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Sample records for neuromorphic vision systems

  1. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-01

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  2. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-12

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  3. Benchmarking Neuromorphic Vision: Lessons Learnt from Computer Vision

    Directory of Open Access Journals (Sweden)

    Cheston eTan

    2015-10-01

    Full Text Available Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, and algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision.

  4. Benchmarking neuromorphic vision: lessons learnt from computer vision.

    Science.gov (United States)

    Tan, Cheston; Lallee, Stephane; Orchard, Garrick

    2015-01-01

    Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, while algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision.

  5. Large-scale neuromorphic computing systems

    Science.gov (United States)

    Furber, Steve

    2016-10-01

    Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.

  6. Performance Evaluation of Neuromorphic-Vision Object Recognition Algorithms

    Science.gov (United States)

    2014-08-01

    develop artificial vision systems based on the design principles employed by mammalian vision systems. Three such algorithms are briefly described...algorithmic emulations of the entire visual pathway - from retina to the visual cortex. The objective of the effort is to explore the potential for...develop artificial vision systems based on the design principles employed by mammalian vision systems. Three such algorithms are briefly described in

  7. A Neuromorphic System for Video Object Recognition

    Directory of Open Access Journals (Sweden)

    Deepak eKhosla

    2014-11-01

    Full Text Available Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS, is inspired by recent findings in computational neuroscience on feed-forward object detection and classification pipelines for processing and extracting relevant information from visual data. The NEOVUS architecture is inspired by the ventral (what and dorsal (where streams of the mammalian visual pathway and combines retinal processing, form-based and motion-based object detection, and convolutional neural nets based object classification. Our system was evaluated by the Defense Advanced Research Projects Agency (DARPA under the NEOVISION2 program on a variety of urban area video datasets collected from both stationary and moving platforms. The datasets are challenging as they include a large number of targets in cluttered scenes with varying illumination and occlusion conditions. The NEOVUS system was also mapped to commercially available off-the-shelf hardware. The dynamic power requirement for the system that includes a 5.6Mpixel retinal camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W, for an effective energy consumption of 5.4 nanoJoules (nJ per bit of incoming video. In a systematic evaluation of five different teams by DARPA on three aerial datasets, the NEOVUS demonstrated the best performance with the highest recognition accuracy and at least three orders of magnitude lower energy consumption than two independent state of the art computer vision systems. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition towards enabling practical low-power and mobile video processing applications.

  8. 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...

  9. 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.

  10. Neuromorphic computing applications for network intrusion detection systems

    Science.gov (United States)

    Garcia, Raymond C.; Pino, Robinson E.

    2014-05-01

    What is presented here is a sequence of evolving concepts for network intrusion detection. These concepts start with neuromorphic structures for XOR-based signature matching and conclude with computationally based network intrusion detection system with an autonomous structuring algorithm. There is evidence that neuromorphic computation for network intrusion detection is fractal in nature under certain conditions. Specifically, the neural structure can take fractal form when simple neural structuring is autonomous. A neural structure is fractal by definition when its fractal dimension exceeds the synaptic matrix dimension. The authors introduce the use of fractal dimension of the neuromorphic structure as a factor in the autonomous restructuring feedback loop.

  11. An improved cortex-like neuromorphic system for target recognitions

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    Tsitiridis, Aristeidis; Yuen, Peter; Hong, Kan; Chen, Tong; Ibrahim, Izzati; Jackman, James; James, David; Richardson, Mark

    2010-10-01

    This paper reports on the enhancement of biologically-inspired machine vision through a rotation invariance mechanism. Research over the years has suggested that rotation invariance is one of the fundamental generic elements of object constancy, a known generic visual ability of the human brain. Cortex-like vision unlike conventional pixel based machine vision is achieved by mimicking neuromorphic mechanisms of the primates' brain. In this preliminary study, rotation invariance is implemented through histograms from Gabor features of an object. The performance of rotation invariance in the neuromorphic algorithm is assessed by the classification accuracies of a test data set which consists of image objects in five different orientations. It is found that a much more consistent classification result over these five different oriented data sets has been achieved by the integrated rotation invariance neuromorphic algorithm compared to the one without. In addition, the issue of varying aspect ratios of input images to these models is also addressed, in an attempt to create a robust algorithm against a wider variability of input data. The extension of the present achievement is to improve the recognition accuracies while incorporating it to a series of different real-world scenarios which would challenge the approach accordingly.

  12. 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.

  13. 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.

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

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    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.

  15. A neuromorphic system for object detection and classification

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    Khosla, Deepak; Chen, Yang; Kim, Kyungnam; Cheng, Shinko Y.; Honda, Alexander L.; Zhang, Lei

    2013-05-01

    Unattended object detection, recognition and tracking on unmanned reconnaissance platforms in battlefields and urban spaces are topics of emerging importance. In this paper, we present an unattended object recognition system that automatically detects objects of interest in videos and classifies them into various categories (e.g., person, car, truck, etc.). Our system is inspired by recent findings in visual neuroscience on feed-forward object detection and recognition pipeline and mirrors that via two main neuromorphic modules (1) A front-end detection module that combines form and motion based visual attention to search for and detect "integrated" object percepts as is hypothesized to occur in the human visual pathways; (2) A back-end recognition module that processes only the detected object percepts through a neuromorphic object classification algorithm based on multi-scale convolutional neural networks, which can be efficiently implemented in COTS hardware. Our neuromorphic system was evaluated using a variety of urban area video data collected from both stationary and moving platforms. The data are quite challenging as it includes targets at long ranges, occurring under variable conditions of illuminations and occlusion with high clutter. The experimental results of our system showed excellent detection and classification performance. In addition, the proposed bio-inspired approach is good for hardware implementation due to its low complexity and mapping to off-the-shelf conventional hardware.

  16. Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System.

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    Friedmann, Simon; Schemmel, Johannes; Grubl, Andreas; Hartel, Andreas; Hock, Matthias; Meier, Karlheinz

    2017-02-01

    We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a general-purpose processor with full-custom analog elements. This processor is operating in parallel with a fully parallel neuromorphic system consisting of an array of synapses connected to analog, continuous time neuron circuits. Novel analog correlation sensor circuits process spike events for each synapse in parallel and in real-time. The processor uses this pre-processing to compute new weights possibly using additional information following its program. Therefore, to a certain extent, learning rules can be defined in software giving a large degree of flexibility. Synapses realize correlation detection geared towards Spike-Timing Dependent Plasticity (STDP) as central computational primitive in the analog domain. Operating at a speed-up factor of 1000 compared to biological time-scale, we measure time-constants from tens to hundreds of micro-seconds. We analyze variability across multiple chips and demonstrate learning using a multiplicative STDP rule. We conclude that the presented approach will enable flexible and efficient learning as a platform for neuroscientific research and technological applications.

  17. 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.

  18. Generalized Reconfigurable Memristive Dynamical System (MDS for Neuromorphic Applications

    Directory of Open Access Journals (Sweden)

    Mohammad eBavandpour

    2015-11-01

    Full Text Available 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.

  19. 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.

  20. Hardware implementation of machine vision systems: image and video processing

    Science.gov (United States)

    Botella, Guillermo; García, Carlos; Meyer-Bäse, Uwe

    2013-12-01

    This contribution focuses on different topics covered by the special issue titled `Hardware Implementation of Machine vision Systems' including FPGAs, GPUS, embedded systems, multicore implementations for image analysis such as edge detection, segmentation, pattern recognition and object recognition/interpretation, image enhancement/restoration, image/video compression, image similarity and retrieval, satellite image processing, medical image processing, motion estimation, neuromorphic and bioinspired vision systems, video processing, image formation and physics based vision, 3D processing/coding, scene understanding, and multimedia.

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

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    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.

  2. 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

  3. 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.

  4. 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.

  5. 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

    2008-01-01

    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. PMID:19562085

  6. A CAD System for Exploring Neuromorphic Computing with Emerging Technologies

    Science.gov (United States)

    2017-03-01

    Our continued research agenda includes richer applications, including aircraft control and speech recognition , improved evolutionary optimization...phoneme recognition on audio feeds. 
 • A general classification application to make classification decisions on data sets by using pre...Zarella, “TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth,” arXiv:1601- .04183, 2016. 
 9. S. K. Esser et al, “Convolutional Networks for

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

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    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 e...

  8. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

    Science.gov (United States)

    Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

    2017-01-01

    Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

  9. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

    Directory of Open Access Journals (Sweden)

    Moritz B. Milde

    2017-07-01

    Full Text Available Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

  10. Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

    Science.gov (United States)

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

    2017-01-01

    Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

  11. Neuromorphic UAS Collision Avoidance Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Using biologically-inspired neuromorphic optic flow algorithms is a novel approach in collision avoidance for UAS. Traditional computer vision algorithms rely on...

  12. 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.

  13. Hierarchical Address Event Routing for Reconfigurable Large-Scale Neuromorphic Systems.

    Science.gov (United States)

    Park, Jongkil; Yu, Theodore; Joshi, Siddharth; Maier, Christoph; Cauwenberghs, Gert

    2017-10-01

    We present a hierarchical address-event routing (HiAER) architecture for scalable communication of neural and synaptic spike events between neuromorphic processors, implemented with five Xilinx Spartan-6 field-programmable gate arrays and four custom analog neuromophic integrated circuits serving 262k neurons and 262M synapses. The architecture extends the single-bus address-event representation protocol to a hierarchy of multiple nested buses, routing events across increasing scales of spatial distance. The HiAER protocol provides individually programmable axonal delay in addition to strength for each synapse, lending itself toward biologically plausible neural network architectures, and scales across a range of hierarchies suitable for multichip and multiboard systems in reconfigurable large-scale neuromorphic systems. We show approximately linear scaling of net global synaptic event throughput with number of routing nodes in the network, at 3.6×107 synaptic events per second per 16k-neuron node in the hierarchy.

  14. Controllable spiking patterns in long-wavelength VCSELs for neuromorphic photonics systems

    CERN Document Server

    Hurtado, Antonio

    2015-01-01

    Multiple controllable spiking patterns are obtained in a 1310 nm Vertical Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely parallel and orthogonal. Achievement of reproducible spiking responses in VCSELs operating at the telecom wavelengths offers great promise for future uses of these devices in ultrafast neuromorphic photonic systems for non-traditional computing applications.

  15. 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.

  16. 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.

  17. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.

    Science.gov (United States)

    Brüderle, Daniel; Petrovici, Mihai A; Vogginger, Bernhard; Ehrlich, Matthias; Pfeil, Thomas; Millner, Sebastian; Grübl, Andreas; Wendt, Karsten; Müller, Eric; Schwartz, Marc-Olivier; de Oliveira, Dan Husmann; Jeltsch, Sebastian; Fieres, Johannes; Schilling, Moritz; Müller, Paul; Breitwieser, Oliver; Petkov, Venelin; Muller, Lyle; Davison, Andrew P; Krishnamurthy, Pradeep; Kremkow, Jens; Lundqvist, Mikael; Muller, Eilif; Partzsch, Johannes; Scholze, Stefan; Zühl, Lukas; Mayr, Christian; Destexhe, Alain; Diesmann, Markus; Potjans, Tobias C; Lansner, Anders; Schüffny, René; Schemmel, Johannes; Meier, Karlheinz

    2011-05-01

    In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results.

  18. Controllable spiking patterns in long-wavelength vertical cavity surface emitting lasers for neuromorphic photonics systems

    Energy Technology Data Exchange (ETDEWEB)

    Hurtado, Antonio, E-mail: antonio.hurtado@strath.ac.uk [Institute of Photonics, SUPA Department of Physics, University of Strathclyde, TIC Centre, 99 George Street, Glasgow G1 1RD (United Kingdom); Javaloyes, Julien [Departament de Fisica, Universitat de les Illes Balears, c/Valldemossa km 7.5, 07122 Mallorca (Spain)

    2015-12-14

    Multiple controllable spiking patterns are achieved in a 1310 nm Vertical-Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely, parallel and orthogonal. Furthermore, reproducible spiking responses are demonstrated experimentally at sub-nanosecond speed resolution and with a controlled number of spikes fired. This work opens therefore exciting research avenues for the use of VCSELs in ultrafast neuromorphic photonic systems for non-traditional computing applications, such as all-optical binary-to-spiking format conversion and spiking information encoding.

  19. Synthetic Vision Systems

    Science.gov (United States)

    Prinzel, L.J.; Kramer, L.J.

    2009-01-01

    A synthetic vision system is an aircraft cockpit display technology that presents the visual environment external to the aircraft using computer-generated imagery in a manner analogous to how it would appear to the pilot if forward visibility were not restricted. The purpose of this chapter is to review the state of synthetic vision systems, and discuss selected human factors issues that should be considered when designing such displays.

  20. 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.

  1. 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.

  2. Brain-Based Devices for Neuromorphic Computer Systems

    Science.gov (United States)

    2013-07-01

    to keep the wheels in contact with the ceiling. Another key feature is the hook and central gear system that allows the QuadHopter™ to perch on...line. The dimensions of the hook and the gap between the wheels are such that the device can also perch on roof parapets, wall tops, or other such...79 A spiking neural network simulation of working memory Jason G. Fleischer1,2, Joseph A. Gally1, and Gerald M. Edelman1 Abstract Working

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  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. 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

  10. 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.

  11. Wearable Improved Vision System for Color Vision Deficiency Correction

    Science.gov (United States)

    Riccio, Daniel; Di Perna, Luigi; Sanniti Di Baja, Gabriella; De Nino, Maurizio; Rossi, Settimio; Testa, Francesco; Simonelli, Francesca; Frucci, Maria

    2017-01-01

    Color vision deficiency (CVD) is an extremely frequent vision impairment that compromises the ability to recognize colors. In order to improve color vision in a subject with CVD, we designed and developed a wearable improved vision system based on an augmented reality device. The system was validated in a clinical pilot study on 24 subjects with CVD (18 males and 6 females, aged 37.4 ± 14.2 years). The primary outcome was the improvement in the Ishihara Vision Test score with the correction proposed by our system. The Ishihara test score significantly improved (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$p = 0.03$ \\end{document}) from 5.8 ± 3.0 without correction to 14.8 ± 5.0 with correction. Almost all patients showed an improvement in color vision, as shown by the increased test scores. Moreover, with our system, 12 subjects (50%) passed the vision color test as normal vision subjects. The development and preliminary validation of the proposed platform confirm that a wearable augmented-reality device could be an effective aid to improve color vision in subjects with CVD. PMID:28507827

  12. 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.

  13. A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

    Science.gov (United States)

    Nair, Manu V.; Muller, Lorenz K.; Indiveri, Giacomo

    2017-12-01

    Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network’s throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper, we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two benchmark classification tasks.

  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. 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.

  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. 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.

  18. 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.

  19. VISION 21 SYSTEMS ANALYSIS METHODOLOGIES

    Energy Technology Data Exchange (ETDEWEB)

    G.S. Samuelsen; A. Rao; F. Robson; B. Washom

    2003-08-11

    Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into power plant systems that meet performance and emission goals of the Vision 21 program. The study efforts have narrowed down the myriad of fuel processing, power generation, and emission control technologies to selected scenarios that identify those combinations having the potential to achieve the Vision 21 program goals of high efficiency and minimized environmental impact while using fossil fuels. The technology levels considered are based on projected technical and manufacturing advances being made in industry and on advances identified in current and future government supported research. Included in these advanced systems are solid oxide fuel cells and advanced cycle gas turbines. The results of this investigation will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

  20. Closed-loop neuromorphic benchmarks

    CSIR Research Space (South Africa)

    Stewart, TC

    2015-11-01

    Full Text Available the study was exempt from ethical approval procedures.) Did the study presented in the manuscript involve human or animal subjects: No I v i w 1Closed-loop Neuromorphic Benchmarks Terrence C. Stewart 1,∗, Travis DeWolf 1, Ashley Kleinhans 2 and Chris..._link335 program from ev3dev-c (https://github.com/in4lio/ev3dev-c). This allows the EV3 to336 listen for UDP commands that tell it to set motor values and read sensor values. Communication with337 a PC was over a USB link (although the system also...

  1. 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.

  2. Compact Autonomous Hemispheric Vision System

    Science.gov (United States)

    Pingree, Paula J.; Cunningham, Thomas J.; Werne, Thomas A.; Eastwood, Michael L.; Walch, Marc J.; Staehle, Robert L.

    2012-01-01

    Solar System Exploration camera implementations to date have involved either single cameras with wide field-of-view (FOV) and consequently coarser spatial resolution, cameras on a movable mast, or single cameras necessitating rotation of the host vehicle to afford visibility outside a relatively narrow FOV. These cameras require detailed commanding from the ground or separate onboard computers to operate properly, and are incapable of making decisions based on image content that control pointing and downlink strategy. For color, a filter wheel having selectable positions was often added, which added moving parts, size, mass, power, and reduced reliability. A system was developed based on a general-purpose miniature visible-light camera using advanced CMOS (complementary metal oxide semiconductor) imager technology. The baseline camera has a 92 FOV and six cameras are arranged in an angled-up carousel fashion, with FOV overlaps such that the system has a 360 FOV (azimuth). A seventh camera, also with a FOV of 92 , is installed normal to the plane of the other 6 cameras giving the system a > 90 FOV in elevation and completing the hemispheric vision system. A central unit houses the common electronics box (CEB) controlling the system (power conversion, data processing, memory, and control software). Stereo is achieved by adding a second system on a baseline, and color is achieved by stacking two more systems (for a total of three, each system equipped with its own filter.) Two connectors on the bottom of the CEB provide a connection to a carrier (rover, spacecraft, balloon, etc.) for telemetry, commands, and power. This system has no moving parts. The system's onboard software (SW) supports autonomous operations such as pattern recognition and tracking.

  3. 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.

  4. 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.

  5. Neuromorphic Computing for Cognitive Cybersecurity

    Science.gov (United States)

    2017-03-20

    neuromorphic computing using threshold gate networks. Keywords: Neuromorphic computing; Neural networks; cybersecurity Introduction Traditional CMOS scaling...for neural nets is a combined multiply-accumulate operation, evaluated by using a threshold . Neurons of this type implement threshold gate...there is much work to be done in the following areas: • One shot learning, unsupervised learning, concept drift; • Data reduction techniques

  6. COHERENT LASER VISION SYSTEM (CLVS) OPTION PHASE

    Energy Technology Data Exchange (ETDEWEB)

    Robert Clark

    1999-11-18

    The purpose of this research project was to develop a prototype fiber-optic based Coherent Laser Vision System (CLVS) suitable for DOE's EM Robotic program. The system provides three-dimensional (3D) vision for monitoring situations in which it is necessary to update the dimensional spatial data on the order of once per second. The system has total immunity to ambient lighting conditions.

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

    Science.gov (United States)

    2017-03-01

    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...popular choice, and has been adopted in modern LTE / LTE - Advanced systems. By contrast, the reservoir computing system conducts symbol detection and...Spike Intervals LIF Leaky Integrate-and-Fire LS Least-Square LSM Liquid State Machine LTE Long-Term Evolution MIMO Multiple-Input and

  8. 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.

  9. The Circuit Realization of a Neuromorphic Computing System with Memristor-Based Synapse Design

    Science.gov (United States)

    2013-04-01

    memristor-based neural networks mainly fo- cused on system-level simulations using high level languages [11][12] or restricted the synapse design to...BASED SYNAPSE DESIGN 5a. CONTRACT NUMBER FA8750-11-1-0271 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Beiye Liu (UPitt...artificial neural systems. In this work, we propose a memristor-based design of bidirectional transmission excitation/inhibition synapses and implement a

  10. 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

  11. 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.

  12. Flight testing an integrated synthetic vision system

    Science.gov (United States)

    Kramer, Lynda J.; Arthur, Jarvis J., III; Bailey, Randall E.; Prinzel, Lawrence J., III

    2005-05-01

    NASA's Synthetic Vision Systems (SVS) project is developing technologies with practical applications to eliminate low visibility conditions as a causal factor to civil aircraft accidents while replicating the operational benefits of clear day flight operations, regardless of the actual outside visibility condition. A major thrust of the SVS project involves the development/demonstration of affordable, certifiable display configurations that provide intuitive out-the-window terrain and obstacle information with advanced pathway guidance for transport aircraft. The SVS concept being developed at NASA encompasses the integration of tactical and strategic Synthetic Vision Display Concepts (SVDC) with Runway Incursion Prevention System (RIPS) alerting and display concepts, real-time terrain database integrity monitoring equipment (DIME), and Enhanced Vision Systems (EVS) and/or improved Weather Radar for real-time object detection and database integrity monitoring. A flight test evaluation was jointly conducted (in July and August 2004) by NASA Langley Research Center and an industry partner team under NASA's Aviation Safety and Security, Synthetic Vision System project. A Gulfstream G-V aircraft was flown over a 3-week period in the Reno/Tahoe International Airport (NV) local area and an additional 3-week period in the Wallops Flight Facility (VA) local area to evaluate integrated Synthetic Vision System concepts. The enabling technologies (RIPS, EVS and DIME) were integrated into the larger SVS concept design. This paper presents experimental methods and the high level results of this flight test.

  13. Near real-time stereo vision system

    Science.gov (United States)

    Anderson, Charles H. (Inventor); Matthies, Larry H. (Inventor)

    1993-01-01

    The apparatus for a near real-time stereo vision system for use with a robotic vehicle is described. The system is comprised of two cameras mounted on three-axis rotation platforms, image-processing boards, a CPU, and specialized stereo vision algorithms. Bandpass-filtered image pyramids are computed, stereo matching is performed by least-squares correlation, and confidence ranges are estimated by means of Bayes' theorem. In particular, Laplacian image pyramids are built and disparity maps are produced from the 60 x 64 level of the pyramids at rates of up to 2 seconds per image pair. The first autonomous cross-country robotic traverses (of up to 100 meters) have been achieved using the stereo vision system of the present invention with all computing done onboard the vehicle. The overall approach disclosed herein provides a unifying paradigm for practical domain-independent stereo ranging.

  14. Neuromorphic Artificial Touch for Categorization of Naturalistic Textures.

    Science.gov (United States)

    Rongala, Udaya Bhaskar; Mazzoni, Alberto; Oddo, Calogero Maria

    2017-04-01

    We implemented neuromorphic artificial touch and emulated the firing behavior of mechanoreceptors by injecting the raw outputs of a biomimetic tactile sensor into an Izhikevich neuronal model. Naturalistic textures were evaluated with a passive touch protocol. The resulting neuromorphic spike trains were able to classify ten naturalistic textures ranging from textiles to glass to BioSkin, with accuracy as high as 97%. Remarkably, rather than on firing rate features calculated over the stimulation window, the highest achieved decoding performance was based on the precise spike timing of the neuromorphic output as captured by Victor Purpura distance. We also systematically varied the sliding velocity and the contact force to investigate the role of sensing conditions in categorizing the stimuli via the artificial sensory system. We found that the decoding performance based on the timing of neuromorphic spike events was robust for a broad range of sensing conditions. Being able to categorize naturalistic textures in different sensing conditions, these neurorobotic results pave the way to the use of neuromorphic tactile sensors in future real-life neuroprosthetic applications.

  15. Lumber Grading With A Computer Vision System

    Science.gov (United States)

    Richard W. Conners; Tai-Hoon Cho; Philip A. Araman

    1989-01-01

    Over the past few years significant progress has been made in developing a computer vision system for locating and identifying defects on surfaced hardwood lumber. Unfortunately, until September of 1988 little research had gone into developing methods for analyzing rough lumber. This task is arguably more complex than the analysis of surfaced lumber. The prime...

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

    Science.gov (United States)

    Rivera-Acosta, Miguel; Ortega-Cisneros, Susana; Rivera, Jorge; Sandoval-Ibarra, Federico

    2017-09-22

    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.

  17. 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.

  18. 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.

  19. 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.

  20. Holographic Optics For Vision Systems

    Science.gov (United States)

    Freeman, Michael H.

    1989-05-01

    The human visual system is often equated to a photographic camera. This is a poor analogy because the differences are far greater than the similarities. The processing of the human visual system is complex and non-linear so that even optical transfer function concepts must be applied with caution. Holographic optics offers some extra degrees of freedom with respect to refractive optics. Unlike refractive optics, diffractive effects are not, in the first order, dependent on material and geometric shape and require no significant volume. On the other hand they may suffer from fractional efficiencies and strong wavelength dependencies. The Pilkington 'Diffrax' lens invented by the author is an example of a product which steers between the disadvantages and maximises the advantages to provide the world's first diffractive bifocal contact lens. Indications for other visual applications are not very propitious although time and development may show this to be incorrect. This paper will review the interaction between the preferences and antipathies of the human visual system and the optical effects of diffractive systems.

