide synthetic vision in case of limited visibility. For true outdoor testing (on ground level), the system has been implemented on a wearable computer.

  4. Data fusion for a vision-aided radiological detection system: Calibration algorithm performance

    Science.gov (United States)

    Stadnikia, Kelsey; Henderson, Kristofer; Martin, Allan; Riley, Phillip; Koppal, Sanjeev; Enqvist, Andreas

    2018-05-01

    In order to improve the ability to detect, locate, track and identify nuclear/radiological threats, the University of Florida nuclear detection community has teamed up with the 3D vision community to collaborate on a low cost data fusion system. The key is to develop an algorithm to fuse the data from multiple radiological and 3D vision sensors as one system. The system under development at the University of Florida is being assessed with various types of radiological detectors and widely available visual sensors. A series of experiments were devised utilizing two EJ-309 liquid organic scintillation detectors (one primary and one secondary), a Microsoft Kinect for Windows v2 sensor and a Velodyne HDL-32E High Definition LiDAR Sensor which is a highly sensitive vision sensor primarily used to generate data for self-driving cars. Each experiment consisted of 27 static measurements of a source arranged in a cube with three different distances in each dimension. The source used was Cf-252. The calibration algorithm developed is utilized to calibrate the relative 3D-location of the two different types of sensors without need to measure it by hand; thus, preventing operator manipulation and human errors. The algorithm can also account for the facility dependent deviation from ideal data fusion correlation. Use of the vision sensor to determine the location of a sensor would also limit the possible locations and it does not allow for room dependence (facility dependent deviation) to generate a detector pseudo-location to be used for data analysis later. Using manually measured source location data, our algorithm-predicted the offset detector location within an average of 20 cm calibration-difference to its actual location. Calibration-difference is the Euclidean distance from the algorithm predicted detector location to the measured detector location. The Kinect vision sensor data produced an average calibration-difference of 35 cm and the HDL-32E produced an average

  5. Coupon Test of an Elbow Component by Using Vision-based Measurement System

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung Wan; Jeon, Bub Gyu; Choi, Hyoung Suk; Kim, Nam Sik [Pusan National University, Busan (Korea, Republic of)

    2016-05-15

    Among the various methods to overcome this shortcoming, vision-based methods to measure the strain of a structure are being proposed and many studies are being conducted on them. The vision-based measurement method is a noncontact method for measuring displacement and strain of objects by comparing between images before and after deformation. This method offers such advantages as no limitations in the surface condition, temperature, and shape of objects, the possibility of full filed measurement, and the possibility of measuring the distribution of stress or defects of structures based on the measurement results of displacement and strain in a map. The strains were measured with various methods using images in coupon test and the measurements were compared. In the future, the validity of the algorithm will be compared using stain gauge and clip gage, and based on the results, the physical properties of materials will be measured using a vision-based measurement system. This will contribute to the evaluation of reliability and effectiveness which are required for investigating local damages.

  6. Coupon Test of an Elbow Component by Using Vision-based Measurement System

    International Nuclear Information System (INIS)

    Kim, Sung Wan; Jeon, Bub Gyu; Choi, Hyoung Suk; Kim, Nam Sik

    2016-01-01

    Among the various methods to overcome this shortcoming, vision-based methods to measure the strain of a structure are being proposed and many studies are being conducted on them. The vision-based measurement method is a noncontact method for measuring displacement and strain of objects by comparing between images before and after deformation. This method offers such advantages as no limitations in the surface condition, temperature, and shape of objects, the possibility of full filed measurement, and the possibility of measuring the distribution of stress or defects of structures based on the measurement results of displacement and strain in a map. The strains were measured with various methods using images in coupon test and the measurements were compared. In the future, the validity of the algorithm will be compared using stain gauge and clip gage, and based on the results, the physical properties of materials will be measured using a vision-based measurement system. This will contribute to the evaluation of reliability and effectiveness which are required for investigating local damages

  7. ROV-based Underwater Vision System for Intelligent Fish Ethology Research

    Directory of Open Access Journals (Sweden)

    Rui Nian

    2013-09-01

    Full Text Available Fish ethology is a prospective discipline for ocean surveys. In this paper, one ROV-based system is established to perform underwater visual tasks with customized optical sensors installed. One image quality enhancement method is first presented in the context of creating underwater imaging models combined with homomorphic filtering and wavelet decomposition. The underwater vision system can further detect and track swimming fish from the resulting images with the strategies developed using curve evolution and particular filtering, in order to obtain a deeper understanding of fish behaviours. The simulation results have shown the excellent performance of the developed scheme, in regard to both robustness and effectiveness.

  8. An Application of Computer Vision Systems to Solve the Problem of Unmanned Aerial Vehicle Control

    Directory of Open Access Journals (Sweden)

    Aksenov Alexey Y.

    2014-09-01

    Full Text Available The paper considers an approach for application of computer vision systems to solve the problem of unmanned aerial vehicle control. The processing of images obtained through onboard camera is required for absolute positioning of aerial platform (automatic landing and take-off, hovering etc. used image processing on-board camera. The proposed method combines the advantages of existing systems and gives the ability to perform hovering over a given point, the exact take-off and landing. The limitations of implemented methods are determined and the algorithm is proposed to combine them in order to improve the efficiency.

  9. An Automated Mouse Tail Vascular Access System by Vision and Pressure Feedback.

    Science.gov (United States)

    Chang, Yen-Chi; Berry-Pusey, Brittany; Yasin, Rashid; Vu, Nam; Maraglia, Brandon; Chatziioannou, Arion X; Tsao, Tsu-Chin

    2015-08-01

    This paper develops an automated vascular access system (A-VAS) with novel vision-based vein and needle detection methods and real-time pressure feedback for murine drug delivery. Mouse tail vein injection is a routine but critical step for preclinical imaging applications. Due to the small vein diameter and external disturbances such as tail hair, pigmentation, and scales, identifying vein location is difficult and manual injections usually result in poor repeatability. To improve the injection accuracy, consistency, safety, and processing time, A-VAS was developed to overcome difficulties in vein detection noise rejection, robustness in needle tracking, and visual servoing integration with the mechatronics system.

  10. Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.

    Science.gov (United States)

    Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

    2016-09-14

    Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

  11. Comparison of the Infiniti vision and the series 20,000 Legacy systems.

    Science.gov (United States)

    Fernández de Castro, Luis E; Solomon, Kerry D; Hu, Daniel J; Vroman, David T; Sandoval, Helga P

    2008-01-01

    To compare the efficiency of the Infiniti vision system and the Series 20,000 Legacy system phacoemulsification units during routine cataract extraction. Thirty-nine eyes of 39 patients were randomized to have their cataract removed using either the Infiniti or the Legacy system, both using the Neosonix handpiece. System settings were standardized. Ultrasound time, amount of balanced salt solution (BSS) used intraoperatively, and postoperative visual acuity at postoperative days 1, 7 and 30 were evaluated. Preoperatively, best corrected visual acuity was significantly worse in the Infiniti group compared to the Legacy group (0.38 +/- 0.23 and 0.21 +/- 0.16, respectively; p = 0.012). The mean phacoemulsification time was 39.6 +/- 22.9 s (range 6.0-102.0) for the Legacy group and 18.3 +/-19.1 s (range 1.0-80.0) for the Infiniti group (p = 0.001). The mean amounts of intraoperative BSS used were 117 +/- 37.7 ml (range 70-195) in the Legacy group and 85.3 +/- 38.9 ml (range 40-200) in the Infiniti group (p = 0.005). No differences in postoperative visual acuity were found. The ability to use higher flow rates and vacuum settings with the Infiniti vision system allowed for cataract removal with less phacoemulsification time than when using the Legacy system. Copyright 2008 S. Karger AG, Basel.

  12. Acquisition And Processing Of Range Data Using A Laser Scanner-Based 3-D Vision System

    Science.gov (United States)

    Moring, I.; Ailisto, H.; Heikkinen, T.; Kilpela, A.; Myllyla, R.; Pietikainen, M.

    1988-02-01

    In our paper we describe a 3-D vision system designed and constructed at the Technical Research Centre of Finland in co-operation with the University of Oulu. The main application fields our 3-D vision system was developed for are geometric measurements of large objects and manipulator and robot control tasks. It seems to be potential in automatic vehicle guidance applications, too. The system has now been operative for about one year and its performance has been extensively tested. Recently we have started a field test phase to evaluate its performance in real industrial tasks and environments. The system consists of three main units: the range finder, the scanner and the computer. The range finder is based on the direct measurement of the time-of-flight of a laser pulse. The time-interval between the transmitted and the received light pulses is converted into a continuous analog voltage, which is amplified, filtered and offset-corrected to produce the range information. The scanner consists of two mirrors driven by moving iron galvanometers. This system is controlled by servo amplifiers. The computer unit controls the scanner, transforms the measured coordinates into a cartesian coordinate system and serves as a user interface and postprocessing environment. Methods for segmenting the range image into a higher level description have been developed. The description consists of planar and curved surfaces and their features and relations. Parametric surface representations based on the Ferguson surface patch are studied, too.

  13. Optimization of dynamic envelope measurement system for high speed train based on monocular vision

    Science.gov (United States)

    Wu, Bin; Liu, Changjie; Fu, Luhua; Wang, Zhong

    2018-01-01

    The definition of dynamic envelope curve is the maximum limit outline caused by various adverse effects during the running process of the train. It is an important base of making railway boundaries. At present, the measurement work of dynamic envelope curve of high-speed vehicle is mainly achieved by the way of binocular vision. There are some problems of the present measuring system like poor portability, complicated process and high cost. A new measurement system based on the monocular vision measurement theory and the analysis on the test environment is designed and the measurement system parameters, the calibration of camera with wide field of view, the calibration of the laser plane are designed and optimized in this paper. The accuracy has been verified to be up to 2mm by repeated tests and experimental data analysis. The feasibility and the adaptability of the measurement system is validated. There are some advantages of the system like lower cost, a simpler measurement and data processing process, more reliable data. And the system needs no matching algorithm.