  1. 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

  2. Visual Turing test for computer vision systems.

    Science.gov (United States)

    Geman, Donald; Geman, Stuart; Hallonquist, Neil; Younes, Laurent

    2015-03-24

    Today, computer vision systems are tested by their accuracy in detecting and localizing instances of objects. As an alternative, and motivated by the ability of humans to provide far richer descriptions and even tell a story about an image, we construct a "visual Turing test": an operator-assisted device that produces a stochastic sequence of binary questions from a given test image. The query engine proposes a question; the operator either provides the correct answer or rejects the question as ambiguous; the engine proposes the next question ("just-in-time truthing"). The test is then administered to the computer-vision system, one question at a time. After the system's answer is recorded, the system is provided the correct answer and the next question. Parsing is trivial and deterministic; the system being tested requires no natural language processing. The query engine employs statistical constraints, learned from a training set, to produce questions with essentially unpredictable answers-the answer to a question, given the history of questions and their correct answers, is nearly equally likely to be positive or negative. In this sense, the test is only about vision. The system is designed to produce streams of questions that follow natural story lines, from the instantiation of a unique object, through an exploration of its properties, and on to its relationships with other uniquely instantiated objects.

  3. Fast neuromorphic sound localization for binaural hearing aids.

    Science.gov (United States)

    Park, Paul K J; Ryu, Hyunsurk; Lee, Jun Haeng; Shin, Chang-Woo; Lee, Kyoo Bin; Woo, Jooyeon; Kim, Jun-Seok; Kang, Byung Chang; Liu, Shih-Chii; Delbruck, Tobi

    2013-01-01

    We report on the neuromorphic sound localization circuit which can enhance the perceptual sensation in a hearing aid system. All elements are simple leaky integrate-and-fire neuron circuits with different parameters optimized to suppress the impacts of synaptic circuit noises. The detection range and resolution of the proposed neuromorphic circuit are 500 us and 5 us, respectively. Our results show that, the proposed technique can localize a sound pulse with extremely narrow duration (∼ 1 ms) resulting in real-time response.

  4. Remote Vision Systems for Teleoperated Ground Vehicles

    Science.gov (United States)

    1991-05-01

    Paperworkr Reductlo Proyect (0704-0188). Washingtont. DC 20503._____________________ I AGENCY USE ONLY (Leave bAW4V 2 REPORT DATE 3 REPORT TYPE AND DATES...of the sensory feedback to the operator." [2]. Based on NOSC’s experience with teleoperated vehicles and research in remote presence principles...effort. Lessons learned from this development, and from field tests of TOV vision systems, are presented in this paper. )UEe’ Figure 1. TOV Remote

  5. 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.

  6. Serendipitous Offline Learning in a Neuromorphic Robot.

    Science.gov (United States)

    Stewart, Terrence C; Kleinhans, Ashley; Mundy, Andrew; Conradt, Jörg

    2016-01-01

    We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. 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 the 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 behavior.

  7. Adaptive LIDAR Vision System for Advanced Robotics Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced robotic systems demand an enhanced vision system and image processing algorithms to reduce the percentage of manual operation required. Unstructured...

  8. 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.

  9. Robot vision system programmed in Prolog

    Science.gov (United States)

    Batchelor, Bruce G.; Hack, Ralf

    1995-10-01

    This is the latest in a series of publications which develop the theme of programming a machine vision system using the artificial intelligence language Prolog. The article states the long-term objective of the research program of which this work forms part. Many but not yet all of the goals laid out in this plan have already been achieved in an integrated system, which uses a multi-layer control hierarchy. The purpose of the present paper is to demonstrate that a system based upon a Prolog controller is capable of making complex decisions and operating a standard robot. The authors chose, as a vehicle for this exercise, the task of playing dominoes against a human opponent. This game was selected for this demonstration since it models a range of industrial assembly tasks, where parts are to be mated together. (For example, a 'daisy chain' of electronic equipment and the interconnecting cables/adapters may be likened to a chain of dominoes.)

  10. 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.

  11. 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...

  12. Hybrid Collaborative Stereo Vision System for Mobile Robots Formation

    OpenAIRE

    Flavio Roberti; Juan Marcos Toibero; Carlos Soria; Raquel Frizera Vassallo; Ricardo Carelli

    2009-01-01

    This paper presents the use of a hybrid collaborative stereo vision system (3D-distributed visual sensing using different kinds of vision cameras) for the autonomous navigation of a wheeled robot team. It is proposed a triangulation-based method for the 3D-posture computation of an unknown object by considering the collaborative hybrid stereo vision system, and this way to steer the robot team to a desired position relative to such object while maintaining a desired robot formation. Experimen...

  13. Hybrid Collaborative Stereo Vision System for Mobile Robots Formation

    Directory of Open Access Journals (Sweden)

    Flavio Roberti

    2010-02-01

    Full Text Available This paper presents the use of a hybrid collaborative stereo vision system (3D-distributed visual sensing using different kinds of vision cameras for the autonomous navigation of a wheeled robot team. It is proposed a triangulation-based method for the 3D-posture computation of an unknown object by considering the collaborative hybrid stereo vision system, and this way to steer the robot team to a desired position relative to such object while maintaining a desired robot formation. Experimental results with real mobile robots are included to validate the proposed vision system.

  14. Hybrid Collaborative Stereo Vision System for Mobile Robots Formation

    Directory of Open Access Journals (Sweden)

    Flavio Roberti

    2009-12-01

    Full Text Available This paper presents the use of a hybrid collaborative stereo vision system (3D-distributed visual sensing using different kinds of vision cameras for the autonomous navigation of a wheeled robot team. It is proposed a triangulation-based method for the 3D-posture computation of an unknown object by considering the collaborative hybrid stereo vision system, and this way to steer the robot team to a desired position relative to such object while maintaining a desired robot formation. Experimental results with real mobile robots are included to validate the proposed vision system.

  15. Studying, Teaching and Applying Sustainability Visions Using Systems Modeling

    Directory of Open Access Journals (Sweden)

    David M. Iwaniec

    2014-07-01

    Full Text Available The objective of articulating sustainability visions through modeling is to enhance the outcomes and process of visioning in order to successfully move the system toward a desired state. Models emphasize approaches to develop visions that are viable and resilient and are crafted to adhere to sustainability principles. This approach is largely assembled from visioning processes (resulting in descriptions of desirable future states generated from stakeholder values and preferences and participatory modeling processes (resulting in systems-based representations of future states co-produced by experts and stakeholders. Vision modeling is distinct from normative scenarios and backcasting processes in that the structure and function of the future desirable state is explicitly articulated as a systems model. Crafting, representing and evaluating the future desirable state as a systems model in participatory settings is intended to support compliance with sustainability visioning quality criteria (visionary, sustainable, systemic, coherent, plausible, tangible, relevant, nuanced, motivational and shared in order to develop rigorous and operationalizable visions. We provide two empirical examples to demonstrate the incorporation of vision modeling in research practice and education settings. In both settings, vision modeling was used to develop, represent, simulate and evaluate future desirable states. This allowed participants to better identify, explore and scrutinize sustainability solutions.

  16. Flight test comparison between enhanced vision (FLIR) and synthetic vision systems

    Science.gov (United States)

    Arthur, Jarvis J., III; Kramer, Lynda J.; Bailey, Randall E.

    2005-05-01

    Limited visibility and reduced situational awareness have been cited as predominant causal factors for both Controlled Flight Into Terrain (CFIT) and runway incursion accidents. NASA"s Synthetic Vision Systems (SVS) project is developing practical application technologies with the goal of eliminating low visibility conditions as a causal factor to civil aircraft accidents while replicating the operational benefits of clear day flight operations, regardless of the actual outside visibility condition. A major thrust of the SVS project involves the development/demonstration of affordable, certifiable display configurations that provide intuitive out-the-window terrain and obstacle information with advanced pathway guidance. A flight test evaluation was conducted in the summer of 2004 by NASA Langley Research Center under NASA's Aviation Safety and Security, Synthetic Vision System - Commercial and Business program. A Gulfstream G-V aircraft, modified and operated under NASA contract by the Gulfstream Aerospace Corporation, was flown over a 3-week period at the Reno/Tahoe International Airport and an additional 3-week period at the NASA Wallops Flight Facility to evaluate integrated Synthetic Vision System concepts. Flight testing was conducted to evaluate the performance, usability, and acceptance of an integrated synthetic vision concept which included advanced Synthetic Vision display concepts for a transport aircraft flight deck, a Runway Incursion Prevention System, an Enhanced Vision Systems (EVS), and real-time Database Integrity Monitoring Equipment. This paper focuses on comparing qualitative and subjective results between EVS and SVS display concepts.

  17. Technological process supervising using vision systems cooperating with the LabVIEW vision builder

    Science.gov (United States)

    Hryniewicz, P.; Banaś, W.; Gwiazda, A.; Foit, K.; Sękala, A.; Kost, G.

    2015-11-01

    One of the most important tasks in the production process is to supervise its proper functioning. Lack of required supervision over the production process can lead to incorrect manufacturing of the final element, through the production line downtime and hence to financial losses. The worst result is the damage of the equipment involved in the manufacturing process. Engineers supervise the production flow correctness use the great range of sensors supporting the supervising of a manufacturing element. Vision systems are one of sensors families. In recent years, thanks to the accelerated development of electronics as well as the easier access to electronic products and attractive prices, they become the cheap and universal type of sensors. These sensors detect practically all objects, regardless of their shape or even the state of matter. The only problem is considered with transparent or mirror objects, detected from the wrong angle. Integrating the vision system with the LabVIEW Vision and the LabVIEW Vision Builder it is possible to determine not only at what position is the given element but also to set its reorientation relative to any point in an analyzed space. The paper presents an example of automated inspection. The paper presents an example of automated inspection of the manufacturing process in a production workcell using the vision supervising system. The aim of the work is to elaborate the vision system that could integrate different applications and devices used in different production systems to control the manufacturing process.

  18. 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.

  19. Networked vision system using a Prolog controller

    Science.gov (United States)

    Batchelor, B. G.; Caton, S. J.; Chatburn, L. T.; Crowther, R. A.; Miller, J. W. V.

    2005-11-01

    Prolog offers a very different style of programming compared to conventional languages; it can define object properties and abstract relationships in a way that Java, C, C++, etc. find awkward. In an accompanying paper, the authors describe how a distributed web-based vision systems can be built using elements that may even be located on different continents. One particular system of this general type is described here. The top-level controller is a Prolog program, which operates one, or more, image processing engines. This type of function is natural to Prolog, since it is able to reason logically using symbolic (non-numeric) data. Although Prolog is not suitable for programming image processing functions directly, it is ideal for analysing the results derived by an image processor. This article describes the implementation of two systems, in which a Prolog program controls several image processing engines, a simple robot, a pneumatic pick-and-place arm), LED illumination modules and a various mains-powered devices.

  20. 3-D Signal Processing in a Computer Vision System

    Science.gov (United States)

    Dongping Zhu; Richard W. Conners; Philip A. Araman

    1991-01-01

    This paper discusses the problem of 3-dimensional image filtering in a computer vision system that would locate and identify internal structural failure. In particular, a 2-dimensional adaptive filter proposed by Unser has been extended to 3-dimension. In conjunction with segmentation and labeling, the new filter has been used in the computer vision system to...

  1. 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.

  2. 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. PMID:23423583

  3. 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.

  4. Thermal memristor and neuromorphic networks for manipulating heat flow

    Science.gov (United States)

    Ben-Abdallah, Philippe

    2017-06-01

    A memristor is one of four fundamental two-terminal solid elements in electronics. In addition with the resistor, the capacitor and the inductor, this passive element relates the electric charges to current in solid state elements. Here we report the existence of a thermal analog for this element made with metal-insulator transition materials. We demonstrate that these memristive systems can be used to create thermal neurons opening so the way to neuromorphic networks for smart thermal management and information treatment.

  5. 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.

  6. 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

  7. Skimming Digits: Neuromorphic Classification of Spike-Encoded Images

    Directory of Open Access Journals (Sweden)

    Gregory Kevin Cohen

    2016-04-01

    Full Text Available The growing demands placed upon the field of computer vision has renewed the focus on alternative visual scene representations and processing paradigms. Silicon retinea provide an alternative means of imaging the visual environment, and produce frame-free spatio-temporal data. This paper presents an investigation into event-based digit classification using N-MNIST,a neuromorphic dataset created with a silicon retina, and the Synaptic Kernel Inverse Method (SKIM, a learning method based on principles of dendritic computation. As this work represents the first large-scale and multi-class classification task performed using the SKIM network, it explores different training patterns and output determination methods necessary to extend the original SKIM method to support multi-class problems. Making use of SKIM networks applied to real-world datasets, implementing the largest hidden layer sizes and simultaneously training the largest number of output neurons, the classification system achieved a best-case accuracy of 92.87% for a network containing 10,000 hidden layer neurons. These results represent the highest accuracies achieved against the dataset to date and serves to validate the application of the SKIM method to event-based visual classification tasks. Additionally, the study found that using a square pulse as the supervisory training signal produced the highest accuracy for most output determination methods, but the results also demonstrate that an exponential pattern is better suited to hardware implementations as it makes use of the simplest output determination method based on the maximum value.

  8. Neuromorphic Silicon Neuron Circuits

    National Research Council Canada - National Science Library

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; Schaik, André van; 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...

  9. 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?

  10. 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

  11. Eye Vision Testing System and Eyewear Using Micromachines

    Directory of Open Access Journals (Sweden)

    Nabeel A. Riza

    2015-11-01

    Full Text Available Proposed is a novel eye vision testing system based on micromachines that uses micro-optic, micromechanic, and microelectronic technologies. The micromachines include a programmable micro-optic lens and aperture control devices, pico-projectors, Radio Frequency (RF, optical wireless communication and control links, and energy harvesting and storage devices with remote wireless energy transfer capabilities. The portable lightweight system can measure eye refractive powers, optimize light conditions for the eye under testing, conduct color-blindness tests, and implement eye strain relief and eye muscle exercises via time sequenced imaging. A basic eye vision test system is built in the laboratory for near-sighted (myopic vision spherical lens refractive error correction. Refractive error corrections from zero up to −5.0 Diopters and −2.0 Diopters are experimentally demonstrated using the Electronic-Lens (E-Lens and aperture control methods, respectively. The proposed portable eye vision test system is suited for children’s eye tests and developing world eye centers where technical expertise may be limited. Design of a novel low-cost human vision corrective eyewear is also presented based on the proposed aperture control concept. Given its simplistic and economical design, significant impact can be created for humans with vision problems in the under-developed world.

  12. 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

    state acceleration driven pendulum. Sensor input for the filter is provided by a vision based system that measures the position of the slung load. The estimator needs no prior knowledge of the system as it estimates the length of the suspension system together with the system states. Finally...

  13. Direction Identification System of Garlic Clove Based on Machine Vision

    OpenAIRE

    Gao Chi; Gao Hui

    2013-01-01

    In order to fulfill the requirements of seeding direction of garlic cloves, the paper proposed a research method of garlic clove direction identification based on machine vision, it expounded the theory of garlic clove direction identification, stated the arithmetic of it, designed the direction identification device of it, then developed the control system of garlic clove direction identification based on machine vision, at last tested the garlic clove direction identification, and the resul...

  14. 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.

  15. 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...

  16. 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.

  17. A modular real-time vision system for humanoid robots

    Science.gov (United States)

    Trifan, Alina L.; Neves, António J. R.; Lau, Nuno; Cunha, Bernardo

    2012-01-01

    Robotic vision is nowadays one of the most challenging branches of robotics. In the case of a humanoid robot, a robust vision system has to provide an accurate representation of the surrounding world and to cope with all the constraints imposed by the hardware architecture and the locomotion of the robot. Usually humanoid robots have low computational capabilities that limit the complexity of the developed algorithms. Moreover, their vision system should perform in real time, therefore a compromise between complexity and processing times has to be found. This paper presents a reliable implementation of a modular vision system for a humanoid robot to be used in color-coded environments. From image acquisition, to camera calibration and object detection, the system that we propose integrates all the functionalities needed for a humanoid robot to accurately perform given tasks in color-coded environments. The main contributions of this paper are the implementation details that allow the use of the vision system in real-time, even with low processing capabilities, the innovative self-calibration algorithm for the most important parameters of the camera and its modularity that allows its use with different robotic platforms. Experimental results have been obtained with a NAO robot produced by Aldebaran, which is currently the robotic platform used in the RoboCup Standard Platform League, as well as with a humanoid build using the Bioloid Expert Kit from Robotis. As practical examples, our vision system can be efficiently used in real time for the detection of the objects of interest for a soccer playing robot (ball, field lines and goals) as well as for navigating through a maze with the help of color-coded clues. In the worst case scenario, all the objects of interest in a soccer game, using a NAO robot, with a single core 500Mhz processor, are detected in less than 30ms. Our vision system also includes an algorithm for self-calibration of the camera parameters as well

  18. 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

  19. Superconducting Optoelectronic Circuits for Neuromorphic Computing

    Science.gov (United States)

    Shainline, Jeffrey M.; Buckley, Sonia M.; Mirin, Richard P.; Nam, Sae Woo

    2017-03-01

    Neural networks have proven effective for solving many difficult computational problems, yet implementing complex neural networks in software is computationally expensive. To explore the limits of information processing, it is necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density (1 mW /cm2 at 20-MHz firing rate) necessary to scale to systems with enormous entropy. Estimates comparing the proposed hardware platform to a human brain show that with the same number of neurons (1 011) and 700 independent connections per neuron, the hardware presented here may achieve an order of magnitude improvement in synaptic events per second per watt.

  20. 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...

  1. 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...... 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...

  2. 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.

  3. 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.

  4. Thermal memristor and neuromorphic networks for manipulating heat flow

    Directory of Open Access Journals (Sweden)

    Philippe Ben-Abdallah

    2017-06-01

    Full Text Available A memristor is one of four fundamental two-terminal solid elements in electronics. In addition with the resistor, the capacitor and the inductor, this passive element relates the electric charges to current in solid state elements. Here we report the existence of a thermal analog for this element made with metal-insulator transition materials. We demonstrate that these memristive systems can be used to create thermal neurons opening so the way to neuromorphic networks for smart thermal management and information treatment.

  5. A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach.

    Science.gov (United States)

    Jimenez-Fernandez, Angel; Cerezuela-Escudero, Elena; Miro-Amarante, Lourdes; Dominguez-Moralse, Manuel Jesus; de Asis Gomez-Rodriguez, Francisco; Linares-Barranco, Alejandro; Jimenez-Moreno, Gabriel

    2017-04-01

    This paper presents a new architecture, design flow, and field-programmable gate array (FPGA) implementation analysis of a neuromorphic binaural auditory sensor, designed completely in the spike domain. Unlike digital cochleae that decompose audio signals using classical digital signal processing techniques, the model presented in this paper processes information directly encoded as spikes using pulse frequency modulation and provides a set of frequency-decomposed audio information using an address-event representation interface. In this case, a systematic approach to design led to a generic process for building, tuning, and implementing audio frequency decomposers with different features, facilitating synthesis with custom features. This allows researchers to implement their own parameterized neuromorphic auditory systems in a low-cost FPGA in order to study the audio processing and learning activity that takes place in the brain. In this paper, we present a 64-channel binaural neuromorphic auditory system implemented in a Virtex-5 FPGA using a commercial development board. The system was excited with a diverse set of audio signals in order to analyze its response and characterize its features. The neuromorphic auditory system response times and frequencies are reported. The experimental results of the proposed system implementation with 64-channel stereo are: a frequency range between 9.6 Hz and 14.6 kHz (adjustable), a maximum output event rate of 2.19 Mevents/s, a power consumption of 29.7 mW, the slices requirements of 11141, and a system clock frequency of 27 MHz.

  6. A neuromorphic model of spatial lookahead planning.

    Science.gov (United States)

    Ivey, Richard; Bullock, Daniel; Grossberg, Stephen

    2011-04-01

    In order to create spatial plans in a complex and changing world, organisms need to rapidly adapt to novel configurations of obstacles that impede simple routes to goal acquisition. Some animals can mentally create successful multistep spatial plans in new visuo-spatial layouts that preclude direct, one-segment routes to goal acquisition. Lookahead multistep plans can, moreover, be fully developed before an animal executes any step in the plan. What neural computations suffice to yield preparatory multistep lookahead plans during spatial cognition of an obstructed two-dimensional scene? To address this question, we introduce a novel neuromorphic system for spatial lookahead planning in which a feasible sequence of actions is prepared before movement begins. The proposed system combines neurobiologically plausible mechanisms of recurrent shunting competitive networks, visuo-spatial diffusion, and inhibition-of-return. These processes iteratively prepare a multistep trajectory to the desired goal state in the presence of obstacles. The planned trajectory can be stored using a primacy gradient in a sequential working memory and enacted by a competitive queuing process. The proposed planning system is compared with prior planning models. Simulation results demonstrate system robustness to environmental variations. Notably, the model copes with many configurations of obstacles that lead other visuo-spatial planning models into selecting undesirable or infeasible routes. Our proposal is inspired by mechanisms of spatial attention and planning in primates. Accordingly, our simulation results are compared with neurophysiological and behavioral findings from relevant studies of spatial lookahead behavior. Copyright © 2010 Elsevier Ltd. All rights reserved.

  7. Multivariate Analysis Techniques for Optimal Vision System Design

    DEFF Research Database (Denmark)

    Sharifzadeh, Sara

    (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......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...... based on the existing sparse regression methods (EN and lasso) and one unsupervised feature selection strategy based on the local maxima of the spectral 1D/2D signals of food items are proposed. In addition, two novel feature extraction and selection strategies are introduced; sparse supervised PCA...

  8. 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.

  9. 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...

  10. Serendipitous offline learning in a neuromorphic robot

    CSIR Research Space (South Africa)

    Stewart, TC

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex senso-rimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor...

  11. IPS - a vision aided navigation system

    Science.gov (United States)

    Börner, Anko; Baumbach, Dirk; Buder, Maximilian; Choinowski, Andre; Ernst, Ines; Funk, Eugen; Grießbach, Denis; Schischmanow, Adrian; Wohlfeil, Jürgen; Zuev, Sergey

    2017-04-01

    Ego localization is an important prerequisite for several scientific, commercial, and statutory tasks. Only by knowing one's own position, can guidance be provided, inspections be executed, and autonomous vehicles be operated. Localization becomes challenging if satellite-based navigation systems are not available, or data quality is not sufficient. To overcome this problem, a team of the German Aerospace Center (DLR) developed a multi-sensor system based on the human head and its navigation sensors - the eyes and the vestibular system. This system is called integrated positioning system (IPS) and contains a stereo camera and an inertial measurement unit for determining an ego pose in six degrees of freedom in a local coordinate system. IPS is able to operate in real time and can be applied for indoor and outdoor scenarios without any external reference or prior knowledge. In this paper, the system and its key hardware and software components are introduced. The main issues during the development of such complex multi-sensor measurement systems are identified and discussed, and the performance of this technology is demonstrated. The developer team started from scratch and transfers this technology into a commercial product right now. The paper finishes with an outlook.

  12. 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.

  13. Memristor: A New Concept in Synchronization of Coupled Neuromorphic Circuits

    Directory of Open Access Journals (Sweden)

    Ch. K. Volos

    2014-10-01

    Full Text Available The existence of the memristor, as a fourth fundamental circuit element, by researchers at Hewlett Packard (HP labs in 2008, has attracted much interest since then. This occurs because the memristor opens up new functionalities in electronics and it has led to the interpretation of phenomena not only in electronic devices but also in biological systems. Furthermore, many research teams work on projects, which use memristors in neuromorphic devices to simulate learning, adaptive and spontaneous behavior while other teams on systems, which attempt to simulate the behavior of biological synapses. In this paper, the latest achievements and applications of this newly development circuit element are presented. Also, the basic features of neuromorphic circuits, in which the memristor can be used as an electrical synapse, are studied. In this direction, a flux-controlled memristor model is adopted for using as a coupling element between coupled electronic circuits, which simulate the behavior of neuron-cells. For this reason, the circuits which are chosen realize the systems of differential equations that simulate the well-known Hindmarsh-Rose and FitzHugh-Nagumo neuron models. Finally, the simulation results of the use of a memristor as an electric synapse present the effectiveness of the proposed method and many interesting dynamic phenomena concerning the behavior of coupled neuron-cells.

  14. Flexible Vision Control System For Precision Robotic Arc Welding

    Science.gov (United States)

    Richardson, Richard W.