  14. Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

    Science.gov (United States)

    Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

    2016-01-01

    Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. PMID:27649178

  15. Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

    Directory of Open Access Journals (Sweden)

    Basam Musleh

    2016-09-01

    Full Text Available Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels and the vehicle environment (meters depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

  16. Low Vision

    Science.gov (United States)

    ... USAJobs Home » Statistics and Data » Low Vision Listen Low Vision Low Vision Defined: Low Vision is defined as the best- ... Ethnicity 2010 U.S. Age-Specific Prevalence Rates for Low Vision by Age, and Race/Ethnicity Table for 2010 ...

  17. A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

    Directory of Open Access Journals (Sweden)

    Fabio Boi

    2016-12-01

    Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.

  18. A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

    Science.gov (United States)

    Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

    2016-01-01

    Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

  19. A Vision-Based Dynamic Rotational Angle Measurement System for Large Civil Structures

    Science.gov (United States)

    Lee, Jong-Jae; Ho, Hoai-Nam; Lee, Jong-Han

    2012-01-01

    In this paper, we propose a vision-based rotational angle measurement system for large-scale civil structures. Despite the fact that during the last decade several rotation angle measurement systems were introduced, they however often required complex and expensive equipment. Therefore, alternative effective solutions with high resolution are in great demand. The proposed system consists of commercial PCs, commercial camcorders, low-cost frame grabbers, and a wireless LAN router. The calculation of rotation angle is obtained by using image processing techniques with pre-measured calibration parameters. Several laboratory tests were conducted to verify the performance of the proposed system. Compared with the commercial rotation angle measurement, the results of the system showed very good agreement with an error of less than 1.0% in all test cases. Furthermore, several tests were conducted on the five-story modal testing tower with a hybrid mass damper to experimentally verify the feasibility of the proposed system. PMID:22969348

  20. Container-code recognition system based on computer vision and deep neural networks

    Science.gov (United States)

    Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

    2018-04-01

    Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

  1. A neural network based artificial vision system for licence plate recognition.

    Science.gov (United States)

    Draghici, S

    1997-02-01

    This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

  2. Neuromorphic Audio-Visual Sensor Fusion on a Sound-Localising Robot

    Directory of Open Access Journals (Sweden)

    Vincent Yue-Sek Chan

    2012-02-01

    Full Text Available This paper presents the first robotic system featuring audio-visual sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localisation through self-motion and visual feedback, using an adaptive ITD-based sound localisation algorithm. After training, the robot can localise sound sources (white or pink noise in a reverberant environment with an RMS error of 4 to 5 degrees in azimuth. In the second part of the paper, we investigate the source binding problem. An experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. The results show that this technique can be quite effective, despite its simplicity.

  3. Night vision imaging system design, integration and verification in spacecraft vacuum thermal test

    Science.gov (United States)

    Shang, Yonghong; Wang, Jing; Gong, Zhe; Li, Xiyuan; Pei, Yifei; Bai, Tingzhu; Zhen, Haijing

    2015-08-01

    The purposes of spacecraft vacuum thermal test are to characterize the thermal control systems of the spacecraft and its component in its cruise configuration and to allow for early retirement of risks associated with mission-specific and novel thermal designs. The orbit heat flux is simulating by infrared lamp, infrared cage or electric heater. As infrared cage and electric heater do not emit visible light, or infrared lamp just emits limited visible light test, ordinary camera could not operate due to low luminous density in test. Moreover, some special instruments such as satellite-borne infrared sensors are sensitive to visible light and it couldn't compensate light during test. For improving the ability of fine monitoring on spacecraft and exhibition of test progress in condition of ultra-low luminous density, night vision imaging system is designed and integrated by BISEE. System is consist of high-gain image intensifier ICCD camera, assistant luminance system, glare protect system, thermal control system and computer control system. The multi-frame accumulation target detect technology is adopted for high quality image recognition in captive test. Optical system, mechanical system and electrical system are designed and integrated highly adaptable to vacuum environment. Molybdenum/Polyimide thin film electrical heater controls the temperature of ICCD camera. The results of performance validation test shown that system could operate under vacuum thermal environment of 1.33×10-3Pa vacuum degree and 100K shroud temperature in the space environment simulator, and its working temperature is maintains at 5° during two-day test. The night vision imaging system could obtain video quality of 60lp/mm resolving power.

  4. Visual system plasticity in mammals: the story of monocular enucleation-induced vision loss

    Science.gov (United States)

    Nys, Julie; Scheyltjens, Isabelle; Arckens, Lutgarde

    2015-01-01

    The groundbreaking work of Hubel and Wiesel in the 1960’s on ocular dominance plasticity instigated many studies of the visual system of mammals, enriching our understanding of how the development of its structure and function depends on high quality visual input through both eyes. These studies have mainly employed lid suturing, dark rearing and eye patching applied to different species to reduce or impair visual input, and have created extensive knowledge on binocular vision. However, not all aspects and types of plasticity in the visual cortex have been covered in full detail. In that regard, a more drastic deprivation method like enucleation, leading to complete vision loss appears useful as it has more widespread effects on the afferent visual pathway and even on non-visual brain regions. One-eyed vision due to monocular enucleation (ME) profoundly affects the contralateral retinorecipient subcortical and cortical structures thereby creating a powerful means to investigate cortical plasticity phenomena in which binocular competition has no vote.In this review, we will present current knowledge about the specific application of ME as an experimental tool to study visual and cross-modal brain plasticity and compare early postnatal stages up into adulthood. The structural and physiological consequences of this type of extensive sensory loss as documented and studied in several animal species and human patients will be discussed. We will summarize how ME studies have been instrumental to our current understanding of the differentiation of sensory systems and how the structure and function of cortical circuits in mammals are shaped in response to such an extensive alteration in experience. In conclusion, we will highlight future perspectives and the clinical relevance of adding ME to the list of more longstanding deprivation models in visual system research. PMID:25972788

  5. Sound stream segregation: a neuromorphic approach to solve the "cocktail party problem" in real-time.

    Science.gov (United States)

    Thakur, Chetan Singh; Wang, Runchun M; Afshar, Saeed; Hamilton, Tara J; Tapson, Jonathan C; Shamma, Shihab A; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the "cocktail party effect." It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and

  6. Gesture Therapy: A Vision-Based System for Arm Rehabilitation after Stroke

    Science.gov (United States)

    Sucar, L. Enrique; Azcárate, Gildardo; Leder, Ron S.; Reinkensmeyer, David; Hernández, Jorge; Sanchez, Israel; Saucedo, Pedro

    Each year millions of people in the world survive a stroke, in the U.S. alone the figure is over 600,000 people per year. Movement impairments after stroke are typically treated with intensive, hands-on physical and occupational therapy for several weeks after the initial injury. However, due to economic pressures, stroke patients are receiving less therapy and going home sooner, so the potential benefit of the therapy is not completely realized. Thus, it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. Current solutions are too expensive, as they require a robotic system for rehabilitation. We have developed a low-cost, computer vision system that allows individuals with stroke to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a web based virtual environment for facilitating repetitive movement training, with state-of-the art computer vision algorithms that track the hand of a patient and obtain its 3-D coordinates, using two inexpensive cameras and a conventional personal computer. An initial prototype of the system has been evaluated in a pilot clinical study with promising results.

  7. An Integrated Vision-Based System for Spacecraft Attitude and Topology Determination for Formation Flight Missions

    Science.gov (United States)

    Rogers, Aaron; Anderson, Kalle; Mracek, Anna; Zenick, Ray

    2004-01-01

    With the space industry's increasing focus upon multi-spacecraft formation flight missions, the ability to precisely determine system topology and the orientation of member spacecraft relative to both inertial space and each other is becoming a critical design requirement. Topology determination in satellite systems has traditionally made use of GPS or ground uplink position data for low Earth orbits, or, alternatively, inter-satellite ranging between all formation pairs. While these techniques work, they are not ideal for extension to interplanetary missions or to large fleets of decentralized, mixed-function spacecraft. The Vision-Based Attitude and Formation Determination System (VBAFDS) represents a novel solution to both the navigation and topology determination problems with an integrated approach that combines a miniature star tracker with a suite of robust processing algorithms. By combining a single range measurement with vision data to resolve complete system topology, the VBAFDS design represents a simple, resource-efficient solution that is not constrained to certain Earth orbits or formation geometries. In this paper, analysis and design of the VBAFDS integrated guidance, navigation and control (GN&C) technology will be discussed, including hardware requirements, algorithm development, and simulation results in the context of potential mission applications.

  8. Diagnosis System for Diabetic Retinopathy and Glaucoma Screening to Prevent Vision Loss

    Directory of Open Access Journals (Sweden)

    Siva Sundhara Raja DHANUSHKODI

    2014-03-01

    Full Text Available Aim: Diabetic retinopathy (DR and glaucoma are two most common retinal disorders that are major causes of blindness in diabetic patients. DR caused in retinal images due to the damage in retinal blood vessels, which leads to the formation of hemorrhages spread over the entire region of retina. Glaucoma is caused due to hypertension in diabetic patients. Both DR and glaucoma affects the vision loss in diabetic patients. Hence, a computer aided development of diagnosis system for Diabetic retinopathy and Glaucoma screening is proposed in this paper to prevent vision loss. Method: The diagnosis system of DR consists of two stages namely detection and segmentation of fovea and hemorrhages. The diagnosis system of glaucoma screening consists of three stages namely blood vessel segmentation, Extraction of optic disc (OD and optic cup (OC region and determination of rim area between OD and OC. Results: The specificity and accuracy for hemorrhages detection is found to be 98.47% and 98.09% respectively. The accuracy for OD detection is found to be 99.3%. This outperforms state-of-the-art methods. Conclusion: In this paper, the diagnosis system is developed to classify the DR and glaucoma screening in to mild, moderate and severe respectively.