    1989-02-01

    A system is described which is based on a unique weld image sensor design which integrates the optical system into the weld end effector to produce the so-called "coaxial view" of the weld zone. The resulting weld image is processed by a flexible, table driven vision processing system which can be adapted to detect a variety of features and feature relationships. Provision is made for interactive "teaching" of image features for generation of table parameters from test welds. A table driven control program allows various vision control strategies to be invoked. The main result of the system is a level of emulation of the capability of the expert welder or welding operator, essential to successful precision welding robotization.

  15. CAIP system for vision-based on-machine measurement

    Science.gov (United States)

    Xia, Rui-xue; Lu, Rong-sheng; Shi, Yan-qiong; Li, Qi; Dong, Jing-tao; Liu, Ning

    2011-12-01

    Computer-Aided Inspection Planning (CAIP) is an important module of modern dimensional measuring instruments, utilizing the CAIP for machined parts inspection is an important indication of the level of automation and intelligence. Aiming at the characteristic of visual inspection, it develops a CAIP system for vision-based On-Machine Measurement (OMM) based on a CAD development platform whose kernel is Open CASCADE. The working principle of vision-based OMM system is introduced, and the key technologies of CAIP include inspection information extraction, sampling strategy, inspection path planning, inspection codes generation, inspection procedure verification, data post-processor, comparison, and so on. The entire system was verified on a CNC milling machine, and relevant examples show that the system can accomplish automatic inspection planning task for common parts efficiently.

  16. 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

  17. 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.

  18. A trunk ranging system based on binocular stereo vision

    Science.gov (United States)

    Zhao, Xixuan; Kan, Jiangming

    2017-07-01

    Trunk ranging is an essential function for autonomous forestry robots. Traditional trunk ranging systems based on personal computers are not convenient in practical application. This paper examines the implementation of a trunk ranging system based on the binocular vision theory via TI's DaVinc DM37x system. The system is smaller and more reliable than that implemented using a personal computer. It calculates the three-dimensional information from the images acquired by binocular cameras, producing the targeting and ranging results. The experimental results show that the measurement error is small and the system design is feasible for autonomous forestry robots.

  19. 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...

  20. Integration of nanoscale memristor synapses in neuromorphic computing architectures.

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis

    2013-09-27

    Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.

  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. Integration of nanoscale memristor synapses in neuromorphic computing architectures

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis

    2013-09-01

    Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.

  3. 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.

  4. Projector calibration method based on stereo vision system

    Science.gov (United States)

    Yang, Shourui; Liu, Miao; Song, Jiahui; Yin, Shibin; Guo, Yin; Ren, Yongjie; Zhu, Jigui

    2017-12-01

    Digital projectors have been widely used in many accuracy-sensitive fields and the projector should be calibrated precisely. Different from the existing methods using a single camera and a high-accuracy diffuse planar target, the projector calibration method is proposed based on a stereo vision system and a white board. A calibration pattern with several virtual mark points is projected onto the white board at different poses and captured by the stereo vision system. A two-step optimization algorithm is proposed to calculate the intrinsic parameters with roughly coplanar points. The white board has no mark points on it and there is no need to guarantee its flatness, so it avoids using the expensive and fragile diffuse target. Finally, the experimental results have demonstrated the improvement in accuracy of the proposed method.

  5. 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

  6. 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.

  7. 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.

  8. Establishing an evoked-potential vision-tracking system

    Science.gov (United States)

    Skidmore, Trent A.

    1991-01-01

    This paper presents experimental evidence to support the feasibility of an evoked-potential vision-tracking system. The topics discussed are stimulator construction, verification of the photic driving response in the electroencephalogram, a method for performing frequency separation, and a transient-analysis example. The final issue considered is that of object multiplicity (concurrent visual stimuli with different flashing rates). The paper concludes by discussing several applications currently under investigation.

  9. Vector Disparity Sensor with Vergence Control for Active Vision Systems

    Directory of Open Access Journals (Sweden)

    Eduardo Ros

    2012-02-01

    Full Text Available 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.

  10. 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.

  11. Automatic gear sorting system based on monocular vision

    Directory of Open Access Journals (Sweden)

    Wenqi Wu

    2015-11-01

    Full Text Available An automatic gear sorting system based on monocular vision is proposed in this paper. A CCD camera fixed on the top of the sorting system is used to obtain the images of the gears on the conveyor belt. The gears׳ features including number of holes, number of teeth and color are extracted, which is used to categorize the gears. Photoelectric sensors are used to locate the gears׳ position and produce the trigger signals for pneumatic cylinders. The automatic gear sorting is achieved by using pneumatic actuators to push different gears into their corresponding storage boxes. The experimental results verify the validity and reliability of the proposed method and system.

  12. 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.

  13. Bionic Vision-Based Intelligent Power Line Inspection System.

    Science.gov (United States)

    Li, Qingwu; Ma, Yunpeng; He, Feijia; Xi, Shuya; Xu, Jinxin

    2017-01-01

    Detecting the threats of the external obstacles to the power lines can ensure the stability of the power system. Inspired by the attention mechanism and binocular vision of human visual system, an intelligent power line inspection system is presented in this paper. Human visual attention mechanism in this intelligent inspection system is used to detect and track power lines in image sequences according to the shape information of power lines, and the binocular visual model is used to calculate the 3D coordinate information of obstacles and power lines. In order to improve the real time and accuracy of the system, we propose a new matching strategy based on the traditional SURF algorithm. The experimental results show that the system is able to accurately locate the position of the obstacles around power lines automatically, and the designed power line inspection system is effective in complex backgrounds, and there are no missing detection instances under different conditions.

  14. 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.

  15. ACCURACY OF A 3D VISION SYSTEM FOR INSPECTION

    DEFF Research Database (Denmark)

    Carmignato, Simone; Savio, Enrico; De Chiffre, Leonardo

    2003-01-01

    ABSTRACT. This paper illustrates an experimental method to assess the accuracy of a three-dimensional (3D) vision system for the inspection of complex geometry. The aim is to provide a procedure to evaluate task related measurement uncertainty for virtually any measurement task. The key element...... for the purpose to establish traceability. Accuracy performances of optical digitisation systems are assessed on the basis of deviations existing between acquired cloud points and the CMM measurements. To demonstrate the feasibility of the proposed method, the procedure is applied to an industrial case study....

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Scratch measurement system using machine vision: part II

    Science.gov (United States)

    Sarr, Dennis P.

    1992-03-01

    Aircraft skins and windows must not have scratches, which are unacceptable for cosmetic and structural reasons. Manual methods are inadequate in giving accurate reading and do not provide a hardcopy report. A prototype scratch measurement system (SMS) using computer vision and image analysis has been developed. This paper discusses the prototype description, novel ideas, improvements, repeatability, reproducibility, accuracy, and the calibration method. Boeing's Calibration Certification Laboratory has given the prototype a qualified certification. The SMS is portable for usage in factory or aircraft hangars anywhere in the world.

  2. 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.

  3. The robot's eyes - Stereo vision system for automated scene analysis

    Science.gov (United States)

    Williams, D. S.

    1977-01-01

    Attention is given to the robot stereo vision system which maintains the image produced by solid-state detector television cameras in a dynamic random access memory called RAPID. The imaging hardware consists of sensors (two solid-state image arrays using a charge injection technique), a video-rate analog-to-digital converter, the RAPID memory, and various types of computer-controlled displays, and preprocessing equipment (for reflexive actions, processing aids, and object detection). The software is aimed at locating objects and transversibility. An object-tracking algorithm is discussed and it is noted that tracking speed is in the 50-75 pixels/s range.

  4. 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.

  5. Highly Scalable Monitoring System on Chip for Multi-Stream Auto-Adaptable Vision System

    OpenAIRE

    Isavudeen, Ali; Ngan, Nicolas; DOKLADALOVA, Eva; Akil , Mohamed

    2017-01-01

    International audience; The integration of multiple and technologically heterogeneous sensors (infrared, color, etc) in vision systems tend to democratize. The objective is to benefit from the multi-modal perception allowing to improve the quality and ro-bustness of challenging applications such as the advanced driver assistance, 3-D vision, inspection systems or military observation equipment. However, the multiplication of heterogeneous processing pipelines makes the design of efficient com...

  6. 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.

  7. Stochastic Learning in Oxide Binary Synaptic Device for Neuromorphic Computing

    Directory of Open Access Journals (Sweden)

    Shimeng eYu

    2013-10-01

    Full Text Available 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 resistance 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.

  8. 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.

  9. 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

  10. 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...

  11. Design of Gear Defect Detection System Based on Machine Vision

    Science.gov (United States)

    Wang, Yu; Wu, Zhiheng; Duan, Xianyun; Tong, Jigang; Li, Ping; Chen, min; Lin, Qinglin

    2018-01-01

    In order to solve such problems as low efficiency, low quality and instability of gear surface defect detection, we designed a detection system based on machine vision, sensor coupling. By multisensory coupling, and then CCD camera image collection of gear products, using VS2010 to cooperate with Halcon library for a series of analysis and processing of images. At last, the results are fed back to the control end, and the rejected device is removed to the collecting box. The system has successfully identified defective gear. The test results show that this system can identify and eliminate the defects gear quickly and efficiently. It has reached the requirement of gear product defect detection line automation and has a certain application value.

  12. A Portable Stereo Vision System for Whole Body Surface Imaging.

    Science.gov (United States)

    Yu, Wurong; Xu, Bugao

    2010-04-01

    This paper presents a whole body surface imaging system based on stereo vision technology. We have adopted a compact and economical configuration which involves only four stereo units to image the frontal and rear sides of the body. The success of the system depends on a stereo matching process that can effectively segment the body from the background in addition to recovering sufficient geometric details. For this purpose, we have developed a novel sub-pixel, dense stereo matching algorithm which includes two major phases. In the first phase, the foreground is accurately segmented with the help of a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed in combination with global optimization within a regularization framework, so as to ensure both accuracy and reliability. Our experimental results show that the system can realistically capture smooth and natural whole body shapes with high accuracy.

  13. 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.

  14. The modeling of portable 3D vision coordinate measuring system

    Science.gov (United States)

    Liu, Shugui; Huang, Fengshan; Peng, Kai

    2005-02-01

    The portable three-dimensional vision coordinate measuring system, which consists of a light pen, a CCD camera and a laptop computer, can be widely applied in most coordinate measuring fields especially on the industrial spots. On the light pen there are at least three point-shaped light sources (LEDs) acting as the measured control characteristic points and a touch trigger probe with a spherical stylus which is used to contact the point to be measured. The most important character of this system is that three light sources and the probe stylus are aligned in one line with known positions. In building and studying this measuring system, how to construct the system"s mathematical model is the most key problem called perspective of three-collinear-points problem, which is a particular case of perspective of three-points problem (P3P). On the basis of P3P and spatial analytical geometry theory, the system"s mathematical model is established in this paper. What"s more, it is verified that perspective of three-collinear-points problem has a unique solution. And the analytical equations of the measured point"s coordinates are derived by using the system"s mathematical model and the restrict condition that three light sources and the probe stylus are aligned in one line. Finally, the effectiveness of the mathematical model is confirmed by experiments.

  15. Applying Memristors Towards Low-Power, Dynamic Learning for Neuromorphic Applications

    Science.gov (United States)

    2017-03-01

    time speech recognition and spatio-temporal navigation. We present simulations of the mrDANNA system using physically integrated memristors (aka ReRAM...neuromorphic computation, which has gained widespread acceptance for its success in areas such as speech recognition , artificial intelligence, and...he top-perform and modified il a network w ionary optimiz rks which sol 2D navigatio Figure 1b. Futu d include thr speech recogn ted in hardwa PGAs

  16. An adaptable neuromorphic model of orientation selectivity based on floating gate dynamics

    Science.gov (United States)

    Gupta, Priti; Markan, C. M.

    2014-01-01

    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 in silicon. PMID

  17. 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.

  18. Wearable design issues for electronic vision enhancement systems

    Science.gov (United States)

    Dvorak, Joe

    2006-09-01

    As the baby boomer generation ages, visual impairment will overtake a significant portion of the US population. At the same time, more and more of our world is becoming digital. These two trends, coupled with the continuing advances in digital electronics, argue for a rethinking in the design of aids for the visually impaired. This paper discusses design issues for electronic vision enhancement systems (EVES) [R.C. Peterson, J.S. Wolffsohn, M. Rubinstein, et al., Am. J. Ophthalmol. 136 1129 (2003)] that will facilitate their wearability and continuous use. We briefly discuss the factors affecting a person's acceptance of wearable devices. We define the concept of operational inertia which plays an important role in our design of wearable devices and systems. We then discuss how design principles based upon operational inertia can be applied to the design of EVES.

  19. 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.

  20. Research situation and development trend of the binocular stereo vision system

    Science.gov (United States)

    Wang, Tonghao; Liu, Bingqi; Wang, Ying; Chen, Yichao

    2017-05-01

    Since the 21st century, with the development of the computer and signal processing technology, a new comprehensive subject that called computer vision was generated. Computer vision covers a wide range of knowledge, which includes physics, mathematics, biology, computer technology and other arts subjects. It contains much content, and becomes more and more powerful, not only can realize the function of the human eye "see", also can realize the human eyes cannot. In recent years, binocular stereo vision which is a main branch of the computer vision has become the focus of the research in the field of the computer vision. In this paper, the binocular stereo vision system, the development of present situation and application at home and abroad are summarized. With the current problems of the binocular stereo vision system, his own opinions are given. Furthermore, a prospective view of the future application and development of this technology are prospected.

  1. neu-VISION: an explosives detection system for transportation security

    Science.gov (United States)

    Warman, Kieffer; Penn, David

    2008-04-01

    Terrorists were targeting commercial airliners long before the 9/11 attacks on the World Trade Center and the Pentagon. Despite heightened security measures, commercial airliners remain an attractive target for terrorists, as evidenced by the August 2006 terrorist plot to destroy as many as ten aircraft in mid-flight from the United Kingdom to the United States. As a response to the security threat air carriers are now required to screen 100-percent of all checked baggage for explosives. The scale of this task is enormous and the Transportation Security Administration has deployed thousands of detection systems. Although this has resulted in improved security, the performance of the installed systems is not ideal. Further improvements are needed and can only be made with new technologies that ensure a flexible Concept of Operations and provide superior detection along with low false alarm rates and excellent dependability. To address security needs Applied Signal Technology, Inc. is developing an innovative and practical solution to meet the performance demands of aviation security. The neu-VISION TM system is expected to provide explosives detection performance for checked baggage that both complements and surpasses currently deployed performance. The neu-VISION TM system leverages a 5 year R&D program developing the Associated Particle Imaging (API) technique; a neutron based non-intrusive material identification and imaging technique. The superior performance afforded by this neutron interrogation technique delivers false alarm rates much lower than deployed technologies and "sees through" dense, heavy materials. Small quantities of explosive material are identified even in the cluttered environments.

  2. 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.

  3. Tunable low energy, compact and high performance neuromorphic circuit for spike-based synaptic plasticity.

    Directory of Open Access Journals (Sweden)

    Mostafa Rahimi Azghadi

    Full Text Available Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities.

  4. Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Narayan eSrinivasa

    2015-12-01

    Full Text Available Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that are can exhibit adaptive behaviors.Many such designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoid it.

  5. 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.

  6. Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware.

    Science.gov (United States)

    Srinivasa, Narayan; Stepp, Nigel D; Cruz-Albrecht, Jose

    2015-01-01

    Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it.

  7. 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.

  8. 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.

  9. Automatic vision system for an objective cotation of textile surfaces

    Science.gov (United States)

    Konik, Hubert; Laget, Bernard; Redortier, Bernard; Calonnier, Maurice

    1996-02-01

    This paper presents a general method for achieving an automatic vision system for the quantification of visual aspects in the textile field. The process begins in fact with the decomposition of the image into a structure and a texture image. This operation is achieved by filtering in the Fourier domain, following an additive model of decomposition with disconnected masks. Some new quantifiers are then computed for texture images and a segmentation is only done if necessary. A new method is introduced as well by using localized pyramids, called local pyramids, centered on each of the relevant parts and no more critical for particularly elongated objects. The results are also efficient on more than 200 images, where the automatic conation is in accordance with the expert evaluations.

  10. 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.

  11. Survey of computer vision in roadway transportation systems

    Science.gov (United States)

    Manikoth, Natesh; Loce, Robert; Bernal, Edgar; Wu, Wencheng

    2012-01-01

    There is a world-wide 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 conference presentation and publication is brief introduction to the field, and will be followed by an in-depth journal paper that provides more details on the imaging systems and algorithms.

  12. 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.

  13. Visual tracking in stereo. [by computer vision system

    Science.gov (United States)

    Saund, E.

    1981-01-01

    A method is described for visual object tracking by a computer vision system using TV cameras and special low-level image processing hardware. The tracker maintains an internal model of the location, orientation, and velocity of the object in three-dimensional space. This model is used to predict where features of the object will lie on the two-dimensional images produced by stereo TV cameras. The differences in the locations of features in the two-dimensional images as predicted by the internal model and as actually seen create an error signal in the two-dimensional representation. This is multiplied by a generalized inverse Jacobian matrix to deduce the error in the internal model. The procedure repeats to update the internal model of the object's location, orientation and velocity continuously.

  14. 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.

  15. 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...

  16. Helmet-mounted pilot night vision systems: Human factors issues

    Science.gov (United States)

    Hart, Sandra G.; Brickner, Michael S.

    1989-01-01

    Helmet-mounted displays of infrared imagery (forward-looking infrared (FLIR)) allow helicopter pilots to perform low level missions at night and in low visibility. However, pilots experience high visual and cognitive workload during these missions, and their performance capabilities may be reduced. Human factors problems inherent in existing systems stem from three primary sources: the nature of thermal imagery; the characteristics of specific FLIR systems; and the difficulty of using FLIR system for flying and/or visually acquiring and tracking objects in the environment. The pilot night vision system (PNVS) in the Apache AH-64 provides a monochrome, 30 by 40 deg helmet-mounted display of infrared imagery. Thermal imagery is inferior to television imagery in both resolution and contrast ratio. Gray shades represent temperatures differences rather than brightness variability, and images undergo significant changes over time. The limited field of view, displacement of the sensor from the pilot's eye position, and monocular presentation of a bright FLIR image (while the other eye remains dark-adapted) are all potential sources of disorientation, limitations in depth and distance estimation, sensations of apparent motion, and difficulties in target and obstacle detection. Insufficient information about human perceptual and performance limitations restrains the ability of human factors specialists to provide significantly improved specifications, training programs, or alternative designs. Additional research is required to determine the most critical problem areas and to propose solutions that consider the human as well as the development of technology.

  17. 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.

  18. Offshore remote sensing of the ocean by stereo vision systems

    Science.gov (United States)

    Gallego, Guillermo; Shih, Ping-Chang; Benetazzo, Alvise; Yezzi, Anthony; Fedele, Francesco

    2014-05-01

    In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting oberved waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss furure lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage

  19. 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.

  20. Information Systems in the University of Saskatchewan Libraries: A Vision for the 1990s.

    Science.gov (United States)

    Saskatchewan Univ., Saskatoon. Libraries.

    This report describes the vision of the Information Systems Advisory Committee (ISAC) of an Information Systems Model for the 1990s. It includes an evaluation of the present automation environment at the university, a vision of library automation at the University of Saskatchewan between 1994 and 1999, and specific recommendations on such issues…

  1. 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...

  2. Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique

    OpenAIRE

    Ghazali, Kamarul Hawari; Mustafa, Mohd. Marzuki; Hussain, Aini

    2009-01-01

    Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the f...

  3. Intraocular pressure fluctuation during microincision vitrectomy with constellation vision system.

    Science.gov (United States)

    Sugiura, Yoshimi; Okamoto, Fumiki; Okamoto, Yoshifumi; Hiraoka, Takahiro; Oshika, Tetsuro

    2013-11-01

    To investigate intraocular pressure (IOP) fluctuation during various vitrectomy maneuvers using the vitrectomy system (Alcon Constellation Vision System). An experimental study as laboratory investigation. In porcine eyes, 23- and 25-gauge vitrectomy was performed, and IOP fluctuations were evaluated in vitreous cutting mode, in aspiration mode, and during scleral compression. The measurements were performed with the IOP control setting turned on or off. Using the 23-gauge system with the IOP control setting turned on, IOP decreased from 30 to 23.7 mm Hg after starting vitreous cutting, and then returned to 30 mm Hg in 2.6 seconds. When the IOP control setting was turned off, IOP decreased to 19.1 mm Hg in 0.9 seconds, and remained at that pressure. Under aspiration at 650 mm Hg without cutting, IOP showed a sharp depression from 30 to 12.2 mm Hg, and then returned to 30.6 mm Hg in 2.6 seconds with the IOP control setting turned on. When the IOP control setting was turned off, IOP decreased to 2.2 mm Hg in 9.7 seconds, and did not recover. When the sclera was compressed without aspiration, IOP rapidly increased to 70-100 mm Hg, and then slowly decreased to 30 mm Hg in 3.5-4.0 seconds, with or without the IOP control system. Similar data were obtained with 25-gauge vitrectomy. The IOP control system can attenuate IOP fluctuations during vitrectomy maneuvers. There was no significant difference in IOP fluctuations between 23- and 25-gauge systems. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. The analysis of measurement accuracy of the parallel binocular stereo vision system

    Science.gov (United States)

    Yu, Huan; Xing, Tingwen; Jia, Xin

    2016-09-01

    Parallel binocular stereo vision system is a special form of binocular vision system. In order to simulate the human eyes observation state, the two cameras used to obtain images of the target scene are placed parallel to each other. This paper built a triangular geometric model, analyzed the structure parameters of parallel binocular stereo vision system and the correlations between them, and discussed the influences of baseline distance B between two cameras, the focal length f, the angle of view ω and other structural parameters on the accuracy of measurement. This paper used Matlab software to test the error function of parallel binocular stereo vision system under different structure parameters, and the simulation results showed the range of structure parameters when errors were small, thereby improved the accuracy of parallel binocular stereo vision system.

  5. Design of illumination systems for vision-assisted placement of surface-mount components

    Science.gov (United States)

    Cheraghi, S. H.; Lehtihet, E. A.; Egbelu, Pius J.

    1994-03-01

    One of the major parts of any vision system design is the development of effective illumination techniques. For high accuracy applications one can not afford to ignore an obvious source of error, namely a poor lighting system. In electronic manufacturing, accurate placement of fine pitch surface-mount components (SMCs) requires the integration of a vision system with the placement system. This paper describes the design of very effective lighting techniques for a vision-assisted system to place surface-mount components. The lighting systems provide consistent images of SMCs and pads with high contrast.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. An automatic 3D reconstruction system based on binocular vision measurement

    Science.gov (United States)

    Liu, Shuangyin; Wang, Zhenwei; Fan, Fang

    2017-10-01

    With the rapid development of computer vision, vision measurement and 3D reconstruction have become a hot research trend. However, it is still a problem to reconstruct the weak texture surface in engineering. In this paper, we present the systematic design and implementation of an automatic measurement system based on binocular vision. The hardware configuration of the verification platform is presented, including CCD cameras, stepper motors, laser displacement sensors and so on. Binocular-vision algorithms including camera calibration, feature extraction, stereo match and 3D reconstruction are prompted to reconstruct the weak texture surface. An experiment demonstrates the effectiveness and feasibility of this platform.

  11. Binocular stereo vision system based on phase matching

    Science.gov (United States)

    Liu, Huixian; Huang, Shujun; Gao, Nan; Zhang, Zonghua

    2016-11-01

    Binocular stereo vision is an efficient way for three dimensional (3D) profile measurement and has broad applications. Image acquisition, camera calibration, stereo matching, and 3D reconstruction are four main steps. Among them, stereo matching is the most important step that has a significant impact on the final result. In this paper, a new stereo matching technique is proposed to combine the absolute fringe order and the unwrapped phase of every pixel. Different from traditional phase matching method, sinusoidal fringe in two perpendicular directions are projected. It can be realized through the following three steps. Firstly, colored sinusoidal fringe in both horizontal (red fringe) and vertical (blue fringe) are projected on the object to be measured, and captured by two cameras synchronously. The absolute fringe order and the unwrapped phase of each pixel along the two directions are calculated based on the optimum three-fringe numbers selection method. Then, based on the absolute fringe order of the left and right phase maps, stereo matching method is presented. In this process, the same absolute fringe orders in both horizontal and vertical directions are searched to find the corresponding point. Based on this technique, as many as possible pairs of homologous points between two cameras are found to improve the precision of the measurement result. Finally, a 3D measuring system is set up and the 3D reconstruction results are shown. The experimental results show that the proposed method can meet the requirements of high precision for industrial measurements.

  12. Computer Vision Malaria Diagnostic Systems-Progress and Prospects.

    Science.gov (United States)

    Pollak, Joseph Joel; Houri-Yafin, Arnon; Salpeter, Seth J

    2017-01-01

    Accurate malaria diagnosis is critical to prevent malaria fatalities, curb overuse of antimalarial drugs, and promote appropriate management of other causes of fever. While several diagnostic tests exist, the need for a rapid and highly accurate malaria assay remains. Microscopy and rapid diagnostic tests are the main diagnostic modalities available, yet they can demonstrate poor performance and accuracy. Automated microscopy platforms have the potential to significantly improve and standardize malaria diagnosis. Based on image recognition and machine learning algorithms, these systems maintain the benefits of light microscopy and provide improvements such as quicker scanning time, greater scanning area, and increased consistency brought by automation. While these applications have been in development for over a decade, recently several commercial platforms have emerged. In this review, we discuss the most advanced computer vision malaria diagnostic technologies and investigate several of their features which are central to field use. Additionally, we discuss the technological and policy barriers to implementing these technologies in low-resource settings world-wide.

  13. Honey characterization using computer vision system and artificial neural networks.

    Science.gov (United States)

    Shafiee, Sahameh; Minaei, Saeid; Moghaddam-Charkari, Nasrollah; Barzegar, Mohsen

    2014-09-15

    This paper reports the development of a computer vision system (CVS) for non-destructive characterization of honey based on colour and its correlated chemical attributes including ash content (AC), antioxidant activity (AA), and total phenolic content (TPC). Artificial neural network (ANN) models were applied to transform RGB values of images to CIE L*a*b* colourimetric measurements and to predict AC, TPC and AA from colour features of images. The developed ANN models were able to convert RGB values to CIE L*a*b* colourimetric parameters with low generalization error of 1.01±0.99. In addition, the developed models for prediction of AC, TPC and AA showed high performance based on colour parameters of honey images, as the R(2) values for prediction were 0.99, 0.98, and 0.87, for AC, AA and TPC, respectively. The experimental results show the effectiveness and possibility of applying CVS for non-destructive honey characterization by the industry. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Development of image processing LSI "SuperVchip" for real-time vision systems

    Science.gov (United States)

    Muramatsu, Shoji; Kobayashi, Yoshiki; Otsuka, Yasuo; Shojima, Hiroshi; Tsutsumi, Takayuki; Imai, Toshihiko; Yamada, Shigeyoshi

    2002-03-01

    A new image processing LSI SuperVchip with high-performance computing power has been developed. The SuperVchip has powerful capability for vision systems as follows: 1. General image processing by 3x3, 5x5, 7x7 kernel for high speed filtering function. 2. 16-parallel gray search engine units for robust template matching. 3. 49 block matching Pes to calculate the summation of the absolution difference in parallel for stereo vision function. 4. A color extraction unit for color object recognition. The SuperVchip also has peripheral function of vision systems, such as video interface, PCI extended interface, RISC engine interface and image memory controller on a chip. Therefore, small and high performance vision systems are realized via SuperVchip. In this paper, the above specific circuits are presented, and an architecture of a vision device equipped with SuperVchip and its performance are also described.

  15. 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

  16. 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.

  17. Target detect system in 3D using vision apply on plant reproduction by tissue culture

    Science.gov (United States)

    Vazquez Rueda, Martin G.; Hahn, Federico

    2001-03-01

    This paper presents the preliminary results for a system in tree dimension that use a system vision to manipulate plants in a tissue culture process. The system is able to estimate the position of the plant in the work area, first calculate the position and send information to the mechanical system, and recalculate the position again, and if it is necessary, repositioning the mechanical system, using an neural system to improve the location of the plant. The system use only the system vision to sense the position and control loop using a neural system to detect the target and positioning the mechanical system, the results are compared with an open loop system.

  18. 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......, a multithreshold legmentation algorithm is applied in a stereo-vision running at 150Hz. Based on the estimated 3D ball positions, a novel two-phase trajectory prediction is exploited to determine the hitting position. Benefiting from the high-speed visual feedback, the hitting position and thus the motion planning...... 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%....

  19. 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.

  20. Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

    OpenAIRE

    Marichal, N.; Tomas-Rodriguez, M.; Hernandez, A.; Castillo, S; Campoy, P.

    2014-01-01

    In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrime...

  1. Image/video understanding systems based on network-symbolic models and active vision

    Science.gov (United States)

    Kuvich, Gary

    2004-07-01

    Vision is a part of information system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. It is hard to split the entire system apart, and vision mechanisms cannot be completely understood separately from informational processes related to knowledge and intelligence. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Vision is a component of situation awareness, motion and planning systems. Foveal vision provides semantic analysis, recognizing objects in the scene. Peripheral vision guides fovea to salient objects and provides scene context. Biologically inspired Network-Symbolic representation, in which both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, converts visual information into relational Network-Symbolic structures, avoiding precise artificial computations of 3-D models. Network-Symbolic transformations derive more abstract structures that allows for invariant recognition of an object as exemplar of a class and for a reliable identification even if the object is occluded. Systems with such smart vision will be able to navigate in real environment and understand real-world situations.

  2. A Knowledge-Intensive Approach to Computer Vision Systems

    NARCIS (Netherlands)

    Koenderink-Ketelaars, N.J.J.P.

    2010-01-01

    This thesis focusses on the modelling of knowledge-intensive computer vision tasks. Knowledge-intensive tasks are tasks that require a high level of expert knowledge to be performed successfully. Such tasks are generally performed by a task expert. Task experts have a lot of experience in performing

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

    African Journals Online (AJOL)

    Our problem is a diagnostic task. Due to environment degraded conditions, direct measurements are not possible. Due to the rapidity of the machine, human intervention is not possible in case of position fault. So, an oriented vision solution is proposed. The problem must be solved for high velocity industrial tooling ...

  4. Atmospheric Characterization During Super-Resolution Vision System Developmental Testing

    Science.gov (United States)

    2013-05-01

    5 vii viii INTENTIONALLY LEFT BLANK. 1. Introduction Optical turbulence effects...imagery and baseline collection of non-corrected imagery. 36 8. References Goodman , J. W. Statistical Optics , J. Wiley & Sons, New York, NY, 1985...Electro- Optical Vulnerability Assessment Facility FFT Fast Fourier Transform NVESD Night Vision and Electro- Optical Sensors Directorate SLAD

  5. 3D morphology reconstruction using linear array CCD binocular stereo vision imaging system

    Science.gov (United States)

    Pan, Yu; Wang, Jinjiang

    2018-01-01

    Binocular vision imaging system, which has a small field of view, cannot reconstruct the 3-D shape of the dynamic object. We found a linear array CCD binocular vision imaging system, which uses different calibration and reconstruct methods. On the basis of the binocular vision imaging system, the linear array CCD binocular vision imaging systems which has a wider field of view can reconstruct the 3-D morphology of objects in continuous motion, and the results are accurate. This research mainly introduces the composition and principle of linear array CCD binocular vision imaging system, including the calibration, capture, matching and reconstruction of the imaging system. The system consists of two linear array cameras which were placed in special arrangements and a horizontal moving platform that can pick up objects. The internal and external parameters of the camera are obtained by calibrating in advance. And then using the camera to capture images of moving objects, the results are then matched and 3-D reconstructed. The linear array CCD binocular vision imaging systems can accurately measure the 3-D appearance of moving objects, this essay is of great significance to measure the 3-D morphology of moving objects.

  6. Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

    Science.gov (United States)

    Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

    2017-05-01

    Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

  7. Time comparison in image processing: APS sensors versus an artificial retina based vision system

    Science.gov (United States)

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

    2007-09-01

    To resolve the computational complexity of computer vision algorithms, one of the solutions is to perform some low-level image processing on the sensor focal plane. It becomes a smart sensor device called a retina. This concept makes vision systems more compact. It increases performance thanks to the reduction of the data flow exchanges with external circuits. This paper presents a comparison between two different vision system architectures. The first one involves a smart sensor including analogue processors allowing on-chip image processing. An external microprocessor is used to control the on-chip dataflow and integrated operators. The second system implements a logarithmic CMOS/APS sensor interfaced to the same microprocessor, in which all computations are carried out. We have designed two vision systems as proof of concept. The comparison is related to image processing time.

  8. Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

    Science.gov (United States)

    Knight, James C.; Tully, Philip J.; Kaplan, Bernhard A.; Lansner, Anders; Furber, Steve B.

    2016-01-01

    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 2.0 × 104 neurons and 5.1 × 107 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 45× 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. PMID:27092061

  9. 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.

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

    Science.gov (United States)

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

    2015-11-02

    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 stereo vision, which, combined with AR, could have significant clinical applications.

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

    OpenAIRE

    Zhenmin Zhu; Ruichao Song; Hui Luo; Jun Xu; Shiming Chen

    2016-01-01

    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 an...

  12. Intelligent Machine Vision System for Automated Quality Control in Ceramic Tiles Industry

    OpenAIRE

    KESER, Tomislav; HOCENSKI, Željko; HOCENSKI, Verica

    2010-01-01

    Intelligent system for automated visual quality control of ceramic tiles based on machine vision is presented in this paper. The ceramic tiles production process is almost fully and well automated in almost all production stages with exception of quality control stage at the end. The ceramic tiles quality is checked by using visual quality control principles where main goal is to successfully replace man as part of production chain with an automated machine vision system to ...

  13. Fuzzy Petri nets to model vision system decisions within a flexible manufacturing system

    Science.gov (United States)

    Hanna, Moheb M.; Buck, A. A.; Smith, R.

    1994-10-01

    The paper presents a Petri net approach to modelling, monitoring and control of the behavior of an FMS cell. The FMS cell described comprises a pick and place robot, vision system, CNC-milling machine and 3 conveyors. The work illustrates how the block diagrams in a hierarchical structure can be used to describe events at different levels of abstraction. It focuses on Fuzzy Petri nets (Fuzzy logic with Petri nets) including an artificial neural network (Fuzzy Neural Petri nets) to model and control vision system decisions and robot sequences within an FMS cell. This methodology can be used as a graphical modelling tool to monitor and control the imprecise, vague and uncertain situations, and determine the quality of the output product of an FMS cell.

  14. GSFC Information Systems Technology Developments Supporting the Vision for Space Exploration

    Science.gov (United States)

    Hughes, Peter; Dennehy, Cornelius; Mosier, Gary; Smith, Dan; Rykowski, Lisa

    2004-01-01

    The Vision for Space Exploration will guide NASA's future human and robotic space activities. The broad range of human and robotic missions now being planned will require the development of new system-level capabilities enabled by emerging new technologies. Goddard Space Flight Center is actively supporting the Vision for Space Exploration in a number of program management, engineering and technology areas. This paper provides a brief background on the Vision for Space Exploration and a general overview of potential key Goddard contributions. In particular, this paper focuses on describing relevant GSFC information systems capabilities in architecture development; interoperable command, control and communications; and other applied information systems technology/research activities that are applicable to support the Vision for Space Exploration goals. Current GSFC development efforts and task activities are presented together with future plans.

  15. 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.

  16. Aircraft exterior scratch measurement system using machine vision

    Science.gov (United States)

    Sarr, Dennis P.

    1991-08-01

    In assuring the quality of aircraft skin, it must be free of surface imperfections and structural defects. Manual inspection methods involve mechanical and optical technologies. Machine vision instrumentation can be automated for increasing the inspection rate and repeatability of measurement. As shown by previous industry experience, machine vision instrumentation methods are not calibrated and certified as easily as mechanical devices. The defect must be accurately measured and documented via a printout for engineering evaluation and disposition. In the actual usage of the instrument for inspection, the device must be portable for factory usage, on the flight line, or on an aircraft anywhere in the world. The instrumentation must be inexpensive and operable by a mechanic/technician level of training. The instrument design requirements are extensive, requiring a multidisciplinary approach for the research and development. This paper presents the image analysis results of microscopic structures laser images of scratches on various surfaces. Also discussed are the hardware and algorithms used for the microscopic structures laser images. Dedicated hardware and embedded software for implementing the image acquisition and analysis have been developed. The human interface, human vision is used for determining which image should be processed. Once the image is chosen for analysis, the final answer is a numerical value of the scratch depth. The result is an answer that is reliable and repeatable. The prototype has been built and demonstrated to Boeing Commercial Airplanes Group factory Quality Assurance and flight test management with favorable response.

  17. 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

  18. 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.

  19. 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%.

  20. Thermal Expansion and Aging Effects in Neuromorphic Signal Processor

    NARCIS (Netherlands)

    Zjajo, A.; van Leuken, T.G.R.M.

    2016-01-01

    In this paper, we propose an efficient methodology based on a real-time estimator and predictor-corrector scheme for accurate thermal expansion profile and aging evaluation of a neuromorphic signal processor circuit components. As the experimental results indicate, for comparable mesh size, the

  1. Functional vision and cognition in infants with congenital disorders of the peripheral visual system.

    Science.gov (United States)

    Dale, Naomi; Sakkalou, Elena; O'Reilly, Michelle; Springall, Clare; De Haan, Michelle; Salt, Alison

    2017-07-01

    To investigate how vision relates to early development by studying vision and cognition in a national cohort of 1-year-old infants with congenital disorders of the peripheral visual system and visual impairment. This was a cross-sectional observational investigation of a nationally recruited cohort of infants with 'simple' and 'complex' congenital disorders of the peripheral visual system. Entry age was 8 to 16 months. Vision level (Near Detection Scale) and non-verbal cognition (sensorimotor understanding, Reynell Zinkin Scales) were assessed. Parents completed demographic questionnaires. Of 90 infants (49 males, 41 females; mean 13mo, standard deviation [SD] 2.5mo; range 7-17mo); 25 (28%) had profound visual impairment (light perception at best) and 65 (72%) had severe visual impairment (basic 'form' vision). The Near Detection Scale correlated significantly with sensorimotor understanding developmental quotients in the 'total', 'simple', and 'complex' groups (all pvisual impairment, especially in the 'complex' group with congenital disorders of the peripheral visual system with known brain involvement, showed the greatest cognitive delay. Lack of vision is associated with delayed early-object manipulative abilities and concepts; 'form' vision appeared to support early developmental advance. This paper provides baseline characteristics for cross-sectional and longitudinal follow-up investigations in progress. A methodological strength of the study was the representativeness of the cohort according to national epidemiological and population census data. © 2017 Mac Keith Press.

  2. Homework system development with the intention of supporting Saudi Arabia's vision 2030

    Science.gov (United States)

    Elgimari, Atifa; Alshahrani, Shafya; Al-shehri, Amal

    2017-10-01

    This paper suggests a web-based homework system. The suggested homework system can serve targeted students with ages of 7-11 years old. By using the suggested homework system, hard copies of homeworks were replaced by soft copies. Parents were involved in the education process electronically. It is expected to participate in applying Saudi Arabia's Vision 2030, specially in the education sector, where it considers the primary education is its foundation stone, as the success of the Vision depends in large assess on reforms in the education system generating a better basis for employment of young Saudis.

  3. Improving Vision-Based Motor Rehabilitation Interactive Systems for Users with Disabilities Using Mirror Feedback

    Directory of Open Access Journals (Sweden)

    Antoni Jaume-i-Capó

    2014-01-01

    Full Text Available Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror with two different groups of users (8 with disabilities and 32 without disabilities using usability measures (time-to-start (Ts and time-to-complete (Tc. A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user’s own visual feedback (Ts=7.09 (P<0.001 and Tc=4.48 (P<0.005. In vision-based interaction systems, the input device is the user’s own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems.

  4. 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

  5. The Glenn A. Fry Award Lecture 2012: Plasticity of the visual system following central vision loss.

    Science.gov (United States)

    Chung, Susana T L

    2013-06-01

    Following the onset of central vision loss, most patients develop an eccentric retinal location outside the affected macular region, the preferred retinal locus (PRL), as their new reference for visual tasks. The first goal of this article is to present behavioral evidence showing the presence of experience-dependent plasticity in people with central vision loss. The evidence includes the presence of oculomotor re-referencing of fixational saccades to the PRL; the characteristics of the shape of the crowding zone (spatial region within which the presence of other objects affects the recognition of a target) at the PRL are more "foveal-like" instead of resembling those of the normal periphery; and the change in the shape of the crowding zone at a para-PRL location that includes a component referenced to the PRL. These findings suggest that there is a shift in the referencing locus of the oculomotor and the sensory visual system from the fovea to the PRL for people with central vision loss, implying that the visual system for these individuals is still plastic and can be modified through experiences. The second goal of the article is to demonstrate the feasibility of applying perceptual learning, which capitalizes on the presence of plasticity, as a tool to improve functional vision for people with central vision loss. Our finding that visual function could improve with perceptual learning presents an exciting possibility for the development of an alternative rehabilitative strategy for people with central vision loss.

  6. 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...

  7. 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.

  8. A computer vision system for the recognition of trees in aerial photographs

    Science.gov (United States)

    Pinz, Axel J.

    1991-01-01

    Increasing problems of forest damage in Central Europe set the demand for an appropriate forest damage assessment tool. The Vision Expert System (VES) is presented which is capable of finding trees in color infrared aerial photographs. Concept and architecture of VES are discussed briefly. The system is applied to a multisource test data set. The processing of this multisource data set leads to a multiple interpretation result for one scene. An integration of these results will provide a better scene description by the vision system. This is achieved by an implementation of Steven's correlation algorithm.

  9. Monocular vision measurement system for the position and orientation of remote object

    Science.gov (United States)

    Zhou, Tao; Sun, Changku; Chen, Shan

    2008-03-01

    The high-precision measurement method for the position and orientation of remote object, is one of the hot issues in vision inspection, because it is very important in the field of aviation, precision measurement and so on. The position and orientation of the object at a distance of 5 m, can be measured by near infrared monocular vision based on vision measurement principle, using image feature extraction and data optimization. With the existent monocular vision methods and their features analyzed, a new monocular vision method is presented to get the position and orientation of target. In order to reduce the environmental light interference and make greater contrast between the target and background, near infrared light is used as light source. For realizing automatic camera calibration, a new feature-circle-based calibration drone is designed. A set of algorithms for image processing, proved to be efficient, are presented as well. The experiment results show that, the repeatability precision of angles is less than 8"; the repeatability precision of displacement is less than 0.02 mm. This monocular vision measurement method has been already used in wheel alignment system. It will have broader application field.

  10. Active vision and image/video understanding systems for UGV based on network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-09-01

    Vision evolved as a sensory system for reaching, grasping and other motion activities. In advanced creatures, it has become a vital component of situation awareness, navigation and planning systems. Vision is part of a larger information system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. It is hard to split such a system apart. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for natural processing of visual information. It converts visual information into relational Network-Symbolic models, avoiding artificial precise computations of 3-dimensional models. Logic of visual scenes can be captured in such models and used for disambiguation of visual information. Network-Symbolic transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps create unambiguous network-symbolic models. This approach is consistent with NIST RCS. The UGV, equipped with such smart vision, will be able to plan path and navigate in a real environment, perceive and understand complex real-world situations and act accordingly.

  11. 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°.

  12. Flight Testing of Night Vision Systems in Rotorcraft (Test en vol de systemes de vision nocturne a bord des aeronefs a voilure tournante)

    Science.gov (United States)

    2007-07-01

    AGARDographe se limite au test des dispositifs de vision nocturne à amplification de lumière. Il ne traite pas des autres systèmes : imagerie thermique ...complexity of the flight tasks can increase to represent more realistic or operational flight tasks. Another reason for the gradual ( staged ) approach to...using the intended aircraft control systems. 5.1.4.8 Workload or Pilot Compensation In the planning stages of a goggle evaluation, the concept of pilot

  13. Computer vision

    Science.gov (United States)

    Gennery, D.; Cunningham, R.; Saund, E.; High, J.; Ruoff, C.

    1981-01-01

    The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed. The representation of such features as texture, edges, curves, and corners are detailed. Recognition methods are described in which cross correlation coefficients are maximized or numerical values for a set of features are measured. Object tracking is discussed in terms of the robust matching algorithms that must be devised. Stereo vision, camera control and calibration, and the hardware and systems architecture are discussed.

  14. 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.

  15. 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.

  16. Memristive and neuromorphic behavior in a Li(x)CoO2 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

    2015-01-14

    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 Li(x)CoO2 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.

  17. On-demand nanodevice with electrical and neuromorphic multifunction realized by local ion migration.

    Science.gov (United States)

    Yang, Rui; Terabe, Kazuya; Liu, Guangqiang; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K; Aono, Masakazu

    2012-11-27

    A potential route to extend Moore's law beyond the physical limits of existing materials and device architectures is to achieve nanotechnology breakthroughs in materials and device concepts. Here, we discuss an on-demand WO(3-x)-based nanoionic device where electrical and neuromorphic multifunctions are realized through externally induced local migration of oxygen ions. The device is found to possess a wide range of time scales of memorization, resistance switching, and rectification varying from volatile to permanent in a single device, and these can furthermore be realizable in both two- or three-terminal systems. The gradually changing volatile and nonvolatile resistance states are experimentally demonstrated to mimic the human brain's forgetting process for short-term memory and long-term memory.We propose this nanoionic device with its on-demand electrical and neuromorphic multifunction has a unique paradigm shifting potential for the fabrication of configurable circuits, analog memories, digital-neural fused networks, and more in one device architecture.

  18. DEVELOPMENT OF NEUROMORPHIC SIFT OPERATOR WITH APPLICATION TO HIGH SPEED IMAGE MATCHING

    Directory of Open Access Journals (Sweden)

    M. Shankayi

    2015-12-01

    Full Text Available 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.

  19. 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.

  20. A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

    Energy Technology Data Exchange (ETDEWEB)

    Potok, Thomas E [ORNL; Schuman, Catherine D [ORNL; Young, Steven R [ORNL; Patton, Robert M [ORNL; Spedalieri, Federico [University of Southern California, Information Sciences Institute; Liu, Jeremy [University of Southern California, Information Sciences Institute; Yao, Ke-Thia [University of Southern California, Information Sciences Institute; Rose, Garrett [University of Tennessee (UT); Chakma, Gangotree [University of Tennessee (UT)

    2016-01-01

    Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determine network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation. The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware. This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.

  1. Prediction of pork color attributes using computer vision system.

    Science.gov (United States)

    Sun, Xin; Young, Jennifer; Liu, Jeng Hung; Bachmeier, Laura; Somers, Rose Marie; Chen, Kun Jie; Newman, David

    2016-03-01

    Color image processing and regression methods were utilized to evaluate color score of pork center cut loin samples. One hundred loin samples of subjective color scores 1 to 5 (NPB, 2011; n=20 for each color score) were selected to determine correlation values between Minolta colorimeter measurements and image processing features. Eighteen image color features were extracted from three different RGB (red, green, blue) model, HSI (hue, saturation, intensity) and L*a*b* color spaces. When comparing Minolta colorimeter values with those obtained from image processing, correlations were significant (P<0.0001) for L* (0.91), a* (0.80), and b* (0.66). Two comparable regression models (linear and stepwise) were used to evaluate prediction results of pork color attributes. The proposed linear regression model had a coefficient of determination (R(2)) of 0.83 compared to the stepwise regression results (R(2)=0.70). These results indicate that computer vision methods have potential to be used as a tool in predicting pork color attributes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. Image enhancement on the INVIS integrated night vision surveillance and observation system

    NARCIS (Netherlands)

    Dijk, J.; Schutte, K.; Toet, A.; Hogervorst, M.A.

    2010-01-01

    We present the design and first field trial results of the INVIS integrated night vision surveillance and observation system, in particular for the image enhancement techniques implemented. The INVIS is an all-day-andnight all-weather navigation and surveillance tool, combining three-band cameras.

  13. 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.

  14. 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...

  15. Monitoring of the thermal deformations on polymer parts using a vision system

    DEFF Research Database (Denmark)

    Dalla Costa, Giuseppe; Madruga, Daniel González; De Chiffre, Leonardo

    2017-01-01

    must be monitored and the measurements compensated. In this investigation thermal deformations on polymer parts are monitored using a vision system consisting of a camera equipped with telecentriclenses focused on the surface of the part. The magnification of the optics and an axial illumination allow...

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Low Vision

    Science.gov (United States)

    ... USAJobs Home > Statistics and Data > Low Vision Low Vision Low Vision Defined: Low Vision is defined as the best- ... 2010 U.S. Age-Specific Prevalence Rates for Low Vision by Age, and Race/Ethnicity Table for 2010 ...

  1. Street Viewer: An Autonomous Vision Based Traffic Tracking System

    Directory of Open Access Journals (Sweden)

    Andrea Bottino

    2016-06-01

    Full Text Available The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.