  9. Laser cutting of irregular shape object based on stereo vision laser galvanometric scanning system

    Science.gov (United States)

    Qi, Li; Zhang, Yixin; Wang, Shun; Tang, Zhiqiang; Yang, Huan; Zhang, Xuping

    2015-05-01

    Irregular shape objects with different 3-dimensional (3D) appearances are difficult to be shaped into customized uniform pattern by current laser machining approaches. A laser galvanometric scanning system (LGS) could be a potential candidate since it can easily achieve path-adjustable laser shaping. However, without knowing the actual 3D topography of the object, the processing result may still suffer from 3D shape distortion. It is desirable to have a versatile auxiliary tool that is capable of generating 3D-adjusted laser processing path by measuring the 3D geometry of those irregular shape objects. This paper proposed the stereo vision laser galvanometric scanning system (SLGS), which takes the advantages of both the stereo vision solution and conventional LGS system. The 3D geometry of the object obtained by the stereo cameras is used to guide the scanning galvanometers for 3D-shape-adjusted laser processing. In order to achieve precise visual-servoed laser fabrication, these two independent components are integrated through a system calibration method using plastic thin film target. The flexibility of SLGS has been experimentally demonstrated by cutting duck feathers for badminton shuttle manufacture.

  10. High-speed potato grading and quality inspection based on a color vision system

    Science.gov (United States)

    Noordam, Jacco C.; Otten, Gerwoud W.; Timmermans, Toine J. M.; van Zwol, Bauke H.

    2000-03-01

    A high-speed machine vision system for the quality inspection and grading of potatoes has been developed. The vision system grades potatoes on size, shape and external defects such as greening, mechanical damages, rhizoctonia, silver scab, common scab, cracks and growth cracks. A 3-CCD line-scan camera inspects the potatoes in flight as they pass under the camera. The use of mirrors to obtain a 360-degree view of the potato and the lack of product holders guarantee a full view of the potato. To achieve the required capacity of 12 tons/hour, 11 SHARC Digital Signal Processors perform the image processing and classification tasks. The total capacity of the system is about 50 potatoes/sec. The color segmentation procedure uses Linear Discriminant Analysis (LDA) in combination with a Mahalanobis distance classifier to classify the pixels. The procedure for the detection of misshapen potatoes uses a Fourier based shape classification technique. Features such as area, eccentricity and central moments are used to discriminate between similar colored defects. Experiments with red and yellow skin-colored potatoes have shown that the system is robust and consistent in its classification.

  11. Development of yarn breakage detection software system based on machine vision

    Science.gov (United States)

    Wang, Wenyuan; Zhou, Ping; Lin, Xiangyu

    2017-10-01

    For questions spinning mills and yarn breakage cannot be detected in a timely manner, and save the cost of textile enterprises. This paper presents a software system based on computer vision for real-time detection of yarn breakage. The system and Windows8.1 system Tablet PC, cloud server to complete the yarn breakage detection and management. Running on the Tablet PC software system is designed to collect yarn and location information for analysis and processing. And will be processed after the information through the Wi-Fi and http protocol sent to the cloud server to store in the Microsoft SQL2008 database. In order to follow up on the yarn break information query and management. Finally sent to the local display on time display, and remind the operator to deal with broken yarn. The experimental results show that the system of missed test rate not more than 5%o, and no error detection.

  12. A real-time surface inspection system for precision steel balls based on machine vision

    Science.gov (United States)

    Chen, Yi-Ji; Tsai, Jhy-Cherng; Hsu, Ya-Chen

    2016-07-01

    Precision steel balls are one of the most fundament components for motion and power transmission parts and they are widely used in industrial machinery and the automotive industry. As precision balls are crucial for the quality of these products, there is an urgent need to develop a fast and robust system for inspecting defects of precision steel balls. In this paper, a real-time system for inspecting surface defects of precision steel balls is developed based on machine vision. The developed system integrates a dual-lighting system, an unfolding mechanism and inspection algorithms for real-time signal processing and defect detection. The developed system is tested under feeding speeds of 4 pcs s-1 with a detection rate of 99.94% and an error rate of 0.10%. The minimum detectable surface flaw area is 0.01 mm2, which meets the requirement for inspecting ISO grade 100 precision steel balls.

  13. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    OpenAIRE

    Thakur, Chetan Singh; Wang, Runchun M.; Afshar, Saeed; Hamilton, Tara J.; Tapson, Jonathan C.; Shamma, Shihab A.; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation ...

  14. A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

    Science.gov (United States)

    Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

    This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

  15. Regenerative memory in time-delayed neuromorphic photonic resonators

    Science.gov (United States)

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the FitzHugh-Nagumo model with delayed feedback. This proof-of-concept photonic regenerative memory might constitute a building block for a new class of neuron-inspired photonic memories that can handle high bit-rate optical signals.

  16. Vision Lab

    Data.gov (United States)

    Federal Laboratory Consortium — The Vision Lab personnel perform research, development, testing and evaluation of eye protection and vision performance. The lab maintains and continues to develop...

  17. Real-time machine vision system using FPGA and soft-core processor

    Science.gov (United States)

    Malik, Abdul Waheed; Thörnberg, Benny; Meng, Xiaozhou; Imran, Muhammad

    2012-06-01

    This paper presents a machine vision system for real-time computation of distance and angle of a camera from reference points in the environment. Image pre-processing, component labeling and feature extraction modules were modeled at Register Transfer (RT) level and synthesized for implementation on field programmable gate arrays (FPGA). The extracted image component features were sent from the hardware modules to a soft-core processor, MicroBlaze, for computation of distance and angle. A CMOS imaging sensor operating at a clock frequency of 27MHz was used in our experiments to produce a video stream at the rate of 75 frames per second. Image component labeling and feature extraction modules were running in parallel having a total latency of 13ms. The MicroBlaze was interfaced with the component labeling and feature extraction modules through Fast Simplex Link (FSL). The latency for computing distance and angle of camera from the reference points was measured to be 2ms on the MicroBlaze, running at 100 MHz clock frequency. In this paper, we present the performance analysis, device utilization and power consumption for the designed system. The FPGA based machine vision system that we propose has high frame speed, low latency and a power consumption that is much lower compared to commercially available smart camera solutions.

  18. Multi-spectrum-based enhanced synthetic vision system for aircraft DVE operations

    Science.gov (United States)

    Kashyap, Sudesh K.; Naidu, V. P. S.; Shanthakumar, N.

    2016-04-01

    This paper focus on R&D being carried out at CSIR-NAL on Enhanced Synthetic Vision System (ESVS) for Indian regional transport aircraft to enhance all weather operational capabilities with safety and pilot Situation Awareness (SA) improvements. Flight simulator has been developed to study ESVS related technologies and to develop ESVS operational concepts for all weather approach and landing and to provide quantitative and qualitative information that could be used to develop criteria for all-weather approach and landing at regional airports in India. Enhanced Vision System (EVS) hardware prototype with long wave Infrared sensor and low light CMOS camera is used to carry out few field trials on ground vehicle at airport runway at different visibility conditions. Data acquisition and playback system has been developed to capture EVS sensor data (image) in time synch with test vehicle inertial navigation data during EVS field experiments and to playback the experimental data on ESVS flight simulator for ESVS research and concept studies. Efforts are on to conduct EVS flight experiments on CSIR-NAL research aircraft HANSA in Degraded Visual Environment (DVE).

  19. The use of contact lens telescopic systems in low vision rehabilitation.

    Science.gov (United States)

    Vincent, Stephen J

    2017-06-01

    Refracting telescopes are afocal compound optical systems consisting of two lenses that produce an apparent magnification of the retinal image. They are routinely used in visual rehabilitation in the form of monocular or binocular hand held low vision aids, and head or spectacle-mounted devices to improve distance visual acuity, and with slight modifications, to enhance acuity for near and intermediate tasks. Since the advent of ground glass haptic lenses in the 1930's, contact lenses have been employed as a useful refracting element of telescopic systems; primarily as a mobile ocular lens (the eyepiece), that moves with the eye. Telescopes which incorporate a contact lens eyepiece significantly improve the weight, comesis, and field of view compared to traditional spectacle-mounted telescopes, in addition to potential related psycho-social benefits. This review summarises the underlying optics and use of contact lenses to provide telescopic magnification from the era of Descartes, to Dallos, and the present day. The limitations and clinical challenges associated with such devices are discussed, along with the potential future use of reflecting telescopes incorporated within scleral lenses and tactile contact lens systems in low vision rehabilitation. Copyright © 2017 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

  20. The human brain on a computer, the design neuromorphic chips aims to process information as does the mind; El cerebro humano en un ordenador

    Energy Technology Data Exchange (ETDEWEB)

    Pajuelo, L.

    2015-07-01

    Develop chips that mimic the brain processes It will help create computers capable of interpreting information from image, sound and touch so that it may offer answers intelligent-not programmed before- according to these sensory data. chips neuromorphic may mimic the electrical activity neurons and brain synapses, and will be key to intelligence systems artificial (ia) that require interaction with the environment being able to extract information cognitive of what surrounds them. (Author)

  1. A novel vision-based mold monitoring system in an environment of intense vibration

    International Nuclear Information System (INIS)

    Hu, Fen; He, Zaixing; Zhao, Xinyue; Zhang, Shuyou

    2017-01-01

    Mold monitoring has been more and more widely used in the modern manufacturing industry, especially when based on machine vision, but these systems cannot meet the detection speed and accuracy requirements for mold monitoring because they must operate in environments that exhibit intense vibration during production. To ensure that the system runs accurately and efficiently, we propose a new descriptor that combines the geometric relationship-based global context feature and the local scale-invariant feature transform for the image registration step of the mold monitoring system. The experimental results of four types of molds showed that the detection accuracy of the mold monitoring system is improved in the environment with intense vibration. (paper)

  2. A novel vision-based mold monitoring system in an environment of intense vibration

    Science.gov (United States)

    Hu, Fen; He, Zaixing; Zhao, Xinyue; Zhang, Shuyou

    2017-10-01

    Mold monitoring has been more and more widely used in the modern manufacturing industry, especially when based on machine vision, but these systems cannot meet the detection speed and accuracy requirements for mold monitoring because they must operate in environments that exhibit intense vibration during production. To ensure that the system runs accurately and efficiently, we propose a new descriptor that combines the geometric relationship-based global context feature and the local scale-invariant feature transform for the image registration step of the mold monitoring system. The experimental results of four types of molds showed that the detection accuracy of the mold monitoring system is improved in the environment with intense vibration.