  2. Industrial applications of a vision system for undersea robots

    Science.gov (United States)

    Turner, John

    1993-12-01

    The Offshore Oil and Gas Industry in the North Sea has many requirements for 3D measurements in air and underwater. A market audit found that the use of film based photogrammetry was being rejected for many applications because the information was not available fast enough. A development project was set up to replace the photographic cameras with a choice of video of high resolution digital electronic cameras, and the analysis system with a personal computer based image processing system. This product has been in operation with Remotely Controlled Underwater Vehicles since September 1992. The paper deals with the ongoing development of the system, including the automation of the measurement process. It introduces the application of the system as a closed-loop control system for underwater manipulators.

  3. 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.

  4. Automatic behaviour analysis system for honeybees using computer vision

    DEFF Research Database (Denmark)

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

    2016-01-01

    -cost embedded computer with very limited computational resources as compared to an ordinary PC. The system succeeds in counting honeybees, identifying their position and measuring their in-and-out activity. Our algorithm uses background subtraction method to segment the images. After the segmentation stage...... demonstrate that this system can be used as a tool to detect the behaviour of honeybees and assess their state in the beehive entrance. Besides, the result of the computation time show that the Raspberry Pi is a viable solution in such real-time video processing system....

  5. Omnidirectional vision systems calibration, feature extraction and 3D information

    CERN Document Server

    Puig, Luis

    2013-01-01

    This work focuses on central catadioptric systems, from the early step of calibration to high-level tasks such as 3D information retrieval. The book opens with a thorough introduction to the sphere camera model, along with an analysis of the relation between this model and actual central catadioptric systems. Then, a new approach to calibrate any single-viewpoint catadioptric camera is described.  This is followed by an analysis of existing methods for calibrating central omnivision systems, and a detailed examination of hybrid two-view relations that combine images acquired with uncalibrated

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    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......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...

  7. 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

  8. Vision System of Mobile Robot Combining Binocular and Depth Cameras

    National Research Council Canada - National Science Library

    Yuxiang Yang; Xiang Meng; Mingyu Gao

    2017-01-01

    In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper...

  9. Error Characterization of Vision-Aided Navigation Systems

    Science.gov (United States)

    2013-03-01

    iv EKF Extended Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . . . iv GNSS Global Navigation Satellite System...Satellite Systems ( GNSS ), of which GPS is an example, suffer from availability restrictions when satellite signals are physically blocked in areas...location [0,0] or [1,1]. The second option will be used within this work to adhere to the indexing conventions found in MATLAB R©. 2.3 Coordinate

  10. CLOUD COMPUTING: A NEW VISION OF THE DISTRIBUTED SYSTEM

    OpenAIRE

    Taha Chaabouni1; Maher Khemakhem

    2012-01-01

    Cloud computing is a new emerging system which offers information technologies via Internet. Clients use services they need when they need and at the place they want and pay only for what they have consumed. So, cloud computing offers many advantages especially for business. A deep study and understanding of this emerging system and the inherent components help a lot in identifying what should we do in order to improve its performance. In this work, we present first cloud compu...

  11. Vision System of Mobile Robot Combining Binocular and Depth Cameras

    Directory of Open Access Journals (Sweden)

    Yuxiang Yang

    2017-01-01

    Full Text Available In order to optimize the three-dimensional (3D reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning.

  12. 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.

  13. Remote sensing of physiological signs using a machine vision system.

    Science.gov (United States)

    Al-Naji, Ali; Gibson, Kim; Chahl, Javaan

    2017-07-01

    The aim of this work is to remotely measure heart rate (HR) and respiratory rate (RR) using a video camera from long range (> 50 m). The proposed system is based on imperceptible signals produced from blood circulation, including skin colour variations and head motion. As these signals are not visible to the naked eye and to preserve the signal strength in the video, we used an improved video magnification technique to enhance these invisible signals and detect the physiological activity within the subject. The software of the proposed system was built in a graphic user interface (GUI) environment to easily select a magnification system to use (colour or motion magnification) and measure the physiological signs independently. The measurements were performed on a set of 10 healthy subjects equipped with a finger pulse oximeter and respiratory belt transducer that were used as reference methods. The experimental results were statistically analysed by using the Bland-Altman method, Pearson's correlation coefficient, Spearman correlation coefficient, mean absolute error, and root mean squared error. The proposed system achieved high correlation even in the presence of movement artefacts, different skin tones, lighting conditions and distance from the camera. With acceptable performance and low computational complexity, the proposed system is a suitable candidate for homecare applications, security applications and mobile health devices.

  14. A monocular vision system based on cooperative targets detection for aircraft pose measurement

    Science.gov (United States)

    Wang, Zhenyu; Wang, Yanyun; Cheng, Wei; Chen, Tao; Zhou, Hui

    2017-08-01

    In this paper, a monocular vision measurement system based on cooperative targets detection is proposed, which can capture the three-dimensional information of objects by recognizing the checkerboard target and calculating of the feature points. The aircraft pose measurement is an important problem for aircraft’s monitoring and control. Monocular vision system has a good performance in the range of meter. This paper proposes an algorithm based on coplanar rectangular feature to determine the unique solution of distance and angle. A continuous frame detection method is presented to solve the problem of corners’ transition caused by symmetry of the targets. Besides, a displacement table test system based on three-dimensional precision and measurement system human-computer interaction software has been built. Experiment result shows that it has a precision of 2mm in the range of 300mm to 1000mm, which can meet the requirement of the position measurement in the aircraft cabin.

  15. Research of vision measurement system of the instruction sheet caliper rack

    Science.gov (United States)

    Liu, Yu; Kong, Ming; Dong, Ying-jun

    2011-05-01

    This article proposes a method of rack measurement based on computer vision. It establishes a computer vision measurement system; the system consists of precision linear guide, camera, computer and other several parts. The entire system can be divided into displacement platform design system and image acquisition system two parts. The displacement platform system is that the linear guide campaigns driven by the driver controlled by the computer, to expand the scope of this measure realizing the measurement for the whole tooth. Image acquisition system is the use of computer vision technology to analysis and identification the capture images, the light source emitting light to the caliper rack, camerawork is to be the image which acquisitioned. Then input the images to the computer through the USB interface in order to the image analysis, such as Edge Detection, Feature Extraction and so on. And the detection accuracy reaches to sub-pixel level. Experiment with the rack modulus of 0.19894 instruction sheet calipers to measure, using image processing technology to realize the edge detection, and getting the edge of rack. Finally get the basic parameters of the rack such as p and s, and calculated individual circular pitch deviation fpt, total cumulative pitch deviation Fp, tooth thickness deviation fsn. Then comparison the measurement results with the Accretech S1910DX3. It turned out that the accuracy of this method can meet the requirements for the measurement of such rack. And the measurement method is simple and practical, providing technical support for the rack online testing.

  16. 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.

  17. Is A Magnetic Sensor Capable of Evaluating A Vision-Based Face Tracking System?

    OpenAIRE

    Yao, Zhengrong; Li, Haibo

    2003-01-01

    This paper addresses an important issue, how to evaluate a vision-based face tracking system? Although nowadays it is getting popular to employ a magnetic sensor to evaluate the performance of such systems. The related issues such as condition and limitation of usage are often omitted. In this paper we studied this accepted evaluation methodology together with another evaluation method, Peak Signal to Noise (PSNR) commonly used inimage coding community. The condition of proper usage of magnet...

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

    OpenAIRE

    Chia-Sui Wang; Ko-Chun Chen; Tsung Han Lee; Kuei-Shu Hsu

    2015-01-01

    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 rai...

  19. Vision Aided Inertial Navigation System Augmented with a Coded Aperture

    Science.gov (United States)

    2011-03-24

    21 Figure 2-4 Stereopsis Example...camera may be known precisely. Knowledge of this vector allows stereopsis techniques to be employed. With stereopsis , the angle from the focal point...for a MA V are accurate for significantly shorter time periods than those more commonly used for larger systems [9]. Aiding an INS using stereopsis

  20. 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%.

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. A Vision-Based Emergency Response System with a Paramedic Mobile Robot

    Science.gov (United States)

    Jeong, Il-Woong; Choi, Jin; Cho, Kyusung; Seo, Yong-Ho; Yang, Hyun Seung

    Detecting emergency situation is very important to a surveillance system for people like elderly live alone. A vision-based emergency response system with a paramedic mobile robot is presented in this paper. The proposed system is consisted of a vision-based emergency detection system and a mobile robot as a paramedic. A vision-based emergency detection system detects emergency by tracking people and detecting their actions from image sequences acquired by single surveillance camera. In order to recognize human actions, interest regions are segmented from the background using blob extraction method and tracked continuously using generic model. Then a MHI (Motion History Image) for a tracked person is constructed by silhouette information of region blobs and model actions. Emergency situation is finally detected by applying these information to neural network. When an emergency is detected, a mobile robot can help to diagnose the status of the person in the situation. To send the mobile robot to the proper position, we implement mobile robot navigation algorithm based on the distance between the person and a mobile robot. We validate our system by showing emergency detection rate and emergency response demonstration using the mobile robot.

  6. An Evaluation of the VISION Execution System Demonstration Prototypes

    Science.gov (United States)

    1991-01-01

    254731 ý-ELECTE "An valuation of the VISONExecution System Demonstration Prototypes Patricia M-. Boren, Karen E. Isaacson, Judith E. Payne , Marc...Isaacson, Judith E. Payne , Marc L. Robbins, Robert S. Tripp Prepared for the United States Army A co,".I, For RAND? Approved for. public relase...manuscript. Jeffrey Crisci and Cecilia Butler, formerly of the Army Materiel Command (AMC) and currently with the Strategic Logistics Agency (SLA), were

  7. Awareness and Detection of Traffic and Obstacles Using Synthetic and Enhanced Vision Systems

    Science.gov (United States)

    Bailey, Randall E.

    2012-01-01

    Research literature are reviewed and summarized to evaluate the awareness and detection of traffic and obstacles when using Synthetic Vision Systems (SVS) and Enhanced Vision Systems (EVS). The study identifies the critical issues influencing the time required, accuracy, and pilot workload associated with recognizing and reacting to potential collisions or conflicts with other aircraft, vehicles and obstructions during approach, landing, and surface operations. This work considers the effect of head-down display and head-up display implementations of SVS and EVS as well as the influence of single and dual pilot operations. The influences and strategies of adding traffic information and cockpit alerting with SVS and EVS were also included. Based on this review, a knowledge gap assessment was made with recommendations for ground and flight testing to fill these gaps and hence, promote the safe and effective implementation of SVS/EVS technologies for the Next Generation Air Transportation System

  8. Removal of noise and radial lens distortion during calibration of computer vision systems.

    Science.gov (United States)

    Wang, ZhenZhou

    2015-05-04

    The calibration of computer vision systems that contain the camera and the projector usually utilizes markers of the well-designed patterns to calculate the system parameters. Undesirably, the noise and radial distortion exist universally, which decreases the calibration accuracy and consequently decreases the measurement accuracy of the related technology. In this paper, a method is proposed to remove the noise and radial distortion by registering the captured pattern with an ideal pattern. After the optimal modeled pattern is obtained by registration, the degree of freedom of the total calibration markers is reduced to one and both the noise and radial distortion are removed successfully. The accuracy improvement in a structured light scanning system is over 10(24) order of magnitude in the sense of mean square errors. Most importantly, the proposed method can be readily adopted by the computer vision techniques that use projectors or cameras.

  9. The design and realization of a sort of robot vision measure system

    Science.gov (United States)

    Ren, Yong-jie; Zhu, Ji-gui; Yang, Xue-you; Ye, Sheng-hua

    2006-06-01

    The robot vision measure system based on stereovision is a very meaningful research realm within the engineering application. In this system, the industry robot is the movable carrier of the stereovision sensor, not only extending the work space of the sensor, but also reserving the characteristics of vision measure technology such as non-contact, quickness, etc. Controlling the pose of the robot in space, the stereovision sensor can arrive at the given point to collect the image signal of the given point one by one, and then obtain the 3D coordinate data after computing the image data. The method based on the technique of binocular stereovision sensor, which uses two transit instruments and one precision drone to carry out the whole calibration, is presented. At the same time, the measurement program of the robot and the computer was written in different program language. In the end, the system was tested carefully, and the feasibility was proved simultaneously.

  10. 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.

  11. 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.

  12. Multispectral uncooled infrared enhanced-vision system for flight test

    Science.gov (United States)

    Tiana, Carlo L.; Kerr, Richard; Harrah, Steven D.

    2001-08-01

    The 1997 Final Report of the 'White House Commission on Aviation Safety and Security' challenged industrial and government concerns to reduce aviation accident rates by a factor of five within 10 years. In the report, the commission encourages NASA, FAA and others 'to expand their cooperative efforts in aviation safety research and development'. As a result of this publication, NASA has since undertaken a number of initiatives aimed at meeting the stated goal. Among these, the NASA Aviation Safety Program was initiated to encourage and assist in the development of technologies for the improvement of aviation safety. Among the technologies being considered are certain sensor technologies that may enable commercial and general aviation pilots to 'see to land' at night or in poor visibility conditions. Infrared sensors have potential applicability in this field, and this paper describes a system, based on such sensors, that is being deployed on the NASA Langley Research Center B757 ARIES research aircraft. The system includes two infrared sensors operating in different spectral bands, and a visible-band color CCD camera for documentation purposes. The sensors are mounted in an aerodynamic package in a forward position on the underside of the aircraft. Support equipment in the aircraft cabin collects and processes all relevant sensor data. Display of sensor images is achieved in real time on the aircraft's Head Up Display (HUD), or other display devices.

  13. The VirtualwindoW: A Reconfigurable, Modular, Stereo Vision System

    Energy Technology Data Exchange (ETDEWEB)

    M. D. McKay; M. O. Anderson; R. A. Kinoshita; W. D. Willis

    1999-02-01

    An important need while using unmanned vehicles is the ability for the remote operator or observer to easily and accurately perceive the operating environment. A classic problem in providing a complete representation of the remote work area is sensory overload or excessive complexity in the human-machine interface. In addition, remote operations often benefit from depth perception capability while viewing or manipulating objects. Thus, there is an ongoing effort within the remote and teleoperated robotic field to develop better human-machine interfaces. The Department of Energy's Idaho National Engineering and Environmental Laboratory (INEEL) has been researching methods to simplify the human-machine interface using atypical operator techniques. Initial telepresence research conducted at the INEEL developed and implemented a concept called the VirtualwindoW. This system minimized the complexity of remote stereo viewing controls and provided the operator the ''feel'' of viewing the environment, including depth perception, in a natural setting. The VirtualwindoW has shown that the human-machine interface can be simplified while increasing operator performance. This paper deals with the continuing research and development of the VirtualwindoW to provide a reconfigurable, modular system that easily utilizes commercially available off the shelf components. This adaptability is well suited to several aspects of unmanned vehicle applications, most notably environmental perception and vehicle control.

  14. The VirtualwindoW: A Reconfigurable, Modular, Stereo Vision System

    Energy Technology Data Exchange (ETDEWEB)

    Kinoshita, Robert Arthur; Anderson, Matthew Oley; Mckay, Mark D; Willis, Walter David

    1999-04-01

    An important need while using unmanned vehicles is the ability for the remote operator or observer to easily and accurately perceive the operating environment. A classic problem in providing a complete representation of the remote work area is sensory overload or excessive complexity in the human-machine interface. In addition, remote operations often benefit from depth perception capability while viewing or manipulating objects. Thus, there is an on going effort within the remote and teleoperated robotic field to develop better human-machine interfaces. The Department of Energy's Idaho National Engineering and Environmental Laboratory (INEEL) has been researching methods to simplify the human-machine interface using atypical operator techniques. Initial telepresence research conducted at the INEEL developed and implemented a concept called the VirtualwindoW. This system minimized the complexity of remote stereo viewing controls and provided the operator the "feel" of viewing the environment, including depth perception, in a natural setting. The VirtualwindoW has shown that the human-machine interface can be simplified while increasing operator performance. This paper deals with the continuing research and development of the VirtualwindoW to provide a reconfigurable, modular system that easily utilizes commercially available off the shelf components. This adaptability is well suited to several aspects of unmanned vehicle applications, most notably environmental perception and vehicle control.

  15. Ranging Apparatus and Method Implementing Stereo Vision System

    Science.gov (United States)

    Li, Larry C. (Inventor); Cox, Brian J. (Inventor)

    1997-01-01

    A laser-directed ranging system for use in telerobotics applications and other applications involving physically handicapped individuals. The ranging system includes a left and right video camera mounted on a camera platform, and a remotely positioned operator. The position of the camera platform is controlled by three servo motors to orient the roll axis, pitch axis and yaw axis of the video cameras, based upon an operator input such as head motion. A laser is provided between the left and right video camera and is directed by the user to point to a target device. The images produced by the left and right video cameras are processed to eliminate all background images except for the spot created by the laser. This processing is performed by creating a digital image of the target prior to illumination by the laser, and then eliminating common pixels from the subsequent digital image which includes the laser spot. The horizontal disparity between the two processed images is calculated for use in a stereometric ranging analysis from which range is determined.

  16. 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.

  17. Computer graphics testbed to simulate and test vision systems for space applications

    Science.gov (United States)

    Cheatham, John B.; Wu, Chris K.; Lin, Y. H.

    1991-01-01

    A system was developed for displaying computer graphics images of space objects and the use of the system was demonstrated as a testbed for evaluating vision systems for space applications. In order to evaluate vision systems, it is desirable to be able to control all factors involved in creating the images used for processing by the vision system. Considerable time and expense is involved in building accurate physical models of space objects. Also, precise location of the model relative to the viewer and accurate location of the light source require additional effort. As part of this project, graphics models of space objects such as the Solarmax satellite are created that the user can control the light direction and the relative position of the object and the viewer. The work is also aimed at providing control of hue, shading, noise and shadows for use in demonstrating and testing imaging processing techniques. The simulated camera data can provide XYZ coordinates, pitch, yaw, and roll for the models. A physical model is also being used to provide comparison of camera images with the graphics images.

  18. 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.

  19. Robust algorithm for point matching in uncalibrated stereo vision systems

    Directory of Open Access Journals (Sweden)

    Marcelo Ricardo Stemmer

    2005-02-01

    Full Text Available This article introduces a new point matching algorithm for stereo images. The cameras used for capturing the image do not need to be calibrated. The only requirement is the existence of a set of segmented corners in each image. In order to execute the point matching, the algorithm starts by applying non-parametric techniques to the pair of images and a set of candidate matches is selected. After that, the reliability of each point is calculated based on a proposed equation. Finally, the fundamental matrix of the system is estimated and the epipolar restriction is used to eliminate outliers. Tests made on real images demonstrate the viability of the proposed method.

  20. 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.

  1. 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.

  2. Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study

    Directory of Open Access Journals (Sweden)

    Thomas Pfeil

    2016-05-01

    Full Text Available High-level brain function, such as memory, classification, or reasoning, can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy-efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear subthreshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with nonlinear, conductance-based synapses. Emulations of these networks on the analog neuromorphic-hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm that shared-input correlations are actively suppressed by inhibitory feedback also in highly heterogeneous networks exhibiting broad

  3. 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.

  4. Visual Advantage of Enhanced Flight Vision System During NextGen Flight Test Evaluation

    Science.gov (United States)

    Kramer, Lynda J.; Harrison, Stephanie J.; Bailey, Randall E.; Shelton, Kevin J.; Ellis, Kyle K.

    2014-01-01

    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. Simulation and flight tests were jointly sponsored by NASA's Aviation Safety Program, Vehicle Systems Safety Technology project and the Federal Aviation Administration (FAA) to evaluate potential safety and operational benefits of SVS/EFVS technologies in low visibility Next Generation Air Transportation System (NextGen) operations. The flight tests were conducted by a team of Honeywell, Gulfstream Aerospace Corporation and NASA personnel with the goal of obtaining pilot-in-the-loop test data for flight validation, verification, and demonstration of selected SVS/EFVS operational and system-level performance capabilities. Nine test flights were flown in Gulfstream's G450 flight test aircraft outfitted with the SVS/EFVS technologies under low visibility instrument meteorological conditions. Evaluation pilots flew 108 approaches in low visibility weather conditions (600 feet to 3600 feet reported visibility) under different obscurants (mist, fog, drizzle fog, frozen fog) and sky cover (broken, overcast). Flight test videos were evaluated at three different altitudes (decision altitude, 100 feet radar altitude, and touchdown) to determine the visual advantage afforded to the pilot using the EFVS/Forward-Looking InfraRed (FLIR) imagery compared to natural vision. Results indicate the EFVS provided a visual advantage of two to three times over that of the out-the-window (OTW) view. The EFVS allowed pilots to view the runway environment, specifically runway lights, before they would be able to OTW with natural vision.

  5. Implementation of the Canny Edge Detection algorithm for a stereo vision system

    Energy Technology Data Exchange (ETDEWEB)

    Wang, J.R.; Davis, T.A.; Lee, G.K. [North Carolina State Univ., Raleigh, NC (United States)

    1996-12-31

    There exists many applications in which three-dimensional information is necessary. For example, in manufacturing systems, parts inspection may require the extraction of three-dimensional information from two-dimensional images, through the use of a stereo vision system. In medical applications, one may wish to reconstruct a three-dimensional image of a human organ from two or more transducer images. An important component of three-dimensional reconstruction is edge detection, whereby an image boundary is separated from background, for further processing. In this paper, a modification of the Canny Edge Detection approach is suggested to extract an image from a cluttered background. The resulting cleaned image can then be sent to the image matching, interpolation and inverse perspective transformation blocks to reconstruct the 3-D scene. A brief discussion of the stereo vision system that has been developed at the Mars Mission Research Center (MMRC) is also presented. Results of a version of Canny Edge Detection algorithm show promise as an accurate edge extractor which may be used in the edge-pixel based binocular stereo vision system.

  6. 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.

  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. Position Control and Novel Application of SCARA Robot with Vision System

    Directory of Open Access Journals (Sweden)

    Hsiang-Chen Hsu

    2017-06-01

    Full Text Available In this paper, a SCARA robot arm with vision system has been developed to improve the accuracy of pick-and-place the surface mount device (SMD on PCB during surface mount process. Position of the SCARA robot can be controlled by using coordinate auto-compensation technique. Robotic movement and position control are auto-calculated based on forward and inverse kinematics with enhanced the intelligent image vision system. The determined x-y position and rotation angle can then be applied to the desired pick & place location for the SCARA robot. A series of experiments has been conducted to improve the accuracy of pick-and-place SMDs on PCB.

  9. Shadow and feature recognition aids for rapid image geo-registration in UAV vision system architectures

    Science.gov (United States)

    Baer, Wolfgang; Kölsch, Mathias

    2009-05-01

    The problem of real-time image geo-referencing is encountered in all vision based cognitive systems. In this paper we present a model-image feedback approach to this problem and show how it can be applied to image exploitation from Unmanned Arial Vehicle (UAV) vision systems. By calculating reference images from a known terrain database, using a novel ray trace algorithm, we are able to eliminate foreshortening, elevation, and lighting distortions, introduce registration aids and reduce the geo-referencing problem to a linear transformation search over the two dimensional image space. A method for shadow calculation that maintains real-time performance is also presented. The paper then discusses the implementation of our model-image feedback approach in the Perspective View Nascent Technology (PVNT) software package and provides sample results from UAV mission control and target mensuration experiments conducted at China Lake and Camp Roberts, California.

  10. 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.

  11. 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...... 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...

  12. Real-time and low-cost embedded platform for car's surrounding vision system

    Science.gov (United States)

    Saponara, Sergio; Franchi, Emilio

    2016-04-01

    The design and the implementation of a flexible and low-cost embedded system for real-time car's surrounding vision is presented. The target of the proposed multi-camera vision system is to provide the driver a better view of the objects that surround the vehicle. Fish-eye lenses are used to achieve a larger Field of View (FOV) but, on the other hand, introduce radial distortion of the images projected on the sensors. Using low-cost cameras there could be also some alignment issues. Since these complications are noticeable and dangerous, a real-time algorithm for their correction is presented. Then another real-time algorithm, used for merging 4 camera video streams together in a single view, is described. Real-time image processing is achieved through a hardware-software platform

  13. A novel registration method for image-guided neurosurgery system based on stereo vision.

    Science.gov (United States)

    An, Yong; Wang, Manning; Song, Zhijian

    2015-01-01

    This study presents a novel spatial registration method of Image-guided neurosurgery system (IGNS) based on stereo-vision. Images of the patient's head are captured by a video camera, which is calibrated and tracked by an optical tracking system. Then, a set of sparse facial data points are reconstructed from them by stereo vision in the patient space. Surface matching method is utilized to register the reconstructed sparse points and the facial surface reconstructed from preoperative images of the patient. Simulation experiments verified the feasibility of the proposed method. The proposed method it is a new low-cost and easy-to-use spatial registration method for IGNS, with good prospects for clinical application.

  14. 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.

  15. ADVANCED SOLID STATE SENSORS FOR VISION 21 SYSTEMS

    Energy Technology Data Exchange (ETDEWEB)

    C.D. Stinespring

    2005-04-28

    Silicon carbide (SiC) is a high temperature semiconductor with the potential to meet the gas and temperature sensor needs in both present and future power generation systems. These devices have been and are currently being investigated for a variety of high temperature sensing applications. These include leak detection, fire detection, environmental control, and emissions monitoring. Electronically these sensors can be very simple Schottky diode structures that rely on gas-induced changes in electrical characteristics at the metal-semiconductor interface. In these devices, thermal stability of the interfaces has been shown to be an essential requirement for improving and maintaining sensor sensitivity and lifetime. In this report, we describe device fabrication and characterization studies relevant to the development of SiC based gas and temperature sensors. Specifically, we have investigated the use of periodically stepped surfaces to improve the thermal stability of the metal semiconductor interface for simple Pd-SiC Schottky diodes. These periodically stepped surfaces have atomically flat terraces on the order of 200 nm wide separated by steps of 1.5 nm height. It should be noted that 1.5 nm is the unit cell height for the 6H-SiC (0001) substrates used in these studies. These surfaces contrast markedly with the ''standard'' SiC surfaces normally used in device fabrication. Obvious scratches and pots as well as subsurface defects characterize these standard surfaces. This research involved ultrahigh vacuum deposition and characterization studies to investigate the thermal stability of Pd-SiC Schottky diodes on both the stepped and standard surfaces, high temperature electrical characterization of these device structures, and high temperature electrical characterization of diodes under wet and dry oxidizing conditions. To our knowledge, these studies have yielded the first electrical characterization of actual sensor device structures

  16. Thermal vision based intelligent system for human detection and tracking in mobile robot control system

    Directory of Open Access Journals (Sweden)

    Ćirić Ivan T.

    2016-01-01

    Full Text Available This paper presents the results of the authors in thermal vision based mobile robot control. The most important segment of the high level control loop of mobile robot platform is an intelligent real-time algorithm for human detection and tracking. Temperature variations across same objects, air flow with different temperature gradients, reflections, person overlap while crossing each other, and many other non-linearities, uncertainty and noise, put challenges in thermal image processing and therefore the need of computationally intelligent algorithms for obtaining the efficient performance from human motion tracking system. The main goal was to enable mobile robot platform or any technical system to recognize the person in indoor environment, localize it and track it with accuracy high enough to allow adequate human-machine interaction. The developed computationally intelligent algorithms enables robust and reliable human detection and tracking based on neural network classifier and autoregressive neural network for time series prediction. Intelligent algorithm used for thermal image segmentation gives accurate inputs for classification. [Projekat Ministarstva nauke Republike Srbije, br. TR35005

  17. 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

  18. Technical vision system for analysing the mechanical characteristics of bulk materials

    Science.gov (United States)

    Boikov, A. V.; Payor, V. A.; Savelev, R. V.

    2018-01-01

    In this article actual topics concerned with mechanical properties of bulk materials, usage of computer vision and artificial neural networks in this research are discussed. The main principles of the system for analysis of bulk materials mechanical characteristics are described. Bulk material outflow behaviour with predefined parameters (particles shapes and radius, coefficients of friction, etc.) was modelled. The outflow was modelled from the calibrated conical funnel. Obtained dependencies between mechanical characteristics and pile geometrical properties are represented as diagrams and graphs.

  19. Increasing the object recognition distance of compact open air on board vision system

    Science.gov (United States)

    Kirillov, Sergey; Kostkin, Ivan; Strotov, Valery; Dmitriev, Vladimir; Berdnikov, Vadim; Akopov, Eduard; Elyutin, Aleksey

    2016-10-01

    The aim of this work was developing an algorithm eliminating the atmospheric distortion and improves image quality. The proposed algorithm is entirely software without using additional hardware photographic equipment. . This algorithm does not required preliminary calibration. It can work equally effectively with the images obtained at a distances from 1 to 500 meters. An algorithm for the open air images improve designed for Raspberry Pi model B on-board vision systems is proposed. The results of experimental examination are given.

  20. 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.

  1. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    OpenAIRE

    Chetan Singh Thakur; Runchun Mark Wang; Saeed eAfshar; Tara Julia Hamilton; Jonathan eTapson; Shihab eShamma; André evan Schaik

    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 ...

  2. 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.

  3. Epipolar constraint of single-camera mirror binocular stereo vision systems

    Science.gov (United States)

    Chai, Xinghua; Zhou, Fuqiang; Chen, Xin

    2017-08-01

    Virtual binocular sensors, composed of a camera and catoptric mirrors, have become popular among machine vision researchers, owing to their high flexibility and compactness. Usually, the tested target is projected onto a camera at different reflection times, and feature matching is performed using one image. To establish the geometric principles of the feature-matching process of a mirror binocular stereo vision system, we proposed a single-camera model with the epipolar constraint for matching the mirrored features. The constraint between the image coordinates of the real target and its mirror reflection is determined, which can be used to eliminate nonmatching points in the feature-matching process of a mirror binocular system. To validate the epipolar constraint model and to evaluate its performance in practical applications, we performed realistic matching experiments and analysis using a mirror binocular stereo vision system. Our results demonstrate the feasibility of the proposed model, suggesting a method for considerable improvement of efficacy of the process for matching mirrored features.

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

    National Research Council Canada - National Science Library

    Yi-Ting Chen; Ching-Long Shih; Guan-Ting Chen

    2015-01-01

    .... 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...

  5. A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

    Science.gov (United States)

    Balduzzi, David; Tononi, Giulio

    2012-01-01

    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. PMID:22615855

  6. 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.

  7. AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

    Science.gov (United States)

    Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

    2017-03-17

    The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16,000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging

  8. 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.

  9. 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)

  10. Design and Development of a High Speed Sorting System Based on Machine Vision Guiding

    Science.gov (United States)

    Zhang, Wenchang; Mei, Jiangping; Ding, Yabin

    In this paper, a vision-based control strategy to perform high speed pick-and-place tasks on automation product line is proposed, and relevant control software is develop. Using Delta robot to control a sucker to grasp disordered objects from one moving conveyer and then place them on the other in order. CCD camera gets one picture every time the conveyer moves a distance of ds. Objects position and shape are got after image processing. Target tracking method based on "Servo motor + synchronous conveyer" is used to fulfill the high speed porting operation real time. Experiments conducted on Delta robot sorting system demonstrate the efficiency and validity of the proposed vision-control strategy.

  11. Graphic-user-interface system for people with severely impaired vision in mathematics class.

    Science.gov (United States)

    Sribunruangrit, N; Marque, C; Lenay, C; Gapenne, O

    2004-01-01

    Computer software is more and more developed based on graphic-user-interface system (GUI) in order to be user-friendly program. However, this development creates some difficulties for people with impaired vision to use the computers. The "Braille Box", an assistive device, has been developed by modifying Braille cells to form a tactile stimulator array which is compatible with the fingertip. This device allows people with impaired vision to access graphic information on computer screen by tactile perception. We applied the "Braille Box" in mathematics class focused on linear graph, with visually impaired children. The result shows that they can perform task as determining the slope, the intercept and the coordinates of the intersection of two lines.

  12. 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.

  13. 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. PMID:22164069

  14. FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

    Directory of Open Access Journals (Sweden)

    Uwe Meyer-Baese

    2011-08-01

    Full Text Available 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.

  15. A 3D terrain reconstruction method of stereo vision based quadruped robot navigation system

    Science.gov (United States)

    Ge, Zhuo; Zhu, Ying; Liang, Guanhao

    2017-01-01

    To provide 3D environment information for the quadruped robot autonomous navigation system during walking through rough terrain, based on the stereo vision, a novel 3D terrain reconstruction method is presented. In order to solve the problem that images collected by stereo sensors have large regions with similar grayscale and the problem that image matching is poor at real-time performance, watershed algorithm and fuzzy c-means clustering algorithm are combined for contour extraction. Aiming at the problem of error matching, duel constraint with region matching and pixel matching is established for matching optimization. Using the stereo matching edge pixel pairs, the 3D coordinate algorithm is estimated according to the binocular stereo vision imaging model. Experimental results show that the proposed method can yield high stereo matching ratio and reconstruct 3D scene quickly and efficiently.

  16. Improved camera calibration method based on perpendicularity compensation for binocular stereo vision measurement system.

    Science.gov (United States)

    Jia, Zhenyuan; Yang, Jinghao; Liu, Wei; Wang, Fuji; Liu, Yang; Wang, Lingli; Fan, Chaonan; Zhao, Kai

    2015-06-15

    High-precision calibration of binocular vision systems plays an important role in accurate dimensional measurements. In this paper, an improved camera calibration method is proposed. First, an accurate intrinsic parameters calibration method based on active vision with perpendicularity compensation is developed. Compared to the previous work, this method eliminates the effect of non-perpendicularity of the camera motion on calibration accuracy. The principal point, scale factors, and distortion factors are calculated independently in this method, thereby allowing the strong coupling of these parameters to be eliminated. Second, an accurate global optimization method with only 5 images is presented. The results of calibration experiments show that the accuracy of the calibration method can reach 99.91%.

  17. 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.

  18. SAD-Based Stereo Vision Machine on a System-on-Programmable-Chip (SoPC

    Directory of Open Access Journals (Sweden)

    Zhangwei Chen

    2013-03-01

    Full Text Available 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.

  19. 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.

  20. Parametric study of sensor placement for vision-based relative navigation system of multiple spacecraft

    Science.gov (United States)

    Jeong, Junho; Kim, Seungkeun; Suk, Jinyoung

    2017-12-01

    In order to overcome the limited range of GPS-based techniques, vision-based relative navigation methods have recently emerged as alternative approaches for a high Earth orbit (HEO) or deep space missions. Therefore, various vision-based relative navigation systems use for proximity operations between two spacecraft. For the implementation of these systems, a sensor placement problem can occur on the exterior of spacecraft due to its limited space. To deal with the sensor placement, this paper proposes a novel methodology for a vision-based relative navigation based on multiple position sensitive diode (PSD) sensors and multiple infrared beacon modules. For the proposed method, an iterated parametric study is used based on the farthest point optimization (FPO) and a constrained extended Kalman filter (CEKF). Each algorithm is applied to set the location of the sensors and to estimate relative positions and attitudes according to each combination by the PSDs and beacons. After that, scores for the sensor placement are calculated with respect to parameters: the number of the PSDs, number of the beacons, and accuracy of relative estimates. Then, the best scoring candidate is determined for the sensor placement. Moreover, the results of the iterated estimation show that the accuracy improves dramatically, as the number of the PSDs increases from one to three.

  1. SAD-based stereo vision machine on a System-on-Programmable-Chip (SoPC).

    Science.gov (United States)

    Zhang, Xiang; Chen, Zhangwei

    2013-03-04

    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.

  2. 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...

  3. Neuromorphic device architectures with global connectivity through electrolyte gating

    Science.gov (United States)

    Gkoupidenis, Paschalis; Koutsouras, Dimitrios A.; Malliaras, George G.

    2017-05-01

    Information processing in the brain takes place in a network of neurons that are connected with each other by an immense number of synapses. At the same time, neurons are immersed in a common electrochemical environment, and global parameters such as concentrations of various hormones regulate the overall network function. This computational paradigm of global regulation, also known as homeoplasticity, has important implications in the overall behaviour of large neural ensembles and is barely addressed in neuromorphic device architectures. Here, we demonstrate the global control of an array of organic devices based on poly(3,4ethylenedioxythiophene):poly(styrene sulf) that are immersed in an electrolyte, a behaviour that resembles homeoplasticity phenomena of the neural environment. We use this effect to produce behaviour that is reminiscent of the coupling between local activity and global oscillations in the biological neural networks. We further show that the electrolyte establishes complex connections between individual devices, and leverage these connections to implement coincidence detection. These results demonstrate that electrolyte gating offers significant advantages for the realization of networks of neuromorphic devices of higher complexity and with minimal hardwired connectivity.

  4. 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.

  5. Vision sensor and dual MEMS gyroscope integrated system for attitude determination on moving base

    Science.gov (United States)

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

    2018-01-01

    To determine the relative attitude between the objects on a moving base and the base reference system by a MEMS (Micro-Electro-Mechanical Systems) gyroscope, the motion information of the base is redundant, which must be removed from the gyroscope. Our strategy is to add an auxiliary gyroscope attached to the reference system. The master gyroscope is to sense the total motion, and the auxiliary gyroscope is to sense the motion of the moving base. By a generalized difference method, relative attitude in a non-inertial frame can be determined by dual gyroscopes. With the vision sensor suppressing accumulative drift of the MEMS gyroscope, the vision and dual MEMS gyroscope integration system is formed. Coordinate system definitions and spatial transform are executed in order to fuse inertial and visual data from different coordinate systems together. And a nonlinear filter algorithm, Cubature Kalman filter, is used to fuse slow visual data and fast inertial data together. A practical experimental setup is built up and used to validate feasibility and effectiveness of our proposed attitude determination system in the non-inertial frame on the moving base.

  6. Evaluation of a gaze-controlled vision enhancement system for reading in visually impaired people.

    Directory of Open Access Journals (Sweden)

    Carlos Aguilar

    Full Text Available People with low vision, especially those with Central Field Loss (CFL, need magnification to read. The flexibility of Electronic Vision Enhancement Systems (EVES offers several ways of magnifying text. Due to the restricted field of view of EVES, the need for magnification is conflicting with the need to navigate through text (panning. We have developed and implemented a real-time gaze-controlled system whose goal is to optimize the possibility of magnifying a portion of text while maintaining global viewing of the other portions of the text (condition 1. Two other conditions were implemented that mimicked commercially available advanced systems known as CCTV (closed-circuit television systems-conditions 2 and 3. In these two conditions, magnification was uniformly applied to the whole text without any possibility to specifically select a region of interest. The three conditions were implemented on the same computer to remove differences that might have been induced by dissimilar equipment. A gaze-contingent artificial 10° scotoma (a mask continuously displayed in real time on the screen at the gaze location was used in the three conditions in order to simulate macular degeneration. Ten healthy subjects with a gaze-contingent scotoma read aloud sentences from a French newspaper in nine experimental one-hour sessions. Reading speed was measured and constituted the main dependent variable to compare the three conditions. All subjects were able to use condition 1 and they found it slightly more comfortable to use than condition 2 (and similar to condition 3. Importantly, reading speed results did not show any significant difference between the three systems. In addition, learning curves were similar in the three conditions. This proof of concept study suggests that the principles underlying the gaze-controlled enhanced system might be further developed and fruitfully incorporated in different kinds of EVES for low vision reading.

  7. Evaluation of a gaze-controlled vision enhancement system for reading in visually impaired people.

    Science.gov (United States)

    Aguilar, Carlos; Castet, Eric

    2017-01-01

    People with low vision, especially those with Central Field Loss (CFL), need magnification to read. The flexibility of Electronic Vision Enhancement Systems (EVES) offers several ways of magnifying text. Due to the restricted field of view of EVES, the need for magnification is conflicting with the need to navigate through text (panning). We have developed and implemented a real-time gaze-controlled system whose goal is to optimize the possibility of magnifying a portion of text while maintaining global viewing of the other portions of the text (condition 1). Two other conditions were implemented that mimicked commercially available advanced systems known as CCTV (closed-circuit television systems)-conditions 2 and 3. In these two conditions, magnification was uniformly applied to the whole text without any possibility to specifically select a region of interest. The three conditions were implemented on the same computer to remove differences that might have been induced by dissimilar equipment. A gaze-contingent artificial 10° scotoma (a mask continuously displayed in real time on the screen at the gaze location) was used in the three conditions in order to simulate macular degeneration. Ten healthy subjects with a gaze-contingent scotoma read aloud sentences from a French newspaper in nine experimental one-hour sessions. Reading speed was measured and constituted the main dependent variable to compare the three conditions. All subjects were able to use condition 1 and they found it slightly more comfortable to use than condition 2 (and similar to condition 3). Importantly, reading speed results did not show any significant difference between the three systems. In addition, learning curves were similar in the three conditions. This proof of concept study suggests that the principles underlying the gaze-controlled enhanced system might be further developed and fruitfully incorporated in different kinds of EVES for low vision reading.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Air and Water System (AWS) Design and Technology Selection for the Vision for Space Exploration

    Science.gov (United States)

    Jones, Harry; Kliss, Mark

    2005-01-01

    This paper considers technology selection for the crew air and water recycling systems to be used in long duration human space exploration. The specific objectives are to identify the most probable air and water technologies for the vision for space exploration and to identify the alternate technologies that might be developed. The approach is to conduct a preliminary first cut systems engineering analysis, beginning with the Air and Water System (AWS) requirements and the system mass balance, and then define the functional architecture, review the International Space Station (ISS) technologies, and discuss alternate technologies. The life support requirements for air and water are well known. The results of the mass flow and mass balance analysis help define the system architectural concept. The AWS includes five subsystems: Oxygen Supply, Condensate Purification, Urine Purification, Hygiene Water Purification, and Clothes Wash Purification. AWS technologies have been evaluated in the life support design for ISS node 3, and in earlier space station design studies, in proposals for the upgrade or evolution of the space station, and in studies of potential lunar or Mars missions. The leading candidate technologies for the vision for space exploration are those planned for Node 3 of the ISS. The ISS life support was designed to utilize Space Station Freedom (SSF) hardware to the maximum extent possible. The SSF final technology selection process, criteria, and results are discussed. Would it be cost-effective for the vision for space exploration to develop alternate technology? This paper will examine this and other questions associated with AWS design and technology selection.

  14. A Vision-Based Dynamic Rotational Angle Measurement System for Large Civil Structures

    Directory of Open Access Journals (Sweden)

    Jong-Jae Lee

    2012-05-01

    Full Text Available 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.

  15. A three-dimensional vision by off-shelf system with multi-cameras.

    Science.gov (United States)

    Luh, J Y; Klaasen, J A

    1985-01-01

    A three-dimnensional vision system for on-line operation that aids a collision avoidance system for an industrial robot is developed. Because of the real-time requirement, the process that locates and describes the obstacles must be fast. To satisfy the safety requirement, the obstacle model should always contain the physical obstacle entirely. This condition leads to the bounding box description of the obstacle, which is simple for the computer to process. The image processing is performed by a Machine Intelligence Corporation VS-100 machine vision system. The control and object perception is performed by the developed software on a host Digital Equipment Corporation VAX 11/780 Computer. The resultant system outputs a file of the locations and bounding descriptions for each object found. When the system is properly calibrated, the bounding descriptions always completely envelop the obstacle. The response time is data-dependent. When using two cameras and processed on UNIX time sharing mode, the average response time will be less than 2 s if eight or fewer objects are present. When using all three cameras, the average response time will be less than 4 s if eight or fewer objects are present.

  16. Quality detection system and method of micro-accessory based on microscopic vision

    Science.gov (United States)

    Li, Dongjie; Wang, Shiwei; Fu, Yu

    2017-10-01

    Considering that the traditional manual detection of micro-accessory has some problems, such as heavy workload, low efficiency and large artificial error, a kind of quality inspection system of micro-accessory has been designed. Micro-vision technology has been used to inspect quality, which optimizes the structure of the detection system. The stepper motor is used to drive the rotating micro-platform to transfer quarantine device and the microscopic vision system is applied to get graphic information of micro-accessory. The methods of image processing and pattern matching, the variable scale Sobel differential edge detection algorithm and the improved Zernike moments sub-pixel edge detection algorithm are combined in the system in order to achieve a more detailed and accurate edge of the defect detection. The grade at the edge of the complex signal can be achieved accurately by extracting through the proposed system, and then it can distinguish the qualified products and unqualified products with high precision recognition.

  17. 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.

  18. Platelet count estimation using the CellaVision DM96 system.

    Science.gov (United States)

    Gao, Yuon; Mansoor, Adnan; Wood, Brenda; Nelson, Heather; Higa, Diane; Naugler, Christopher

    2013-01-01

    Rapid and accurate determination of platelet count is an important factor in diagnostic medicine. Traditional microscopic methods are labor intensive with variable results and are highly dependent on the individual training. Recent developments in automated peripheral blood differentials using a computerized system have shown many advantages as a viable alternative. The purpose of this paper was to determine the reliability and accuracy of the CellaVision DM 96 system with regards to platelet counts. One hundred twenty seven peripheral blood smears were analyzed for platelet count by manual microscopy, an automated hematology analyzer (Beckman Counter LH 780 or Unicel DXH 800 analyzers) and with the CellaVision DM96 system. Results were compared using the correlations and Bland-Altman plots. Platelet counts from the DM96 system showed an R(2) of 0.94 when compared to manual platelet estimates and an R(2) of 0.92 when compared to the automated hematology analyzer results. Bland-Altman plots did not show any systematic bias.

  19. Platelet count estimation using the CellaVision DM96 system

    Directory of Open Access Journals (Sweden)

    Yuon Gao

    2013-01-01

    Full Text Available Introduction: Rapid and accurate determination of platelet count is an important factor in diagnostic medicine. Traditional microscopic methods are labor intensive with variable results and are highly dependent on the individual training. Recent developments in automated peripheral blood differentials using a computerized system have shown many advantages as a viable alternative. The purpose of this paper was to determine the reliability and accuracy of the CellaVision DM 96 system with regards to platelet counts. Materials and Methods: One hundred twenty seven peripheral blood smears were analyzed for platelet count by manual microscopy, an automated hematology analyzer (Beckman Counter LH 780 or Unicel DXH 800 analyzers and with the CellaVision DM96 system. Results were compared using the correlations and Bland-Altman plots. Results: Platelet counts from the DM96 system showed an R 2 of 0.94 when compared to manual platelet estimates and an R 2 of 0.92 when compared to the automated hematology analyzer results. Bland-Altman plots did not show any systematic bias.

  20. 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.

  1. 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.

  2. Design of a perspective flight guidance display for a synthetic vision system

    Science.gov (United States)

    Gross, Martin; Mayer, Udo; Kaufhold, Rainer

    1998-07-01

    Adverse weather conditions affect flight safety as well as productivity of the air traffic industry. The problem becomes evident in the airport area (Taxiing, takeoff, approach and landing). The productivity of the air traffic industry goes down because the resources of the airport can not be used optimally. Canceled and delayed flights lead directly to additional costs for the airlines. Against the background of aggravated problems due to a predicted increasing air traffic the European Union launched the project AWARD (All Weather ARrival and Departure) in June 1996. Eleven European aerospace companies and research institutions are participating. The project will be finished by the end of 1999. Subject of AWARD is the development of a Synthetic Vision System (based on database and navigation) and an Enhanced Vision System (based on sensors like FLIR and MMWR). Darmstadt University of Technology is responsible for the development of the SVS prototype. The SVS application is depending on precise navigation, databases for terrain and flight relevant information, and a flight guidance display. The objective is to allow landings under CAT III a/b conditions independently from CAT III ILS airport installations. One goal of SVS is to enhance the situation awareness of pilots during all airport area operations by designing an appropriate man-machine- interface for the display. This paper describes the current state of the research and development of the Synthetic Vision System being developed in AWARD. The paper describes which methodology was used to identify the information that should be displayed. Human factors which influenced the basic design of the SVS are portrayed and some of the planned activities for the flight simulation tests are summarized.

  3. 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

  4. Introduction of Enhanced Vision System and its Application for General Aviation

    Directory of Open Access Journals (Sweden)

    Roman Matyáš

    2015-10-01

    Full Text Available Enhanced Vision System (EVS technology has been developing since 1980s. The research itself has been mainly focused on controlling Unmanned Aerial Vehicles (UAVs. In this area, some methods were successfully tested, from take-off to landing. This paper is meant to be an introduction for further research and testing within general aviation area for use of EVS technology by high experienced as well as low experienced pilots in order to increase the level of safety during critical stages of flight.

  5. Evaluation of enzymatic browning in fresh-cut apple slices applying a multispectral vision system

    OpenAIRE

    Lunadei, Loredana; Galleguillos, Pamela; Diezma Iglesias, Belen; Lleó García, Lourdes

    2010-01-01

    n this study a vision system was applied for assessing enzymatic browning evolution in fresh-cut apples slices stored at 7.5 °C and 85 % HR. Twenty-four slices were analyzed per day: at zero time and after storage for 1 , 3 ,7 and 9 days. A classification procedure was applied to virtual images obtained as a combination of the red (R) and blue (B) channel (B/R, R-B and R-B/R+B). In all cases, three images based browning reference classes were generated. An external validation was applied...

  6. 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...