  3. A neuromorphic architecture for object recognition and motion anticipation using burst-STDP.

    Directory of Open Access Journals (Sweden)

    Andrew Nere

    Full Text Available In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP. STDP is responsible for the strengthening (or weakening of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

  4. Computer vision for an autonomous mobile robot

    CSIR Research Space (South Africa)

    Withey, Daniel J

    2015-10-01

    Full Text Available Computer vision systems are essential for practical, autonomous, mobile robots – machines that employ artificial intelligence and control their own motion within an environment. As with biological systems, computer vision systems include the vision...

  5. Calibration method for a vision guiding-based laser-tracking measurement system

    International Nuclear Information System (INIS)

    Shao, Mingwei; Wei, Zhenzhong; Hu, Mengjie; Zhang, Guangjun

    2015-01-01

    Laser-tracking measurement systems (laser trackers) based on a vision-guiding device are widely used in industrial fields, and their calibration is important. As conventional methods typically have many disadvantages, such as difficult machining of the target and overdependence on the retroreflector, a novel calibration method is presented in this paper. The retroreflector, which is necessary in the normal calibration method, is unnecessary in our approach. As the laser beam is linear, points on the beam can be obtained with the help of a normal planar target. In this way, we can determine the function of a laser beam under the camera coordinate system, while its corresponding function under the laser-tracker coordinate system can be obtained from the encoder of the laser tracker. Clearly, when several groups of functions are confirmed, the rotation matrix can be solved from the direction vectors of the laser beams in different coordinate systems. As the intersection of the laser beams is the origin of the laser-tracker coordinate system, the translation matrix can also be determined. Our proposed method not only achieves the calibration of a single laser-tracking measurement system but also provides a reference for the calibration of a multistation system. Simulations to evaluate the effects of some critical factors were conducted. These simulations show the robustness and accuracy of our method. In real experiments, the root mean square error of the calibration result reached 1.46 mm within a range of 10 m, even though the vision-guiding device focuses on a point approximately 5 m away from the origin of its coordinate system, with a field of view of approximately 200 mm  ×  200 mm. (paper)

  6. Commercial Flight Crew Decision-Making during Low-Visibility Approach Operations Using Fused Synthetic/Enhanced Vision Systems

    Science.gov (United States)

    Kramer, Lynda J.; Bailey, Randall E.; Prinzel, Lawrence J., III

    2007-01-01

    NASA is investigating revolutionary crew-vehicle interface technologies that strive to proactively overcome aircraft safety barriers that would otherwise constrain the full realization of the next-generation air transportation system. A fixed-based piloted simulation experiment was conducted to evaluate the complementary use of Synthetic and Enhanced Vision technologies. Specific focus was placed on new techniques for integration and/or fusion of Enhanced and Synthetic Vision and its impact within a two-crew flight deck on the crew's decision-making process during low-visibility approach and landing operations. Overall, the experimental data showed that significant improvements in situation awareness, without concomitant increases in workload and display clutter, could be provided by the integration and/or fusion of synthetic and enhanced vision technologies for the pilot-flying and the pilot-not-flying. During non-normal operations, the ability of the crew to handle substantial navigational errors and runway incursions were neither improved nor adversely impacted by the display concepts. The addition of Enhanced Vision may not, unto itself, provide an improvement in runway incursion detection without being specifically tailored for this application. Existing enhanced vision system procedures were effectively used in the crew decision-making process during approach and missed approach operations but having to forcibly transition from an excellent FLIR image to natural vision by 100 ft above field level was awkward for the pilot-flying.

  7. Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

    Energy Technology Data Exchange (ETDEWEB)

    Enqvist, Andreas; Koppal, Sanjeev [University of Florida, Gainesville, FL, 32606 (United States)

    2015-07-01

    A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for the purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and

  8. Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

    International Nuclear Information System (INIS)

    Enqvist, Andreas; Koppal, Sanjeev

    2015-01-01

    A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for the purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and

  9. Monocular Vision System for Fixed Altitude Flight of Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Kuo-Lung Huang

    2015-07-01

    Full Text Available The fastest and most economical method of acquiring terrain images is aerial photography. The use of unmanned aerial vehicles (UAVs has been investigated for this task. However, UAVs present a range of challenges such as flight altitude maintenance. This paper reports a method that combines skyline detection with a stereo vision algorithm to enable the flight altitude of UAVs to be maintained. A monocular camera is mounted on the downside of the aircraft’s nose to collect continuous ground images, and the relative altitude is obtained via a stereo vision algorithm from the velocity of the UAV. Image detection is used to obtain terrain images, and to measure the relative altitude from the ground to the UAV. The UAV flight system can be set to fly at a fixed and relatively low altitude to obtain the same resolution of ground images. A forward-looking camera is mounted on the upside of the aircraft’s nose. In combination with the skyline detection algorithm, this helps the aircraft to maintain a stable flight pattern. Experimental results show that the proposed system enables UAVs to obtain terrain images at constant resolution, and to detect the relative altitude along the flight path.

  10. A vision-based system for intelligent monitoring: human behaviour analysis and privacy by context.

    Science.gov (United States)

    Chaaraoui, Alexandros Andre; Padilla-López, José Ramón; Ferrández-Pastor, Francisco Javier; Nieto-Hidalgo, Mario; Flórez-Revuelta, Francisco

    2014-05-20

    Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people's behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services.

  11. Inverse Modeling of Human Knee Joint Based on Geometry and Vision Systems for Exoskeleton Applications

    Directory of Open Access Journals (Sweden)

    Eduardo Piña-Martínez

    2015-01-01

    Full Text Available Current trends in Robotics aim to close the gap that separates technology and humans, bringing novel robotic devices in order to improve human performance. Although robotic exoskeletons represent a breakthrough in mobility enhancement, there are design challenges related to the forces exerted to the users’ joints that result in severe injuries. This occurs due to the fact that most of the current developments consider the joints as noninvariant rotational axes. This paper proposes the use of commercial vision systems in order to perform biomimetic joint design for robotic exoskeletons. This work proposes a kinematic model based on irregular shaped cams as the joint mechanism that emulates the bone-to-bone joints in the human body. The paper follows a geometric approach for determining the location of the instantaneous center of rotation in order to design the cam contours. Furthermore, the use of a commercial vision system is proposed as the main measurement tool due to its noninvasive feature and for allowing subjects under measurement to move freely. The application of this method resulted in relevant information about the displacements of the instantaneous center of rotation at the human knee joint.

  12. Cost-Effective Video Filtering Solution for Real-Time Vision Systems

    Directory of Open Access Journals (Sweden)

    Karl Martin

    2005-08-01

    Full Text Available This paper presents an efficient video filtering scheme and its implementation in a field-programmable logic device (FPLD. Since the proposed nonlinear, spatiotemporal filtering scheme is based on order statistics, its efficient implementation benefits from a bit-serial realization. The utilization of both the spatial and temporal correlation characteristics of the processed video significantly increases the computational demands on this solution, and thus, implementation becomes a significant challenge. Simulation studies reported in this paper indicate that the proposed pipelined bit-serial FPLD filtering solution can achieve speeds of up to 97.6 Mpixels/s and consumes 1700 to 2700 logic cells for the speed-optimized and area-optimized versions, respectively. Thus, the filter area represents only 6.6 to 10.5% of the Altera STRATIX EP1S25 device available on the Altera Stratix DSP evaluation board, which has been used to implement a prototype of the entire real-time vision system. As such, the proposed adaptive video filtering scheme is both practical and attractive for real-time machine vision and surveillance systems as well as conventional video and multimedia applications.

  13. A Vision-Based System for Intelligent Monitoring: Human Behaviour Analysis and Privacy by Context

    Directory of Open Access Journals (Sweden)

    Alexandros Andre Chaaraoui

    2014-05-01

    Full Text Available Due to progress and demographic change, society is facing a crucial challenge related to increased life expectancy and a higher number of people in situations of dependency. As a consequence, there exists a significant demand for support systems for personal autonomy. This article outlines the vision@home project, whose goal is to extend independent living at home for elderly and impaired people, providing care and safety services by means of vision-based monitoring. Different kinds of ambient-assisted living services are supported, from the detection of home accidents, to telecare services. In this contribution, the specification of the system is presented, and novel contributions are made regarding human behaviour analysis and privacy protection. By means of a multi-view setup of cameras, people’s behaviour is recognised based on human action recognition. For this purpose, a weighted feature fusion scheme is proposed to learn from multiple views. In order to protect the right to privacy of the inhabitants when a remote connection occurs, a privacy-by-context method is proposed. The experimental results of the behaviour recognition method show an outstanding performance, as well as support for multi-view scenarios and real-time execution, which are required in order to provide the proposed services.

  14. Optimization of spatial light distribution through genetic algorithms for vision systems applied to quality control

    International Nuclear Information System (INIS)

    Castellini, P; Cecchini, S; Stroppa, L; Paone, N

    2015-01-01

    The paper presents an adaptive illumination system for image quality enhancement in vision-based quality control systems. In particular, a spatial modulation of illumination intensity is proposed in order to improve image quality, thus compensating for different target scattering properties, local reflections and fluctuations of ambient light. The desired spatial modulation of illumination is obtained by a digital light projector, used to illuminate the scene with an arbitrary spatial distribution of light intensity, designed to improve feature extraction in the region of interest. The spatial distribution of illumination is optimized by running a genetic algorithm. An image quality estimator is used to close the feedback loop and to stop iterations once the desired image quality is reached. The technique proves particularly valuable for optimizing the spatial illumination distribution in the region of interest, with the remarkable capability of the genetic algorithm to adapt the light distribution to very different target reflectivity and ambient conditions. The final objective of the proposed technique is the improvement of the matching score in the recognition of parts through matching algorithms, hence of the diagnosis of machine vision-based quality inspections. The procedure has been validated both by a numerical model and by an experimental test, referring to a significant problem of quality control for the washing machine manufacturing industry: the recognition of a metallic clamp. Its applicability to other domains is also presented, specifically for the visual inspection of shoes with retro-reflective tape and T-shirts with paillettes. (paper)

  15. Rapid, computer vision-enabled murine screening system identifies neuropharmacological potential of two new mechanisms

    Directory of Open Access Journals (Sweden)

    Steven L Roberds

    2011-09-01

    Full Text Available The lack of predictive in vitro models for behavioral phenotypes impedes rapid advancement in neuropharmacology and psychopharmacology. In vivo behavioral assays are more predictive of activity in human disorders, but such assays are often highly resource-intensive. Here we describe the successful application of a computer vision-enabled system to identify potential neuropharmacological activity of two new mechanisms. The analytical system was trained using multiple drugs that are used clinically to treat depression, schizophrenia, anxiety, and other psychiatric or behavioral disorders. During blinded testing the PDE10 inhibitor TP-10 produced a signature of activity suggesting potential antipsychotic activity. This finding is consistent with TP-10’s activity in multiple rodent models that is similar to that of clinically used antipsychotic drugs. The CK1ε inhibitor PF-670462 produced a signature consistent with anxiolytic activity and, at the highest dose tested, behavioral effects similar to that of opiate analgesics. Neither TP-10 nor PF-670462 was included in the training set. Thus, computer vision-based behavioral analysis can facilitate drug discovery by identifying neuropharmacological effects of compounds acting through new mechanisms.

  16. Cognitive vision system for control of dexterous prosthetic hands: Experimental evaluation

    Directory of Open Access Journals (Sweden)

    Došen Strahinja

    2010-08-01

    Full Text Available Abstract Background Dexterous prosthetic hands that were developed recently, such as SmartHand and i-LIMB, are highly sophisticated; they have individually controllable fingers and the thumb that is able to abduct/adduct. This flexibility allows implementation of many different grasping strategies, but also requires new control algorithms that can exploit the many degrees of freedom available. The current study presents and tests the operation of a new control method for dexterous prosthetic hands. Methods The central component of the proposed method is an autonomous controller comprising a vision system with rule-based reasoning mounted on a dexterous hand (CyberHand. The controller, termed cognitive vision system (CVS, mimics biological control and generates commands for prehension. The CVS was integrated into a hierarchical control structure: 1 the user triggers the system and controls the orientation of the hand; 2 a high-level controller automatically selects the grasp type and size; and 3 an embedded hand controller implements the selected grasp using closed-loop position/force control. The operation of the control system was tested in 13 healthy subjects who used Cyberhand, attached to the forearm, to grasp and transport 18 objects placed at two different distances. Results The system correctly estimated grasp type and size (nine commands in total in about 84% of the trials. In an additional 6% of the trials, the grasp type and/or size were different from the optimal ones, but they were still good enough for the grasp to be successful. If the control task was simplified by decreasing the number of possible commands, the classification accuracy increased (e.g., 93% for guessing the grasp type only. Conclusions The original outcome of this research is a novel controller empowered by vision and reasoning and capable of high-level analysis (i.e., determining object properties and autonomous decision making (i.e., selecting the grasp type and

  17. Optoelectronic vision

    Science.gov (United States)

    Ren, Chunye; Parel, Jean-Marie A.

    1993-06-01

    Scientists have searched every discipline to find effective methods of treating blindness, such as using aids based on conversion of the optical image, to auditory or tactile stimuli. However, the limited performance of such equipment and difficulties in training patients have seriously hampered practical applications. A great edification has been given by the discovery of Foerster (1929) and Krause & Schum (1931), who found that the electrical stimulation of the visual cortex evokes the perception of a small spot of light called `phosphene' in both blind and sighted subjects. According to this principle, it is possible to invite artificial vision by using stimulation with electrodes placed on the vision neural system, thereby developing a prosthesis for the blind that might be of value in reading and mobility. In fact, a number of investigators have already exploited this phenomena to produce a functional visual prosthesis, bringing about great advances in this area.

  18. Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields.

    Science.gov (United States)

    Cunha, B C N; Belk, K E; Scanga, J A; LeValley, S B; Tatum, J D; Smith, G C

    2004-07-01

    This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value

  19. A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

    Science.gov (United States)

    Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

    2012-01-01

    This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

  20. Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

    Science.gov (United States)

    You, Hongzhi; Wang, Da-Hui

    2017-01-01

    Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

  1. Machine vision system: a tool for quality inspection of food and agricultural products.

    Science.gov (United States)

    Patel, Krishna Kumar; Kar, A; Jha, S N; Khan, M A

    2012-04-01

    Quality inspection of food and agricultural produce are difficult and labor intensive. Simultaneously, with increased expectations for food products of high quality and safety standards, the need for accurate, fast and objective quality determination of these characteristics in food products continues to grow. However, these operations generally in India are manual which is costly as well as unreliable because human decision in identifying quality factors such as appearance, flavor, nutrient, texture, etc., is inconsistent, subjective and slow. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. This inspection approach based on image analysis and processing has found a variety of different applications in the food industry. Considerable research has highlighted its potential for the inspection and grading of fruits and vegetables, grain quality and characteristic examination and quality evaluation of other food products like bakery products, pizza, cheese, and noodles etc. The objective of this paper is to provide in depth introduction of machine vision system, its components and recent work reported on food and agricultural produce.

  2. Vision-based measuring system for rider's pose estimation during motorcycle riding

    Science.gov (United States)

    Cheli, F.; Mazzoleni, P.; Pezzola, M.; Ruspini, E.; Zappa, E.

    2013-07-01

    Inertial characteristics of the human body are comparable with the vehicle ones in motorbike riding: the study of a rider's dynamic is a crucial step in system modeling. An innovative vision based system able to measure the six degrees of freedom of the driver with respect to the vehicle is proposed here: the core of the proposed approach is an image acquisition and processing technique capable of reconstructing the position and orientation of a target fixed on the rider's back. The technique is firstly validated in laboratory tests comparing measured and imposed target motion laws and successively tested in a real case scenario during track tests with amateur and professional drivers. The presented results show the capability of the technique to correctly describe the driver's dynamic, his interaction with the vehicle as well as the possibility to use the new measuring technique in the comparison of different driving styles.

  3. Focal-plane change triggered video compression for low-power vision sensor systems.

    Directory of Open Access Journals (Sweden)

    Yu M Chi

    Full Text Available Video sensors with embedded compression offer significant energy savings in transmission but incur energy losses in the complexity of the encoder. Energy efficient video compression architectures for CMOS image sensors with focal-plane change detection are presented and analyzed. The compression architectures use pixel-level computational circuits to minimize energy usage by selectively processing only pixels which generate significant temporal intensity changes. Using the temporal intensity change detection to gate the operation of a differential DCT based encoder achieves nearly identical image quality to traditional systems (4dB decrease in PSNR while reducing the amount of data that is processed by 67% and reducing overall power consumption reduction of 51%. These typical energy savings, resulting from the sparsity of motion activity in the visual scene, demonstrate the utility of focal-plane change triggered compression to surveillance vision systems.

  4. Simulation of Specular Surface Imaging Based on Computer Graphics: Application on a Vision Inspection System

    Directory of Open Access Journals (Sweden)

    Seulin Ralph

    2002-01-01

    Full Text Available This work aims at detecting surface defects on reflecting industrial parts. A machine vision system, performing the detection of geometric aspect surface defects, is completely described. The revealing of defects is realized by a particular lighting device. It has been carefully designed to ensure the imaging of defects. The lighting system simplifies a lot the image processing for defect segmentation and so a real-time inspection of reflective products is possible. To bring help in the conception of imaging conditions, a complete simulation is proposed. The simulation, based on computer graphics, enables the rendering of realistic images. Simulation provides here a very efficient way to perform tests compared to the numerous attempts of manual experiments.

  5. 3D gaze tracking system for NVidia 3D Vision®.

    Science.gov (United States)

    Wibirama, Sunu; Hamamoto, Kazuhiko

    2013-01-01

    Inappropriate parallax setting in stereoscopic content generally causes visual fatigue and visual discomfort. To optimize three dimensional (3D) effects in stereoscopic content by taking into account health issue, understanding how user gazes at 3D direction in virtual space is currently an important research topic. In this paper, we report the study of developing a novel 3D gaze tracking system for Nvidia 3D Vision(®) to be used in desktop stereoscopic display. We suggest an optimized geometric method to accurately measure the position of virtual 3D object. Our experimental result shows that the proposed system achieved better accuracy compared to conventional geometric method by average errors 0.83 cm, 0.87 cm, and 1.06 cm in X, Y, and Z dimensions, respectively.