  7. Three-dimensional movement analysis for near infrared system using stereo vision and optical flow techniques

    Science.gov (United States)

    Parra Escamilla, Geliztle A.; Serrano Garcia, David I.; Otani, Yukitoshi

    2017-04-01

    The purpose of this paper is the measurement of spatial-temporal movements by using stereo vision and 3D optical flow algorithms applied at biological samples. Stereo calibration procedures and algorithms for enhance the contrast intensity were applied. The system was implemented for working at the first near infrared windows (NIR-I) at 850 nm due of the penetration depth obtained at this region in biological tissue. Experimental results of 3D tracking of human veins are presented showing the characteristics of the implementation.

  8. Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

    OpenAIRE

    CUBERO GARCÍA, SERGIO; Aleixos Borrás, María Nuria; Albert Gil, Francisco Eugenio; Torregrosa, A.; Ortiz Sánchez, María Coral; GARCÍA NAVARRETE, OSCAR LEONARDO; BLASCO IVARS, JOSE

    2014-01-01

    The mechanisation and automation of citrus harvesting is considered to be one of the best options to reduce production costs. Computer vision technology has been shown to be a useful tool for fresh fruit and vegetable inspection, and is currently used in post-harvest fruit and vegetable automated grading systems in packing houses. Although computer vision technology has been used in some harvesting robots, it is not commonly utilised in fruit grading during harvesting due to the difficulties ...

  9. 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.

  10. 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.

  11. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing

    Science.gov (United States)

    Wang, Zhongrui; Joshi, Saumil; Savel'Ev, Sergey E.; Jiang, Hao; Midya, Rivu; Lin, Peng; Hu, Miao; Ge, Ning; Strachan, John Paul; Li, Zhiyong; Wu, Qing; Barnell, Mark; Li, Geng-Lin; Xin, Huolin L.; Williams, R. Stanley; Xia, Qiangfei; Yang, J. Joshua

    2017-01-01

    The accumulation and extrusion of Ca2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca2+, respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities.

  12. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

    Science.gov (United States)

    van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J.; Keene, Scott T.; Faria, Grégorio C.; Agarwal, Sapan; Marinella, Matthew J.; Alec Talin, A.; Salleo, Alberto

    2017-04-01

    The brain is capable of massively parallel information processing while consuming only ~1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (500 distinct, non-volatile conductance states within a ~1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

  13. Rear-end vision-based collision detection system for motorcyclists

    Science.gov (United States)

    Muzammel, Muhammad; Yusoff, Mohd Zuki; Meriaudeau, Fabrice

    2017-05-01

    In many countries, the motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. To increase the safety of motorcyclists and minimize their road fatalities, this paper introduces a vision-based rear-end collision detection system. The binary road detection scheme contributes significantly to reduce the negative false detections and helps to achieve reliable results even though shadows and different lane markers are present on the road. The methodology is based on Harris corner detection and Hough transform. To validate this methodology, two types of dataset are used: (1) self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and (2) online datasets (recorded by placing a camera at the front of a car). This method achieved 95.1% accuracy for the self-recorded dataset and gives reliable results for the rear-end vehicle detections under different road scenarios. This technique also performs better for the online car datasets. The proposed technique's high detection accuracy using a monocular vision camera coupled with its low computational complexity makes it a suitable candidate for a motorbike rear-end collision detection system.

  14. 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.

  15. Monocular Vision System for Fixed Altitude Flight of Unmanned Aerial Vehicles.

    Science.gov (United States)

    Huang, Kuo-Lung; Chiu, Chung-Cheng; Chiu, Sheng-Yi; Teng, Yao-Jen; Hao, Shu-Sheng

    2015-07-13

    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.

  16. 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.

  17. 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.

  18. 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.

  19. Rapid, computer vision-enabled murine screening system identifies neuropharmacological potential of two new mechanisms.

    Science.gov (United States)

    Roberds, Steven L; Filippov, Igor; Alexandrov, Vadim; Hanania, Taleen; Brunner, Dani

    2011-01-01

    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.

  20. Optimization of spatial light distribution through genetic algorithms for vision systems applied to quality control

    Science.gov (United States)

    Castellini, P.; Cecchini, S.; Stroppa, L.; Paone, N.

    2015-02-01

    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.

  1. Pseudo-color coding method of infrared images based on human vision system

    Science.gov (United States)

    Zhang, Xiao; Bai, Tingzhu; Li, Hailan

    2008-03-01

    Infrared images often display in gray scale. The low contrast and the unclear visual effect are the most notable characters of infrared images that make difficult to observe. It is a fact that gray scale is not sensitive to human eyes, and it has only 60 to 90 just noticeable differences (JNDs). In comparison with gray scale, color scale might give up to 500 JNDs. Usually people can distinguish many kinds of colors much more than grays. And in gray images, human don't have the ability to tell apart the nuances about detail. Pseudo-color coding enhancement is the task of applying certain alterations to an input gray-image such as to obtain color-image that is a more visually pleasing. In this paper, we introduced a pseudo-color coding method based on human vision system for infrared images display. The HSI space is especially fit for human vision system and is viewed as an approximation of perceptual color space. So the pseudo-color coding method introduced is based on HSI space. In the first place, the individual functional relationship of Hue, Intensity, and Saturation with gray scale level is established. In the second place, the corresponding RGB values are obtained through transformation from the HSI color space to the RGB space. Lastly, the effect of Infrared images enhancement based on the pseudo-color coding method is displayed. Results indicate that this method is superior to other methods through the comparison.

  2. Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

    Directory of Open Access Journals (Sweden)

    Min Chen

    2017-12-01

    Full Text Available Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses.

  3. Experimental Machine Vision System for Training Students in Virtual Instrumentation Techniques

    Directory of Open Access Journals (Sweden)

    Rodica Holonec

    2011-10-01

    Full Text Available The aim of this paper is to present the main techniques in designing and building of a complex machine vision system in order to train electrical engineering students in using virtual instrumentation. The proposed test bench realizes an automatic adjustment of some electrical circuit parameters on a belt conveyer. The students can learn how to combine mechanics, electronics, electrical engineering, image acquisition and processing in order to solve the proposed application. After the system implementation the students are asked to present in which way they can modify or extend the system for industrial environment regarding the automatic adjustment of electric parameters or the calibration of different type of sensors (of distance, of proximity, etc without the intervention of the human factor in the process.

  4. Automated vision system for fabric defect inspection using Gabor filters and PCNN.

    Science.gov (United States)

    Li, Yundong; Zhang, Cheng

    2016-01-01

    In this study, an embedded machine vision system using Gabor filters and Pulse Coupled Neural Network (PCNN) is developed to identify defects of warp-knitted fabrics automatically. The system consists of smart cameras and a Human Machine Interface (HMI) controller. A hybrid detection algorithm combing Gabor filters and PCNN is running on the SOC processor of the smart camera. First, Gabor filters are employed to enhance the contrast of images captured by a CMOS sensor. Second, defect areas are segmented by PCNN with adaptive parameter setting. Third, smart cameras will notice the controller to stop the warp-knitting machine once defects are found out. Experimental results demonstrate that the hybrid method is superior to Gabor and wavelet methods on detection accuracy. Actual operations in a textile factory verify the effectiveness of the inspection system.

  5. Design Considerations for Scalable High-Performance Vision Systems Embedded in Industrial Print Inspection Machines

    Directory of Open Access Journals (Sweden)

    Rössler Peter

    2007-01-01

    Full Text Available This paper describes the design of a scalable high-performance vision system which is used in the application area of optical print inspection. The system is able to process hundreds of megabytes of image data per second coming from several high-speed/high-resolution cameras. Due to performance requirements, some functionality has been implemented on dedicated hardware based on a field programmable gate array (FPGA, which is coupled to a high-end digital signal processor (DSP. The paper discusses design considerations like partitioning of image processing algorithms between hardware and software. The main chapters focus on functionality implemented on the FPGA, including low-level image processing algorithms (flat-field correction, image pyramid generation, neighborhood operations and advanced processing units (programmable arithmetic unit, geometry unit. Verification issues for the complex system are also addressed. The paper concludes with a summary of the FPGA resource usage and some performance results.

  6. APLIKASI SISTEM MONITORING PERTUMBUHAN TANAMAN BERBASIS WEB MENGGUNAKAN MACHINE VISION Application of Web-based Monitoring System for Plant Growing by Using Machine Vision

    Directory of Open Access Journals (Sweden)

    Lilik Sutiarso

    2012-05-01

    Full Text Available Nowadays, demand for integrating between information technology (IT and development of agricultural system isin order to increase the productivity, efficiency and profitability in term of precision agriculture. This matter occurred due to some problems in the field, such as; unintensively monitoring activities for plant during the growing period. One of the alternative solutions to overcome the problem was introducing the machine vision technology in the farming system. The research is actually as a basic research that aims using technology of digital image processing and software of computation (mathematics to support a function of real-time monitoring system for plant growing. The research mechanism was started from digital image processing by using an image segmentation method that can identify between the main object (plant and others (soil, weed. Image processing algorithm used excess color method and color normalization to identify plants, to calculate crop area. Otsu method was used to convert it to binary images. The next was to calculate and analyze a percentage of the plant growing, from after planting until harvesting time. The analyzed data were stored as MySQL database format in the web server. Final output of the research was the web based monitoring instruments for plant growing that can be accessed through intranet (local area network as well as internet technology. From the software testing, monitoring with a machine vision system has a success rate reached 70 % for identifying plants. ABSTRAK Tuntutan integrasi teknologi sistem informasi dan sistem pertanian saat ini dimaksudkan guna mendukung efisiensi,produktivitas dan profitabiltas pertanian. Hal tersebut didorong oleh timbulnya permasalahan di lapangan terkait dengan belum optimalnya produktivitas tanaman yang diakibatkan antara lain, kurang intensifnya pemantauan (monitoring tanaman pada masa pertumbuhan. Salah satu alternatif solusi untuk memperbaiki permasalahan tersebut

  7. Low Vision Aids and Low Vision Rehabilitation

    Science.gov (United States)

    ... Low Vision Aids Low Vision Resources Low Vision Rehabilitation and Low Vision Aids Leer en Español: La ... that same viewing direction for other objects. Vision rehabilitation: using the vision you have Vision rehabilitation is ...

  8. 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...

  9. 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...

  10. Cognitive vision system for control of dexterous prosthetic hands: experimental evaluation.

    Science.gov (United States)

    Dosen, Strahinja; Cipriani, Christian; Kostić, Milos; Controzzi, Marco; Carrozza, Maria C; Popović, Dejan B

    2010-08-23

    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. 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. 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). 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 size). The automatic control eases the burden from the user

  11. 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

  12. Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems.

    Science.gov (United States)

    Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

    2016-12-17

    Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

  13. Precision calibration method for binocular vision measurement systems based on arbitrary translations and 3D-connection information

    Science.gov (United States)

    Yang, Jinghao; Jia, Zhenyuan; Liu, Wei; Fan, Chaonan; Xu, Pengtao; Wang, Fuji; Liu, Yang

    2016-10-01

    Binocular vision systems play an important role in computer vision, and high-precision system calibration is a necessary and indispensable process. In this paper, an improved calibration method for binocular stereo vision measurement systems based on arbitrary translations and 3D-connection information is proposed. First, a new method for calibrating the intrinsic parameters of binocular vision system based on two translations with an arbitrary angle difference is presented, which reduces the effect of the deviation of the motion actuator on calibration accuracy. This method is simpler and more accurate than existing active-vision calibration methods and can provide a better initial value for the determination of extrinsic parameters. Second, a 3D-connection calibration and optimization method is developed that links the information of the calibration target in different positions, further improving the accuracy of the system calibration. Calibration experiments show that the calibration error can be reduced to 0.09%, outperforming traditional methods for the experiments of this study.

  14. A Vision-Based Driver Nighttime Assistance and Surveillance System Based on Intelligent Image Sensing Techniques and a Heterogamous Dual-Core Embedded System Architecture

    Directory of Open Access Journals (Sweden)

    Jenq-Haur Wang

    2012-02-01

    Full Text Available 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.

  15. 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.

  16. 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.

  17. Simulation of Specular Surface Imaging Based on Computer Graphics: Application on a Vision Inspection System

    Science.gov (United States)

    Seulin, Ralph; Merienne, Frederic; Gorria, Patrick

    2002-12-01

    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.

  18. 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.

  19. Computer vision system for egg volume prediction using backpropagation neural network

    Science.gov (United States)

    Siswantoro, J.; Hilman, M. Y.; Widiasri, M.

    2017-11-01

    Volume is one of considered aspects in egg sorting process. A rapid and accurate volume measurement method is needed to develop an egg sorting system. Computer vision system (CVS) provides a promising solution for volume measurement problem. Artificial neural network (ANN) has been used to predict the volume of egg in several CVSs. However, volume prediction from ANN could have less accuracy due to inappropriate input features or inappropriate ANN structure. This paper proposes a CVS for predicting the volume of egg using ANN. The CVS acquired an image of egg from top view and then processed the image to extract its 1D and 2 D size features. The features were used as input for ANN in predicting the volume of egg. The experiment results show that the proposed CSV can predict the volume of egg with a good accuracy and less computation time.

  20. An Address Event Representation-Based Processing System for a Biped Robot

    Directory of Open Access Journals (Sweden)

    Uziel Jaramillo-Avila

    2016-02-01

    Full Text Available In recent years, several important advances have been made in the fields of both biologically inspired sensorial processing and locomotion systems, such as Address Event Representation-based cameras (or Dynamic Vision Sensors and in human-like robot locomotion, e.g., the walking of a biped robot. However, making these fields merge properly is not an easy task. In this regard, Neuromorphic Engineering is a fast-growing research field, the main goal of which is the biologically inspired design of hybrid hardware systems in order to mimic neural architectures and to process information in the manner of the brain. However, few robotic applications exist to illustrate them. The main goal of this work is to demonstrate, by creating a closed-loop system using only bio-inspired techniques, how such applications can work properly. We present an algorithm using Spiking Neural Networks (SNN for a biped robot equipped with a Dynamic Vision Sensor, which is designed to follow a line drawn on the floor. This is a commonly used method for demonstrating control techniques. Most of them are fairly simple to implement without very sophisticated components; however, it can still serve as a good test in more elaborate circumstances. In addition, the locomotion system proposed is able to coordinately control the six DOFs of a biped robot in switching between basic forms of movement. The latter has been implemented as a FPGA-based neuromorphic system. Numerical tests and hardware validation are presented.

  1. Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

    Science.gov (United States)

    Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

    2017-06-01

    We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

  2. 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

  3. 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

  4. Acquired color vision deficiency.

    Science.gov (United States)

    Simunovic, Matthew P

    2016-01-01

    Acquired color vision deficiency occurs as the result of ocular, neurologic, or systemic disease. A wide array of conditions may affect color vision, ranging from diseases of the ocular media through to pathology of the visual cortex. Traditionally, acquired color vision deficiency is considered a separate entity from congenital color vision deficiency, although emerging clinical and molecular genetic data would suggest a degree of overlap. We review the pathophysiology of acquired color vision deficiency, the data on its prevalence, theories for the preponderance of acquired S-mechanism (or tritan) deficiency, and discuss tests of color vision. We also briefly review the types of color vision deficiencies encountered in ocular disease, with an emphasis placed on larger or more detailed clinical investigations. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. 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

  6. 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

  7. The continuous-flow synthesis of carbazate hydrazones using a simplified computer-vision controlled liquid-liquid extraction system

    OpenAIRE

    O'Brien, M.; Cooper, D.; Mhembere, P

    2016-01-01

    A computer-vision controlled liquid-liquid extraction system was used in the continuous-flow synthesis of a series of carbazate hydrazones. The system uses open-source software components (Python, OpenCV) and is simpler and potentially more economical, in terms of hardware, than one we have described previously.

  8. Ensemble of different local descriptors, codebook generation methods and subwindow configurations for building a reliable computer vision system

    Directory of Open Access Journals (Sweden)

    Loris Nanni

    2014-04-01

    The MATLAB code of our system will be publicly available at http://www.dei.unipd.it/wdyn/?IDsezione=3314&IDgruppo_pass=124&preview=. Our free MATLAB toolbox can be used to verify the results of our system. We also hope that our toolbox will serve as the foundation for further explorations by other researchers in the computer vision field.

  9. Microscopic vision modeling method by direct mapping analysis for micro-gripping system with stereo light microscope.

    Science.gov (United States)

    Wang, Yuezong; Zhao, Zhizhong; Wang, Junshuai

    2016-04-01

    We present a novel and high-precision microscopic vision modeling method, which can be used for 3D data reconstruction in micro-gripping system with stereo light microscope. This method consists of four parts: image distortion correction, disparity distortion correction, initial vision model and residual compensation model. First, the method of image distortion correction is proposed. Image data required by image distortion correction comes from stereo images of calibration sample. The geometric features of image distortions can be predicted though the shape deformation of lines constructed by grid points in stereo images. Linear and polynomial fitting methods are applied to correct image distortions. Second, shape deformation features of disparity distribution are discussed. The method of disparity distortion correction is proposed. Polynomial fitting method is applied to correct disparity distortion. Third, a microscopic vision model is derived, which consists of two models, i.e., initial vision model and residual compensation model. We derive initial vision model by the analysis of direct mapping relationship between object and image points. Residual compensation model is derived based on the residual analysis of initial vision model. The results show that with maximum reconstruction distance of 4.1mm in X direction, 2.9mm in Y direction and 2.25mm in Z direction, our model achieves a precision of 0.01mm in X and Y directions and 0.015mm in Z direction. Comparison of our model with traditional pinhole camera model shows that two kinds of models have a similar reconstruction precision of X coordinates. However, traditional pinhole camera model has a lower precision of Y and Z coordinates than our model. The method proposed in this paper is very helpful for the micro-gripping system based on SLM microscopic vision. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. The model and its solution's uniqueness of a portable 3D vision coordinate measuring system

    Science.gov (United States)

    Huang, Fengshan; Qian, Huifen

    2009-11-01

    The portable three-dimensional vision coordinate measuring system, which consists of a light pen, a CCD camera and a laptop computer, can be widely applied in most coordinate measuring fields especially on the industrial spots. On the light pen there are at least three point-shaped light sources (LEDs) acting as the measured control characteristic points and a touch trigger probe with a spherical stylus which is used to contact the point to be measured. The most important character of this system is that three light sources and the probe stylus are aligned in one line with known positions. In building and studying this measuring system, how to construct the system's mathematical model is the most key problem called Perspective of Three-Collinear-points Problem, which is a particular case of Perspective of Three-points Problem (P3P). On the basis of P3P and spatial analytical geometry theory, the system's mathematical model is established. What's more, it is verified that Perspective of Three-Collinear-points Problem has a unique solution. And the analytical equations of the measured point's coordinates are derived by using the system's mathematical model and the restrict condition that three light sources and the probe stylus are aligned in one line. Finally, the effectiveness of the mathematical model is confirmed by experiments.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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....

  16. 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.

  17. Omnidirectional stereo vision sensor based on single camera and catoptric system.

    Science.gov (United States)

    Zhou, Fuqiang; Chai, Xinghua; Chen, Xin; Song, Ya

    2016-09-01

    An omnidirectional stereo vision sensor based on one single camera and catoptric system is proposed. As crucial components, one camera and two pyramid mirrors are used for imaging. The omnidirectional measurement towards different directions in the horizontal field can be performed by four pairs of virtual cameras, with a consummate synchronism and an improved compactness. Moreover, the perspective projection invariance is ensured in the imaging process, which avoids the imaging distortion reflected by the curved mirrors. In this paper, the structure model of the sensor was established and a sensor prototype was designed. The influences of the structural parameters on the field of view and the measurement accuracy were also discussed. In addition, real experiments and analyses were performed to evaluate the performance of the proposed sensor in the measurement application. The results proved the feasibility of the sensor, and exhibited a considerable accuracy in 3D coordinate reconstruction.

  18. 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.

  19. 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

  20. Complex IoT Systems as Enablers for Smart Homes in a Smart City Vision

    DEFF Research Database (Denmark)

    Lynggaard, Per; Skouby, Knud Erik

    2016-01-01

    The world is entering a new era, where Internet-of-Things (IoT), smart homes, and smart cities will play an important role in meeting the so-called big challenges. In the near future, it is foreseen that the majority of the world’s population will live their lives in smart homes and in smart cities...... the “smart” vision. This paper proposes a specific solution in the form of a hierarchical layered ICT based infrastructure that handles ICT issues related to the “big challenges” and seamlessly integrates IoT, smart homes, and smart city structures into one coherent unit. To exemplify benefits...... of this infrastructure, a complex IoT system has been deployed, simulated and elaborated. This simulation deals with wastewater energy harvesting from smart buildings located in a smart city context. From the simulations, it has been found that the proposed infrastructure is able to harvest between 50% and 75...

  1. 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.

  2. Automatic human body modeling for vision-based motion capture system using B-spline parameterization of the silhouette

    Science.gov (United States)

    Jaume-i-Capó, Antoni; Varona, Javier; González-Hidalgo, Manuel; Mas, Ramon; Perales, Francisco J.

    2012-02-01

    Human motion capture has a wide variety of applications, and in vision-based motion capture systems a major issue is the human body model and its initialization. We present a computer vision algorithm for building a human body model skeleton in an automatic way. The algorithm is based on the analysis of the human shape. We decompose the body into its main parts by computing the curvature of a B-spline parameterization of the human contour. This algorithm has been applied in a context where the user is standing in front of a camera stereo pair. The process is completed after the user assumes a predefined initial posture so as to identify the main joints and construct the human model. Using this model, the initialization problem of a vision-based markerless motion capture system of the human body is solved.

  3. Monocular Vision- and IMU-Based System for Prosthesis Pose Estimation During Total Hip Replacement Surgery.

    Science.gov (United States)

    Su, Shaojie; Zhou, Yixin; Wang, Zhihua; Chen, Hong

    2017-06-01

    The average age of population increases worldwide, so does the number of total hip replacement surgeries. Total hip replacement, however, often involves a risk of dislocation and prosthetic impingement. To minimize the risk after surgery, we propose an instrumented hip prosthesis that estimates the relative pose between prostheses intraoperatively and ensures the placement of prostheses within a safe zone. We create a model of the hip prosthesis as a ball and socket joint, which has four degrees of freedom (DOFs), including 3-DOF rotation and 1-DOF translation. We mount a camera and an inertial measurement unit (IMU) inside the hollow ball, or "femoral head prosthesis," while printing customized patterns on the internal surface of the socket, or "acetabular cup." Since the sensors were rigidly fixed to the femoral head prosthesis, measuring its motions poses a sensor ego-motion estimation problem. By matching feature points in images of the reference patterns, we propose a monocular vision based method with a relative error of less than 7% in the 3-DOF rotation and 8% in the 1-DOF translation. Further, to reduce system power consumption, we apply the IMU with its data fused by an extended Kalman filter to replace the camera in the 3-DOF rotation estimation, which yields a less than 4.8% relative error and a 21.6% decrease in power consumption. Experimental results show that the best approach to prosthesis pose estimation is a combination of monocular vision-based translation estimation and IMU-based rotation estimation, and we have verified the feasibility and validity of this system in prosthesis pose estimation.

  4. Vision-Based Tracking System for Head Motion Correction in FMRI Images

    Science.gov (United States)

    Lerner, Tali; Rivlin, Ehud; Gur, Moshe

    This paper presents a new vision-based system for motion correction in functional-MRI experiments. fMRI is a popular technique for studying brain functionality by utilizing MRI technology. In an fMRI experiment a subject is required to perform a task while his brain is scanned by an MRI scanner. In order to achieve a high quality analysis the fMRI slices should be aligned. Hence, the subject is requested to avoid head movements during the entire experiment. However, due to the long duration of such experiments head motion is practically unavoidable. Most of the previous work in this field addresses this problem by extracting the head motion parameters from the acquired MRI data. Therefore, these works are limited to relatively small movements and may confuse head motion with brain activities. In the present work the head movements are detected by a system comprised of two cameras that monitor a specially designed device worn on the subject's head. The system does not depend on the acquired MRI data and therefore can overcome large head movements. Additionally, the system can be extended to cope with inter-block motion and can be integrated into the MRI scanner for real-time updates of the scan-planes. The performance of the proposed system was tested in a laboratory environment and in fMRI experiments. It was found that high accuracy is obtained even when facing large head movements.