  6. Synthetic Vision System Commercial Aircraft Flight Deck Display Technologies for Unusual Attitude Recovery

    Science.gov (United States)

    Prinzel, Lawrence J., III; Ellis, Kyle E.; Arthur, Jarvis J.; Nicholas, Stephanie N.; Kiggins, Daniel

    2017-01-01

    A Commercial Aviation Safety Team (CAST) study of 18 worldwide loss-of-control accidents and incidents determined that the lack of external visual references was associated with a flight crew's loss of attitude awareness or energy state awareness in 17 of these events. Therefore, CAST recommended development and implementation of virtual day-Visual Meteorological Condition (VMC) display systems, such as synthetic vision systems, which can promote flight crew attitude awareness similar to a day-VMC environment. This paper describes the results of a high-fidelity, large transport aircraft simulation experiment that evaluated virtual day-VMC displays and a "background attitude indicator" concept as an aid to pilots in recovery from unusual attitudes. Twelve commercial airline pilots performed multiple unusual attitude recoveries and both quantitative and qualitative dependent measures were collected. Experimental results and future research directions under this CAST initiative and the NASA "Technologies for Airplane State Awareness" research project are described.

  7. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton, MA (United States)

    2017-01-06

    The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.

  8. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, C. Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Liu, Jialin [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton MA (United States)

    2017-01-07

    The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

  9. Sensor fusion to enable next generation low cost Night Vision systems

    Science.gov (United States)

    Schweiger, R.; Franz, S.; Löhlein, O.; Ritter, W.; Källhammer, J.-E.; Franks, J.; Krekels, T.

    2010-04-01

    The next generation of automotive Night Vision Enhancement systems offers automatic pedestrian recognition with a performance beyond current Night Vision systems at a lower cost. This will allow high market penetration, covering the luxury as well as compact car segments. Improved performance can be achieved by fusing a Far Infrared (FIR) sensor with a Near Infrared (NIR) sensor. However, fusing with today's FIR systems will be too costly to get a high market penetration. The main cost drivers of the FIR system are its resolution and its sensitivity. Sensor cost is largely determined by sensor die size. Fewer and smaller pixels will reduce die size but also resolution and sensitivity. Sensitivity limits are mainly determined by inclement weather performance. Sensitivity requirements should be matched to the possibilities of low cost FIR optics, especially implications of molding of highly complex optical surfaces. As a FIR sensor specified for fusion can have lower resolution as well as lower sensitivity, fusing FIR and NIR can solve performance and cost problems. To allow compensation of FIR-sensor degradation on the pedestrian detection capabilities, a fusion approach called MultiSensorBoosting is presented that produces a classifier holding highly discriminative sub-pixel features from both sensors at once. The algorithm is applied on data with different resolution and on data obtained from cameras with varying optics to incorporate various sensor sensitivities. As it is not feasible to record representative data with all different sensor configurations, transformation routines on existing high resolution data recorded with high sensitivity cameras are investigated in order to determine the effects of lower resolution and lower sensitivity to the overall detection performance. This paper also gives an overview of the first results showing that a reduction of FIR sensor resolution can be compensated using fusion techniques and a reduction of sensitivity can be

  10. Automated egg grading system using computer vision: Investigation on weight measure versus shape parameters

    Science.gov (United States)

    Nasir, Ahmad Fakhri Ab; Suhaila Sabarudin, Siti; Majeed, Anwar P. P. Abdul; Ghani, Ahmad Shahrizan Abdul

    2018-04-01

    Chicken egg is a source of food of high demand by humans. Human operators cannot work perfectly and continuously when conducting egg grading. Instead of an egg grading system using weight measure, an automatic system for egg grading using computer vision (using egg shape parameter) can be used to improve the productivity of egg grading. However, early hypothesis has indicated that more number of egg classes will change when using egg shape parameter compared with using weight measure. This paper presents the comparison of egg classification by the two above-mentioned methods. Firstly, 120 images of chicken eggs of various grades (A–D) produced in Malaysia are captured. Then, the egg images are processed using image pre-processing techniques, such as image cropping, smoothing and segmentation. Thereafter, eight egg shape features, including area, major axis length, minor axis length, volume, diameter and perimeter, are extracted. Lastly, feature selection (information gain ratio) and feature extraction (principal component analysis) are performed using k-nearest neighbour classifier in the classification process. Two methods, namely, supervised learning (using weight measure as graded by egg supplier) and unsupervised learning (using egg shape parameters as graded by ourselves), are conducted to execute the experiment. Clustering results reveal many changes in egg classes after performing shape-based grading. On average, the best recognition results using shape-based grading label is 94.16% while using weight-based label is 44.17%. As conclusion, automated egg grading system using computer vision is better by implementing shape-based features since it uses image meanwhile the weight parameter is more suitable by using weight grading system.

  11. Virtual Vision

    Science.gov (United States)

    Terzopoulos, Demetri; Qureshi, Faisal Z.

    Computer vision and sensor networks researchers are increasingly motivated to investigate complex multi-camera sensing and control issues that arise in the automatic visual surveillance of extensive, highly populated public spaces such as airports and train stations. However, they often encounter serious impediments to deploying and experimenting with large-scale physical camera networks in such real-world environments. We propose an alternative approach called "Virtual Vision", which facilitates this type of research through the virtual reality simulation of populated urban spaces, camera sensor networks, and computer vision on commodity computers. We demonstrate the usefulness of our approach by developing two highly automated surveillance systems comprising passive and active pan/tilt/zoom cameras that are deployed in a virtual train station environment populated by autonomous, lifelike virtual pedestrians. The easily reconfigurable virtual cameras distributed in this environment generate synthetic video feeds that emulate those acquired by real surveillance cameras monitoring public spaces. The novel multi-camera control strategies that we describe enable the cameras to collaborate in persistently observing pedestrians of interest and in acquiring close-up videos of pedestrians in designated areas.

  12. The role of vision processing in prosthetic vision.

    Science.gov (United States)

    Barnes, Nick; He, Xuming; McCarthy, Chris; Horne, Lachlan; Kim, Junae; Scott, Adele; Lieby, Paulette

    2012-01-01

    Prosthetic vision provides vision which is reduced in resolution and dynamic range compared to normal human vision. This comes about both due to residual damage to the visual system from the condition that caused vision loss, and due to limitations of current technology. However, even with limitations, prosthetic vision may still be able to support functional performance which is sufficient for tasks which are key to restoring independent living and quality of life. Here vision processing can play a key role, ensuring that information which is critical to the performance of key tasks is available within the capability of the available prosthetic vision. In this paper, we frame vision processing for prosthetic vision, highlight some key areas which present problems in terms of quality of life, and present examples where vision processing can help achieve better outcomes.

  13. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    Science.gov (United States)

    2007-03-31

    IFinal 03/01/04 - 02/28/07 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Neuromorphic VLSI-based Bat Echolocation for Micro-aerial 5b.GRANTNUMBER Vehicle...uncovered interesting new issues in our choice for representing the intensity of signals. We have just finished testing the first chip version of an echo...timing-based algorithm (’openspace’) for sonar-guided navigation amidst multiple obstacles. 15. SUBJECT TERMS Neuromorphic VLSI, bat echolocation

  14. Serendipitous offline learning in a neuromorphic robot

    CSIR Research Space (South Africa)

    Stewart, TC

    2016-02-01

    Full Text Available ) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior....

  15. Vision based interface system for hands free control of an intelligent wheelchair

    Directory of Open Access Journals (Sweden)

    Kim Eun

    2009-08-01

    Full Text Available Abstract Background Due to the shift of the age structure in today's populations, the necessities for developing the devices or technologies to support them have been increasing. Traditionally, the wheelchair, including powered and manual ones, is the most popular and important rehabilitation/assistive device for the disabled and the elderly. However, it is still highly restricted especially for severely disabled. As a solution to this, the Intelligent Wheelchairs (IWs have received considerable attention as mobility aids. The purpose of this work is to develop the IW interface for providing more convenient and efficient interface to the people the disability in their limbs. Methods This paper proposes an intelligent wheelchair (IW control system for the people with various disabilities. To facilitate a wide variety of user abilities, the proposed system involves the use of face-inclination and mouth-shape information, where the direction of an IW is determined by the inclination of the user's face, while proceeding and stopping are determined by the shapes of the user's mouth. Our system is composed of electric powered wheelchair, data acquisition board, ultrasonic/infra-red sensors, a PC camera, and vision system. Then the vision system to analyze user's gestures is performed by three stages: detector, recognizer, and converter. In the detector, the facial region of the intended user is first obtained using Adaboost, thereafter the mouth region is detected based on edge information. The extracted features are sent to the recognizer, which recognizes the face inclination and mouth shape using statistical analysis and K-means clustering, respectively. These recognition results are then delivered to the converter to control the wheelchair. Result & conclusion The advantages of the proposed system include 1 accurate recognition of user's intention with minimal user motion and 2 robustness to a cluttered background and the time-varying illumination

  16. Long-Term Instrumentation, Information, and Control Systems (II&C) Modernization Future Vision and Strategy

    Energy Technology Data Exchange (ETDEWEB)

    Kenneth Thomas; Bruce Hallbert

    2013-02-01

    Life extension beyond 60 years for the U.S operating nuclear fleet requires that instrumentation and control (I&C) systems be upgraded to address aging and reliability concerns. It is impractical for the legacy systems based on 1970’s vintage technology operate over this extended time period. Indeed, utilities have successfully engaged in such replacements when dictated by these operational concerns. However, the replacements have been approached in a like-for-like manner, meaning that they do not take advantage of the inherent capabilities of digital technology to improve business functions. And so, the improvement in I&C system performance has not translated to bottom-line performance improvement for the fleet. Therefore, wide-scale modernization of the legacy I&C systems could prove to be cost-prohibitive unless the technology is implemented in a manner to enable significant business innovation as a means of off-setting the cost of upgrades. A Future Vision of a transformed nuclear plant operating model based on an integrated digital environment has been developed as part of the Advanced Instrumentation, Information, and Control (II&C) research pathway, under the Light Water Reactor (LWR) Sustainability Program. This is a research and development program sponsored by the U.S. Department of Energy (DOE), performed in close collaboration with the nuclear utility industry, to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. DOE’s program focus is on longer-term and higher-risk/reward research that contributes to the national policy objectives of energy security and environmental security . The Advanced II&C research pathway is being conducted by the Idaho National Laboratory (INL). The Future Vision is based on a digital architecture that encompasses all aspects of plant operations and support, integrating plant systems, plant work processes, and plant workers in a

  17. Long-Term Instrumentation, Information, and Control Systems (II&C) Modernization Future Vision and Strategy

    Energy Technology Data Exchange (ETDEWEB)

    Kenneth Thomas

    2012-02-01

    Life extension beyond 60 years for the U.S operating nuclear fleet requires that instrumentation and control (I&C) systems be upgraded to address aging and reliability concerns. It is impractical for the legacy systems based on 1970's vintage technology operate over this extended time period. Indeed, utilities have successfully engaged in such replacements when dictated by these operational concerns. However, the replacements have been approached in a like-for-like manner, meaning that they do not take advantage of the inherent capabilities of digital technology to improve business functions. And so, the improvement in I&C system performance has not translated to bottom-line performance improvement for the fleet. Therefore, wide-scale modernization of the legacy I&C systems could prove to be cost-prohibitive unless the technology is implemented in a manner to enable significant business innovation as a means of off-setting the cost of upgrades. A Future Vision of a transformed nuclear plant operating model based on an integrated digital environment has been developed as part of the Advanced Instrumentation, Information, and Control (II&C) research pathway, under the Light Water Reactor (LWR) Sustainability Program. This is a research and development program sponsored by the U.S. Department of Energy (DOE), performed in close collaboration with the nuclear utility industry, to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. DOE's program focus is on longer-term and higher-risk/reward research that contributes to the national policy objectives of energy security and environmental security . The Advanced II&C research pathway is being conducted by the Idaho National Laboratory (INL). The Future Vision is based on a digital architecture that encompasses all aspects of plant operations and support, integrating plant systems, plant work processes, and plant workers in a

  18. Long-Term Instrumentation, Information, and Control Systems (II and C) Modernization Future Vision and Strategy

    International Nuclear Information System (INIS)

    Thomas, Kenneth

    2012-01-01

    Life extension beyond 60 years for the U.S operating nuclear fleet requires that instrumentation and control (I and C) systems be upgraded to address aging and reliability concerns. It is impractical for the legacy systems based on 1970's vintage technology operate over this extended time period. Indeed, utilities have successfully engaged in such replacements when dictated by these operational concerns. However, the replacements have been approached in a like-for-like manner, meaning that they do not take advantage of the inherent capabilities of digital technology to improve business functions. And so, the improvement in I and C system performance has not translated to bottom-line performance improvement for the fleet. Therefore, wide-scale modernization of the legacy I and C systems could prove to be cost-prohibitive unless the technology is implemented in a manner to enable significant business innovation as a means of off-setting the cost of upgrades. A Future Vision of a transformed nuclear plant operating model based on an integrated digital environment has been developed as part of the Advanced Instrumentation, Information, and Control (II and C) research pathway, under the Light Water Reactor (LWR) Sustainability Program. This is a research and development program sponsored by the U.S. Department of Energy (DOE), performed in close collaboration with the nuclear utility industry, to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants. DOE's program focus is on longer-term and higher-risk/reward research that contributes to the national policy objectives of energy security and environmental security . The Advanced II and C research pathway is being conducted by the Idaho National Laboratory (INL). The Future Vision is based on a digital architecture that encompasses all aspects of plant operations and support, integrating plant systems, plant work processes, and plant

  19. Estimation of 3D reconstruction errors in a stereo-vision system

    Science.gov (United States)

    Belhaoua, A.; Kohler, S.; Hirsch, E.

    2009-06-01

    The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.

  20. Background staining of visualization systems in immunohistochemistry: comparison of the Avidin-Biotin Complex system and the EnVision+ system.

    Science.gov (United States)

    Vosse, Bettine A H; Seelentag, Walter; Bachmann, Astrid; Bosman, Fred T; Yan, Pu

    2007-03-01

    The aim of this study was to evaluate specific immunostaining and background staining in formalin-fixed, paraffin-embedded human tissues with the 2 most frequently used immunohistochemical detection systems, Avidin-Biotin-Peroxidase (ABC) and EnVision+. A series of fixed tissues, including breast, colon, kidney, larynx, liver, lung, ovary, pancreas, prostate, stomach, and tonsil, was used in the study. Three monoclonal antibodies, 1 against a nuclear antigen (Ki-67), 1 against a cytoplasmic antigen (cytokeratin), and 1 against a cytoplasmic and membrane-associated antigen and a polyclonal antibody against a nuclear and cytoplasmic antigen (S-100) were selected for these studies. When the ABC system was applied, immunostaining was performed with and without blocking of endogenous avidin-binding activity. The intensity of specific immunostaining and the percentage of stained cells were comparable for the 2 detection systems. The use of ABC caused widespread cytoplasmic and rare nuclear background staining in a variety of normal and tumor cells. A very strong background staining was observed in colon, gastric mucosa, liver, and kidney. Blocking avidin-binding capacity reduced background staining, but complete blocking was difficult to attain. With the EnVision+ system no background staining occurred. Given the efficiency of the detection, equal for both systems or higher with EnVision+, and the significant background problem with ABC, we advocate the routine use of the EnVision+ system.

  1. Star tracker and vision systems performance in a high radiation environment

    DEFF Research Database (Denmark)

    Jørgensen, John Leif; Riis, Troels; Betto, Maurizio

    1999-01-01

    A part of the payload of the second Ariane 5 prototype vehicle to be launched by Arianespace, was a small technology demonstration satellite. On October 30th, 1997, this test satellite, dubbed Teamsat, was launched into Geostationary Transfer Orbit and would as such pass the Van Allen radiation...... belts twice per orbit. One of the experiments onboard Teamsat was the so-called Autonomous Vision System (AVS). The AVS instrument is a fully autonomous star tracker with several advanced features for non-stellar object detection and tracking, real-time image compression and transmission. The objectives...... for the AVS in Teamsat were to test these functions, to validate their autonomous operation in space, and to assess the operational constraints of a high radiation environment on such processes. This paper describes the AVS experiment, and the radiation flux experienced onboard TEAMSAT. This overview...

  2. Transition of Attention in Terminal Area NextGen Operations Using Synthetic Vision Systems

    Science.gov (United States)

    Ellis, Kyle K. E.; Kramer, Lynda J.; Shelton, Kevin J.; Arthur, Shelton, J. J., III; Prinzel, Lance J., III; Norman, Robert M.

    2011-01-01

    This experiment investigates the capability of Synthetic Vision Systems (SVS) to provide significant situation awareness in terminal area operations, specifically in low visibility conditions. The use of a Head-Up Display (HUD) and Head-Down Displays (HDD) with SVS is contrasted to baseline standard head down displays in terms of induced workload and pilot behavior in 1400 RVR visibility levels. Variances across performance and pilot behavior were reviewed for acceptability when using HUD or HDD with SVS under reduced minimums to acquire the necessary visual components to continue to land. The data suggest superior performance for HUD implementations. Improved attentional behavior is also suggested for HDD implementations of SVS for low-visibility approach and landing operations.

  3. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2016-01-01

    Full Text Available This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour.

  4. Development of a teaching system for an industrial robot using stereo vision

    Science.gov (United States)

    Ikezawa, Kazuya; Konishi, Yasuo; Ishigaki, Hiroyuki

    1997-12-01

    The teaching and playback method is mainly a teaching technique for industrial robots. However, this technique takes time and effort in order to teach. In this study, a new teaching algorithm using stereo vision based on human demonstrations in front of two cameras is proposed. In the proposed teaching algorithm, a robot is controlled repetitively according to angles determined by the fuzzy sets theory until it reaches an instructed teaching point, which is relayed through cameras by an operator. The angles are recorded and used later in playback. The major advantage of this algorithm is that no calibrations are needed. This is because the fuzzy sets theory, which is able to express qualitatively the control commands to the robot, is used instead of conventional kinematic equations. Thus, a simple and easy teaching operation is realized with this teaching algorithm. Simulations and experiments have been performed on the proposed teaching system, and data from testing has confirmed the usefulness of our design.

  5. Road following for blindBike: an assistive bike navigation system for low vision persons

    Science.gov (United States)

    Grewe, Lynne; Overell, William

    2017-05-01

    Road Following is a critical component of blindBike, our assistive biking application for the visually impaired. This paper talks about the overall blindBike system and goals prominently featuring Road Following, which is the task of directing the user to follow the right side of the road. This work unlike what is commonly found for self-driving cars does not depend on lane line markings. 2D computer vision techniques are explored to solve the problem of Road Following. Statistical techniques including the use of Gaussian Mixture Models are employed. blindBike is developed as an Android Application and is running on a smartphone device. Other sensors including Gyroscope and GPS are utilized. Both Urban and suburban scenarios are tested and results are given. The success and challenges faced by blindBike's Road Following module are presented along with future avenues of work.

  6. A survey of autonomous vision-based See and Avoid for Unmanned Aircraft Systems

    Science.gov (United States)

    Mcfadyen, Aaron; Mejias, Luis

    2016-01-01

    This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

  7. Road Interpretation for Driver Assistance Based on an Early Cognitive Vision System

    DEFF Research Database (Denmark)

    Baseski, Emre; Jensen, Lars Baunegaard With; Pugeault, Nicolas

    2009-01-01

    In this work, we address the problem of road interpretation for driver assistance based on an early cognitive vision system. The structure of a road and the relevant traffic are interpreted in terms of ego-motion estimation of the car, independently moving objects on the road, lane markers and large...... scale maps of the road. We make use of temporal and spatial disambiguation mechanisms to increase the reliability of visually extracted 2D and 3D information. This information is then used to interpret the layout of the road by using lane markers that are detected via Bayesian reasoning. We also...... estimate the ego-motion of the car which is used to create large scale maps of the road and also to detect independently moving objects. Sample results for the presented algorithms are shown on a stereo image sequence, that has been collected from a structured road....

  8. A Customized Vision System for Tracking Humans Wearing Reflective Safety Clothing from Industrial Vehicles and Machinery

    Science.gov (United States)

    Mosberger, Rafael; Andreasson, Henrik; Lilienthal, Achim J.

    2014-01-01

    This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions. PMID:25264956

  9. Motorcycle That See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles

    Directory of Open Access Journals (Sweden)

    Gustavo Gil

    2018-01-01

    Full Text Available Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations. This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed. Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles. We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles. Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor. Our promising results support the application of this type of sensors for advanced motorcycle safety applications.

  10. Motorcycles that See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles

    Science.gov (United States)

    2018-01-01

    Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations. This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed. Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles. We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles. Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor. Our promising results support the application of this type of sensors for advanced motorcycle safety applications. PMID:29351267

  11. Motorcycle That See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles.

    Science.gov (United States)

    Gil, Gustavo; Savino, Giovanni; Piantini, Simone; Pierini, Marco

    2018-01-19

    Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations. This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed. Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles. We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles. Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor. Our promising results support the application of this type of sensors for advanced motorcycle safety applications.

  12. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Science.gov (United States)

    2016-01-01

    This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

  13. In-vehicle stereo vision system for identification of traffic conflicts between bus and pedestrian

    Directory of Open Access Journals (Sweden)

    Salvatore Cafiso

    2017-02-01

    Full Text Available The traffic conflict technique (TCT was developed as “surrogate measure of road safety” to identify near-crash events by using measures of the spatial and temporal proximity of road users. Traditionally applications of TCT focus on a specific site by the way of manually or automated supervision. Nowadays the development of in-vehicle (IV technologies provides new opportunities for monitoring driver behavior and interaction with other road users directly into the traffic stream. In the paper a stereo vision and GPS system for traffic conflict investigation is presented for detecting conflicts between vehicle and pedestrian. The system is able to acquire geo-referenced sequences of stereo frames that are used to provide real time information related to conflict occurrence and severity. As case study, an urban bus was equipped with a prototype of the system and a trial in the city of Catania (Italy was carried out analyzing conflicts with pedestrian crossing in front of the bus. Experimental results pointed out the potentialities of the system for collection of data that can be used to get suitable traffic conflict measures. Specifically, a risk index of the conflict between pedestrians and vehicles is proposed to classify collision probability and severity using data collected by the system. This information may be used to develop in-vehicle warning systems and urban network risk assessment.

  14. Noise-driven neuromorphic tuned amplifier

    Science.gov (United States)

    Fanelli, Duccio; Ginelli, Francesco; Livi, Roberto; Zagli, Niccoló; Zankoc, Clement

    2017-12-01

    We study a simple stochastic model of neuronal excitatory and inhibitory interactions. The model is defined on a directed lattice and internodes couplings are modulated by a nonlinear function that mimics the process of synaptic activation. We prove that such a system behaves as a fully tunable amplifier: the endogenous component of noise, stemming from finite size effects, seeds a coherent (exponential) amplification across the chain generating giant oscillations with tunable frequencies, a process that the brain could exploit to enhance, and eventually encode, different signals. On a wider perspective, the characterized amplification process could provide a reliable pacemaking mechanism for biological systems. The device extracts energy from the finite size bath and operates as an out of equilibrium thermal machine, under stationary conditions.

  15. Development of a vision-based pH reading system

    Science.gov (United States)

    Hur, Min Goo; Kong, Young Bae; Lee, Eun Je; Park, Jeong Hoon; Yang, Seung Dae; Moon, Ha Jung; Lee, Dong Hoon

    2015-10-01

    pH paper is generally used for pH interpretation in the QC (quality control) process of radiopharmaceuticals. pH paper is easy to handle and useful for small samples such as radio-isotopes and radioisotope (RI)-labeled compounds for positron emission tomography (PET). However, pHpaper-based detecting methods may have some errors due limitations of eye sight and inaccurate readings. In this paper, we report a new device for pH reading and related software. The proposed pH reading system is developed with a vision algorithm based on the RGB library. The pH reading system is divided into two parts. First is the reading device that consists of a light source, a CCD camera and a data acquisition (DAQ) board. To improve the accuracy of the sensitivity, we utilize the three primary colors of the LED (light emission diode) in the reading device. The use of three colors is better than the use of a single color for a white LED because of wavelength. The other is a graph user interface (GUI) program for a vision interface and report generation. The GUI program inserts the color codes of the pH paper into the database; then, the CCD camera captures the pH paper and compares its color with the RGB database image in the reading mode. The software captures and reports information on the samples, such as pH results, capture images, and library images, and saves them as excel files.

  16. Automatic vision system for analysis of microscopic behavior of flow and transport in porous media

    Science.gov (United States)

    Rashidi, Mehdi; Dehmeshki, Jamshid; Dickenson, Eric; Daemi, M. Farhang

    1997-10-01

    This paper describes the development of a novel automated and efficient vision system to obtain velocity and concentration measurement within a porous medium. An aqueous fluid lace with a fluorescent dye to microspheres flows through a transparent, refractive-index-matched column packed with transparent crystals. For illumination purposes, a planar sheet of laser passes through the column as a CCD camera records all the laser illuminated planes. Detailed microscopic velocity and concentration fields have been computed within a 3D volume of the column. For measuring velocities, while the aqueous fluid, laced with fluorescent microspheres, flows through the transparent medium, a CCD camera records the motions of the fluorescing particles by a video cassette recorder. The recorded images are acquired automatically frame by frame and transferred to the computer for processing, by using a frame grabber an written relevant algorithms through an RS-232 interface. Since the grabbed image is poor in this stage, some preprocessings are used to enhance particles within images. Finally, these enhanced particles are monitored to calculate velocity vectors in the plane of the beam. For concentration measurements, while the aqueous fluid, laced with a fluorescent organic dye, flows through the transparent medium, a CCD camera sweeps back and forth across the column and records concentration slices on the planes illuminated by the laser beam traveling simultaneously with the camera. Subsequently, these recorded images are transferred to the computer for processing in similar fashion to the velocity measurement. In order to have a fully automatic vision system, several detailed image processing techniques are developed to match exact images that have different intensities values but the same topological characteristics. This results in normalized interstitial chemical concentrations as a function of time within the porous column.

  17. Neuromorphic circuits impart a sense of touch

    Science.gov (United States)

    Bartolozzi, Chiara

    2018-06-01

    The sense of touch is the ability to perceive consistency, texture, and shape of objects that we manipulate, and the forces we exchange with them. Touch is a source of information that we effortlessly decode to smoothly and naturally grasp and manipulate objects, maintain our posture while walking, or avoid stumbling into obstacles, allowing us to plan, adapt, and correct actions in an ever-changing external world. As such, artificial devices, such as robots or prostheses, that aim to accomplish similar tasks must possess artificial tactile-sensing systems. On page 998 of this issue, Kim et al. (1) report on a “neuromorphic” tactile sensory system based on organic, flexible, electronic circuits that can measure the force applied on the sensing regions. The encoding of the signal is similar to that used by human nerves that are sensitive to tactile stimuli (mechanoreceptors), so the device outputs can substitute for them and communicate with other nerves (e.g., residual nerve fibers of amputees or motor neurons). The proposed system exploits organic electronics that allow for three-dimensional printing of flexible structures that conform to large curved surfaces, as required for placing sensors on robots (2) and prostheses.

  18. Nanotube devices based crossbar architecture: toward neuromorphic computing

    International Nuclear Information System (INIS)

    Zhao, W S; Gamrat, C; Agnus, G; Derycke, V; Filoramo, A; Bourgoin, J-P

    2010-01-01

    Nanoscale devices such as carbon nanotube and nanowires based transistors, memristors and molecular devices are expected to play an important role in the development of new computing architectures. While their size represents a decisive advantage in terms of integration density, it also raises the critical question of how to efficiently address large numbers of densely integrated nanodevices without the need for complex multi-layer interconnection topologies similar to those used in CMOS technology. Two-terminal programmable devices in crossbar geometry seem particularly attractive, but suffer from severe addressing difficulties due to cross-talk, which implies complex programming procedures. Three-terminal devices can be easily addressed individually, but with limited gain in terms of interconnect integration. We show how optically gated carbon nanotube devices enable efficient individual addressing when arranged in a crossbar geometry with shared gate electrodes. This topology is particularly well suited for parallel programming or learning in the context of neuromorphic computing architectures.

  19. Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution

    International Nuclear Information System (INIS)

    Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M

    2007-01-01

    Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus

  20. Neuromorphic function learning with carbon nanotube based synapses

    International Nuclear Information System (INIS)

    Gacem, Karim; Filoramo, Arianna; Derycke, Vincent; Retrouvey, Jean-Marie; Chabi, Djaafar; Zhao, Weisheng; Klein, Jacques-Olivier

    2013-01-01

    The principle of using nanoscale memory devices as artificial synapses in neuromorphic circuits is recognized as a promising way to build ground-breaking circuit architectures tolerant to defects and variability. Yet, actual experimental demonstrations of the neural network type of circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce. We show here that carbon-nanotube-based memory elements can be used as artificial synapses, combined with conventional neurons and trained to perform functions through the application of a supervised learning algorithm. The same ensemble of eight devices can notably be trained multiple times to code successively any three-input linearly separable Boolean logic function despite device-to-device variability. This work thus represents one of the very few demonstrations of actual function learning with synapses based on nanoscale building blocks. The potential of such an approach for the parallel learning of multiple and more complex functions is also evaluated. (paper)