  5. Research on vision-based error detection system for optic fiber winding

    Science.gov (United States)

    Lu, Wenchao; Li, Huipeng; Yang, Dewei; Zhang, Min

    2011-11-01

    Optic fiber coils are the hearts of fiber optic gyroscopes (FOGs). To detect the irresistible errors during the process of winding of optical fibers, such as gaps, climbs and partial rises between fibers, when fiber optic winding machines are operated, and to enable fully automated winding, we researched and designed this vision-based error detection system for optic fiber winding, on the basis of digital image collection and process[1]. When a Fiber-optic winding machine is operated, background light is used as illumination system to strength the contrast of images between fibers and background. Then microscope and CCD as imaging system and image collecting system are used to receive the analog images of fibers. After that analog images are shifted into digital imagines, which can be processed and analyzed by computers. Canny edge detection and a contour-tracing algorithm are used as the main image processing method. The distances between the fiber peaks were then measured and compared with the desired values. If these values fall outside of a predetermined tolerance zone, an error is detected and classified either as a gap, climb or rise. we used OpenCV and MATLAB database as basic function library and used VC++6.0 as the platform to show the results. The test results showed that the system was useful, and the edge detection and contour-tracing algorithm were effective, because of the high rate of accuracy. At the same time, the results of error detection are correct.

  6. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    Energy Technology Data Exchange (ETDEWEB)

    Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  7. Calibrators measurement system for headlamp tester of motor vehicle base on machine vision

    Science.gov (United States)

    Pan, Yue; Zhang, Fan; Xu, Xi-ping; Zheng, Zhe

    2014-09-01

    With the development of photoelectric detection technology, machine vision has a wider use in the field of industry. The paper mainly introduces auto lamps tester calibrator measuring system, of which CCD image sampling system is the core. Also, it shows the measuring principle of optical axial angle and light intensity, and proves the linear relationship between calibrator's facula illumination and image plane illumination. The paper provides an important specification of CCD imaging system. Image processing by MATLAB can get flare's geometric midpoint and average gray level. By fitting the statistics via the method of the least square, we can get regression equation of illumination and gray level. It analyzes the error of experimental result of measurement system, and gives the standard uncertainty of synthesis and the resource of optical axial angle. Optical axial angle's average measuring accuracy is controlled within 40''. The whole testing process uses digital means instead of artificial factors, which has higher accuracy, more repeatability and better mentality than any other measuring systems.

  8. Optical surgical instrument tracking system based on the principle of stereo vision

    Science.gov (United States)

    Zhou, Zhentian; Wu, Bo; Duan, Juan; Zhang, Xu; Zhang, Nan; Liang, Zhiyuan

    2017-06-01

    Optical tracking systems are widely adopted in surgical navigation. An optical tracking system is designed based on the principle of stereo vision with high-precision and low cost. This system uses optical infrared LEDs that are installed on the surgical instrument as markers and a near-infrared filter is added in front of the Bumblebee2 stereo camera lens to eliminate the interference of ambient light. The algorithm based on the region growing method is designed and used for the marker's pixel coordinates' extraction. In this algorithm, the singular points are eliminated and the gray centroid method is applied to solve the pixel coordinate of the marker's center. Then, the marker's matching algorithm is adopted and three-dimensional coordinates' reconstruction is applied to derive the coordinates of the surgical instrument tip in the world coordinate system. In the simulation, the stability, accuracy, rotation tests, and the tracking angle and area range were carried out for a typical surgical instrument and the miniature surgical instrument. The simulation results show that the proposed optical tracking system has high accuracy and stability. It can meet the requirements of surgical navigation.

  9. Human Factors Engineering as a System in the Vision for Exploration

    Science.gov (United States)

    Whitmore, Mihriban; Smith, Danielle; Holden, Kritina

    2006-01-01

    In order to accomplish NASA's Vision for Exploration, while assuring crew safety and productivity, human performance issues must be well integrated into system design from mission conception. To that end, a two-year Technology Development Project (TDP) was funded by NASA Headquarters to develop a systematic method for including the human as a system in NASA's Vision for Exploration. The specific goals of this project are to review current Human Systems Integration (HSI) standards (i.e., industry, military, NASA) and tailor them to selected NASA Exploration activities. Once the methods are proven in the selected domains, a plan will be developed to expand the effort to a wider scope of Exploration activities. The methods will be documented for inclusion in NASA-specific documents (such as the Human Systems Integration Standards, NASA-STD-3000) to be used in future space systems. The current project builds on a previous TDP dealing with Human Factors Engineering processes. That project identified the key phases of the current NASA design lifecycle, and outlined the recommended HFE activities that should be incorporated at each phase. The project also resulted in a prototype of a webbased HFE process tool that could be used to support an ideal HFE development process at NASA. This will help to augment the limited human factors resources available by providing a web-based tool that explains the importance of human factors, teaches a recommended process, and then provides the instructions, templates and examples to carry out the process steps. The HFE activities identified by the previous TDP are being tested in situ for the current effort through support to a specific NASA Exploration activity. Currently, HFE personnel are working with systems engineering personnel to identify HSI impacts for lunar exploration by facilitating the generation of systemlevel Concepts of Operations (ConOps). For example, medical operations scenarios have been generated for lunar habitation

  10. Computer Vision Based Smart Lane Departure Warning System for Vehicle Dynamics Control

    Directory of Open Access Journals (Sweden)

    Ambarish G. Mohapatra

    2011-09-01

    Full Text Available Collision Avoidance System solves many problems caused by traffic congestion worldwide and a synergy of new information technologies for simulation, real-time control and communications networks. The above system is characterized as an intelligent vehicle system. Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Congestion reduces utilization of the transportation infrastructure and increases travel time, air pollution, fuel consumption and most importantly traffic accidents. The main objective of this work is to develop a machine vision system for lane departure detection and warning to measure the lane related parameters such as heading angle, lateral deviation, yaw rate and sideslip angle from the road scene image using standard image processing technique that can be used for automation of steering a motor vehicle. The exact position of the steering wheel can be monitored using a steering wheel sensor. This core part of this work is based on Hough transformation based edge detection technique for the detection of lane departure parameters. The prototype designed for this work has been tested in a running vehicle for the monitoring of real-time lane related parameters.

  11. Computer vision based method and system for online measurement of geometric parameters of train wheel sets.

    Science.gov (United States)

    Zhang, Zhi-Feng; Gao, Zhan; Liu, Yuan-Yuan; Jiang, Feng-Chun; Yang, Yan-Li; Ren, Yu-Fen; Yang, Hong-Jun; Yang, Kun; Zhang, Xiao-Dong

    2012-01-01

    Train wheel sets must be periodically inspected for possible or actual premature failures and it is very significant to record the wear history for the full life of utilization of wheel sets. This means that an online measuring system could be of great benefit to overall process control. An online non-contact method for measuring a wheel set's geometric parameters based on the opto-electronic measuring technique is presented in this paper. A charge coupled device (CCD) camera with a selected optical lens and a frame grabber was used to capture the image of the light profile of the wheel set illuminated by a linear laser. The analogue signals of the image were transformed into corresponding digital grey level values. The 'mapping function method' is used to transform an image pixel coordinate to a space coordinate. The images of wheel sets were captured when the train passed through the measuring system. The rim inside thickness and flange thickness were measured and analyzed. The spatial resolution of the whole image capturing system is about 0.33 mm. Theoretic and experimental results show that the online measurement system based on computer vision can meet wheel set measurement requirements.

  12. Computer Vision Based Method and System for Online Measurement of Geometric Parameters of Train Wheel Sets

    Directory of Open Access Journals (Sweden)

    Hong-Jun Yang

    2011-12-01

    Full Text Available Train wheel sets must be periodically inspected for possible or actual premature failures and it is very significant to record the wear history for the full life of utilization of wheel sets. This means that an online measuring system could be of great benefit to overall process control. An online non-contact method for measuring a wheel set’s geometric parameters based on the opto-electronic measuring technique is presented in this paper. A charge coupled device (CCD camera with a selected optical lens and a frame grabber was used to capture the image of the light profile of the wheel set illuminated by a linear laser. The analogue signals of the image were transformed into corresponding digital grey level values. The ‘mapping function method’ is used to transform an image pixel coordinate to a space coordinate. The images of wheel sets were captured when the train passed through the measuring system. The rim inside thickness and flange thickness were measured and analyzed. The spatial resolution of the whole image capturing system is about 0.33 mm. Theoretic and experimental results show that the online measurement system based on computer vision can meet wheel set measurement requirements.

  13. An inexpensive Arduino-based LED stimulator system for vision research.

    Science.gov (United States)

    Teikari, Petteri; Najjar, Raymond P; Malkki, Hemi; Knoblauch, Kenneth; Dumortier, Dominique; Gronfier, Claude; Cooper, Howard M

    2012-11-15

    Light emitting diodes (LEDs) are being used increasingly as light sources in life sciences applications such as in vision research, fluorescence microscopy and in brain-computer interfacing. Here we present an inexpensive but effective visual stimulator based on light emitting diodes (LEDs) and open-source Arduino microcontroller prototyping platform. The main design goal of our system was to use off-the-shelf and open-source components as much as possible, and to reduce design complexity allowing use of the system to end-users without advanced electronics skills. The main core of the system is a USB-connected Arduino microcontroller platform designed initially with a specific emphasis on the ease-of-use creating interactive physical computing environments. The pulse-width modulation (PWM) signal of Arduino was used to drive LEDs allowing linear light intensity control. The visual stimulator was demonstrated in applications such as murine pupillometry, rodent models for cognitive research, and heterochromatic flicker photometry in human psychophysics. These examples illustrate some of the possible applications that can be easily implemented and that are advantageous for students, educational purposes and universities with limited resources. The LED stimulator system was developed as an open-source project. Software interface was developed using Python with simplified examples provided for Matlab and LabVIEW. Source code and hardware information are distributed under the GNU General Public Licence (GPL, version 3). Copyright © 2012 Elsevier B.V. All rights reserved.

  14. 5G: Vision and Requirements for Mobile Communication System towards Year 2020

    Directory of Open Access Journals (Sweden)

    Guangyi Liu

    2016-01-01

    Full Text Available The forecast for future 10 years’ traffic demand shows an increase in 1000 scales and more than 100 billion connections of Internet of Things, which imposes a big challenge for future mobile communication technology beyond year 2020. The mobile industry is struggling in the challenges of high capacity demand but low cost for future mobile network when it starts to enable a connected mobile world. 5G is targeted to shed light on these contradictory demands towards year 2020. This paper firstly forecasts the vision of mobile communication’s application in the daily life of the society and then figures out the traffic trends and demands for next 10 years from the Mobile Broadband (MBB service and Internet of Things (IoT perspective, respectively. The requirements from the specific service and user demands are analyzed, and the specific requirements from typical usage scenarios are calculated by the defined performance indicators. To achieve the target of affordable 5G service, the requirements from network deployment and operation perspective are also captured. Finally, the capabilities and the efficiency requirements of the 5G system are demonstrated as a flower. To realize the vision of 5G, “information a finger away, everything in touch,” 5G will provide the fiber-like access data rate, “zero” latency user experience, and connecting to more than 100 billion devices and deliver a consistent experience across a variety of scenarios with the improved energy and cost efficiency by over a hundred of times.

  15. External Vision Systems (XVS) Proof-of-Concept Flight Test Evaluation

    Science.gov (United States)

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

    2014-01-01

    NASA's Fundamental Aeronautics Program, High Speed Project is performing research, development, test and evaluation of flight deck and related technologies to support future low-boom, supersonic configurations (without forward-facing windows) by use of an eXternal Vision System (XVS). The challenge of XVS is to determine a combination of sensor and display technologies which can provide an equivalent level of safety and performance to that provided by forward-facing windows in today's aircraft. This flight test was conducted with the goal of obtaining performance data on see-and-avoid and see-to-follow traffic using a proof-of-concept XVS design in actual flight conditions. Six data collection flights were flown in four traffic scenarios against two different sized participating traffic aircraft. This test utilized a 3x1 array of High Definition (HD) cameras, with a fixed forward field-of-view, mounted on NASA Langley's UC-12 test aircraft. Test scenarios, with participating NASA aircraft serving as traffic, were presented to two evaluation pilots per flight - one using the proof-of-concept (POC) XVS and the other looking out the forward windows. The camera images were presented on the XVS display in the aft cabin with Head-Up Display (HUD)-like flight symbology overlaying the real-time imagery. The test generated XVS performance data, including comparisons to natural vision, and post-run subjective acceptability data were also collected. This paper discusses the flight test activities, its operational challenges, and summarizes the findings to date.

  16. Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity.

    Science.gov (United States)

    Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping

    2016-01-01

    Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture.

  17. Application of 3DHiVision: a system with a new 3D HD renderer

    Science.gov (United States)

    Sun, Peter; Nagata, Shojiro

    2006-02-01

    This paper discusses about some technology breakthroughs to help solve the difficulties that have been clogging the popularity of 3D Stereo. We name this 3DHiVision (3DHV) System Solution. With the advance in technology, modern projection systems and stereo LCD panels have made it possible for a lot more people to enjoy a 3D stereo video experience in a broader range of applications. However, the key limitations to more mainstream applications of 3D video have been the availability of 3D contents and the cost and the complexity of 3D video production, content management and playback systems. With the easy availability of the modern PC based video production tools, advance in the technology of the projection systems and the great interest highly increased in 3D applications, the 3D video industry still remains stagnant and restricted within a small scale. It is because the amount of the cost for the production and playback of high quality 3D video has always been to such an extent that it challenges the limitations of our imagination. Great as these difficulties seem to be, we have surmounted them all and created a complete end-to-end 3DHiVision (3DHV for short) Video system based on an embedded PC platform, which significantly reduces the cost and complexity of creating museum quality 3D video. With this achievement, professional film makers and amateurs as well will be able to easily create, distribute and playback 3D video contents. The HD-Renderer is the central component in our 3DHV solution line. It is a highly efficient software capable of decrypting, decoding, dynamically parallax adjusting and rendering HD video contents up to 1920x1080x2x30p in real-time on an embedded PC (for theaters) or any other home PC (for main stream) with the 3.0GHz P4 CPU / GeForce6600GT GPU hardware requirements or above. And the 1280x720x2x30p contents can be performed with great ease on a notebook with 1.7GHz P4Mobile CPU / GeForce6200 GPU at the time when this paper is written.

  18. An information assistant system for the prevention of tunnel vision in crisis management

    NARCIS (Netherlands)

    Cao, Y.

    2008-01-01

    In the crisis management environment, tunnel vision is a set of bias in decision makers’ cognitive process which often leads to incorrect understanding of the real crisis situation, biased perception of information, and improper decisions. The tunnel vision phenomenon is a consequence of both the

  19. Polymer-electrolyte-gated nanowire synaptic transistors for neuromorphic applications

    Science.gov (United States)

    Zou, Can; Sun, Jia; Gou, Guangyang; Kong, Ling-An; Qian, Chuan; Dai, Guozhang; Yang, Junliang; Guo, Guang-hua

    2017-09-01

    Polymer-electrolytes are formed by dissolving a salt in polymer instead of water, the conducting mechanism involves the segmental motion-assisted diffusion of ion in the polymer matrix. Here, we report on the fabrication of tin oxide (SnO2) nanowire synaptic transistors using polymer-electrolyte gating. A thin layer of poly(ethylene oxide) and lithium perchlorate (PEO/LiClO4) was deposited on top of the devices, which was used to boost device performances. A voltage spike applied on the in-plane gate attracts ions toward the polymer-electrolyte/SnO2 nanowire interface and the ions are gradually returned after the pulse is removed, which can induce a dynamic excitatory postsynaptic current in the nanowire channel. The SnO2 synaptic transistors exhibit the behavior of short-term plasticity like the paired-pulse facilitation and self-adaptation, which is related to the electric double-effect regulation. In addition, the synaptic logic functions and the logical function transformation are also discussed. Such single SnO2 nanowire-based synaptic transistors are of great importance for future neuromorphic devices.

  20. Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications

    Directory of Open Access Journals (Sweden)

    Francesca Sorgini

    2018-01-01

    Full Text Available We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland. In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency–mimetic neuronal models, and can be useful for the design of high performance haptic devices.

  1. Self-localization for an autonomous mobile robot based on an omni-directional vision system

    Science.gov (United States)

    Chiang, Shu-Yin; Lin, Kuang-Yu; Chia, Tsorng-Lin

    2013-12-01

    In this study, we designed an autonomous mobile robot based on the rules of the Federation of International Robotsoccer Association (FIRA) RoboSot category, integrating the techniques of computer vision, real-time image processing, dynamic target tracking, wireless communication, self-localization, motion control, path planning, and control strategy to achieve the contest goal. The self-localization scheme of the mobile robot is based on the algorithms featured in the images from its omni-directional vision system. In previous works, we used the image colors of the field goals as reference points, combining either dual-circle or trilateration positioning of the reference points to achieve selflocalization of the autonomous mobile robot. However, because the image of the game field is easily affected by ambient light, positioning systems exclusively based on color model algorithms cause errors. To reduce environmental effects and achieve the self-localization of the robot, the proposed algorithm is applied in assessing the corners of field lines by using an omni-directional vision system. Particularly in the mid-size league of the RobotCup soccer competition, selflocalization algorithms based on extracting white lines from the soccer field have become increasingly popular. Moreover, white lines are less influenced by light than are the color model of the goals. Therefore, we propose an algorithm that transforms the omni-directional image into an unwrapped transformed image, enhancing the extraction features. The process is described as follows: First, radical scan-lines were used to process omni-directional images, reducing the computational load and improving system efficiency. The lines were radically arranged around the center of the omni-directional camera image, resulting in a shorter computational time compared with the traditional Cartesian coordinate system. However, the omni-directional image is a distorted image, which makes it difficult to recognize the

  2. A Vision-Based Automated Guided Vehicle System with Marker Recognition for Indoor Use

    Science.gov (United States)

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-01-01

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system. PMID:23966180

  3. Synthetic and Enhanced Vision Systems for NextGen (SEVS) Simulation and Flight Test Performance Evaluation

    Science.gov (United States)

    Shelton, Kevin J.; Kramer, Lynda J.; Ellis,Kyle K.; Rehfeld, Sherri A.

    2012-01-01

    The Synthetic and Enhanced Vision Systems for NextGen (SEVS) simulation and flight tests are jointly sponsored by NASA's Aviation Safety Program, Vehicle Systems Safety Technology project and the Federal Aviation Administration (FAA). The flight tests were conducted by a team of Honeywell, Gulfstream Aerospace Corporation and NASA personnel with the goal of obtaining pilot-in-the-loop test data for flight validation, verification, and demonstration of selected SEVS operational and system-level performance capabilities. Nine test flights (38 flight hours) were conducted over the summer and fall of 2011. The evaluations were flown in Gulfstream.s G450 flight test aircraft outfitted with the SEVS technology under very low visibility instrument meteorological conditions. Evaluation pilots flew 108 approaches in low visibility weather conditions (600 ft to 2400 ft visibility) into various airports from Louisiana to Maine. In-situ flight performance and subjective workload and acceptability data were collected in collaboration with ground simulation studies at LaRC.s Research Flight Deck simulator.

  4. A vision-based automated guided vehicle system with marker recognition for indoor use.

    Science.gov (United States)

    Lee, Jeisung; Hyun, Chang-Ho; Park, Mignon

    2013-08-07

    We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

  5. A Vision-Based Automated Guided Vehicle System with Marker Recognition for Indoor Use

    Directory of Open Access Journals (Sweden)

    Jeisung Lee

    2013-08-01

    Full Text Available We propose an intelligent vision-based Automated Guided Vehicle (AGV system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird’s eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.

  6. Japan's universal long-term care system reform of 2005: containing costs and realizing a vision.

    Science.gov (United States)

    Tsutsui, Takako; Muramatsu, Naoko

    2007-09-01

    Japan implemented a mandatory social long-term care insurance (LTCI) system in 2000, making long-term care services a universal entitlement for every senior. Although this system has grown rapidly, reflecting its popularity among seniors and their families, it faces several challenges, including skyrocketing costs. This article describes the recent reform initiated by the Japanese government to simultaneously contain costs and realize a long-term vision of creating a community-based, prevention-oriented long-term care system. The reform involves introduction of two major elements: "hotel" and meal charges for nursing home residents and new preventive benefits. They were intended to reduce economic incentives for institutionalization, dampen provider-induced demand, and prevent seniors from being dependent by intervening while their need levels are still low. The ongoing LTCI reform should be critically evaluated against the government's policy intentions as well as its effect on seniors, their families, and society. The story of this reform is instructive for other countries striving to develop coherent, politically acceptable long-term care policies.

  7. Information theory analysis of sensor-array imaging systems for computer vision

    Science.gov (United States)

    Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.; Self, M. O.

    1983-01-01

    Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

  8. A vision-based material tracking system for heavy plate rolling mills

    Science.gov (United States)

    Tratnig, Mark; Reisinger, Johann; Hlobil, Helmut

    2007-01-01

    A modern heavy plate rolling mill can process more than 20 slabs and plates simultaneously. To avoid material confusions during a compact occupancy and the permanent discharging and re-entering of parts, one must know the identity and position of each part at every moment. One possibility to determine the identity and position of each slab and plate is the application of a comprehensive visual-based tracking system. Compared to a tracking system that calculates the position of a plate based on the diameter and the turns of the transport rolls, a visual system is not corrupted by a position- and material dependent transmission slip. In this paper we therefore present a vision-based material tracking system for the 2-dimensional tracking of glowing material in harsh environment. It covers the production area from the plant's descaler to the pre-stand of the rolling mill and consists of four independent, synchronized overlapping cameras. The paper first presents the conceptual design of the tracking system - and continues then with the camera calibration, the determination of pixel contours, the data segmentation and the fitting & modelling of the objects bodies. In a next step, the work will then show the testing setup. It will be described how the material tracking system was implemented into the control system of the rolling mill and how the delivered tracking data was checked on its correctness. Finally, the paper presents some results. It will be shown that the position of some moving plates was estimated with a precision of approx. 0.5m. The results will be analyzed and it will be explained where the inaccuracies come from and how they eventually can be removed. The paper ends with a conclusion and an outlook on future work.

  9. Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems

    Directory of Open Access Journals (Sweden)

    Amedeo Rodi Vetrella

    2016-12-01

    Full Text Available Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS receivers and Micro-Electro-Mechanical Systems (MEMS-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

  10. Vision Screening

    Science.gov (United States)

    ... Corneal Abrasions Dilating Eye Drops Lazy eye (defined) Pink eye (defined) Retinopathy of Prematurity Strabismus Stye (defined) Vision ... Corneal Abrasions Dilating Eye Drops Lazy eye (defined) Pink eye (defined) Retinopathy of Prematurity Strabismus Stye (defined) Vision ...

  11. Performance of the CellaVision ® DM96 system for detecting red blood cell morphologic abnormalities

    Directory of Open Access Journals (Sweden)

    Christopher L Horn

    2015-01-01

    Full Text Available Background: Red blood cell (RBC analysis is a key feature in the evaluation of hematological disorders. The gold standard light microscopy technique has high sensitivity, but is a relativity time-consuming and labor intensive procedure. This study tested the sensitivity and specificity of gold standard light microscopy manual differential to the CellaVision ® DM96 (CCS; CellaVision, Lund, Sweden automated image analysis system, which takes digital images of samples at high magnification and compares these images with an artificial neural network based on a database of cells and preclassified according to RBC morphology. Methods: In this study, 212 abnormal peripheral blood smears within the Calgary Laboratory Services network of hospital laboratories were selected and assessed for 15 different RBC morphologic abnormalities by manual microscopy. The same samples were reassessed as a manual addition from the instrument screen using the CellaVision ® DM96 system with 8 microscope high power fields (×100 objective and a 22 mm ocular. The results of the investigation were then used to calculate the sensitivity and specificity of the CellaVision ® DM96 system in reference to light microscopy. Results: The sensitivity ranged from a low of 33% (RBC agglutination to a high of 100% (sickle cells, stomatocytes. The remainder of the RBC abnormalities tested somewhere between these two extremes. The specificity ranged from 84% (schistocytes to 99.5% (sickle cells, stomatocytes. Conclusions: Our results showed generally high specificities but variable sensitivities for RBC morphologic abnormalities.

  12. Mathematical leadership vision.

    Science.gov (United States)

    Hamburger, Y A

    2000-11-01

    This article is an analysis of a new type of leadership vision, the kind of vision that is becoming increasingly pervasive among leaders in the modern world. This vision appears to offer a new horizon, whereas, in fact it delivers to its target audience a finely tuned version of the already existing ambitions and aspirations of the target audience. The leader, with advisors, has examined the target audience and has used the results of extensive research and statistical methods concerning the group to form a picture of its members' lifestyles and values. On the basis of this information, the leader has built a "vision." The vision is intended to create an impression of a charismatic and transformational leader when, in fact, it is merely a response. The systemic, arithmetic, and statistical methods employed in this operation have led to the coining of the terms mathematical leader and mathematical vision.

  13. Robotic goalie with 3 ms reaction time at 4% CPU load using event-based dynamic vision sensor.

    Science.gov (United States)

    Delbruck, Tobi; Lang, Manuel

    2013-01-01

    Conventional vision-based robotic systems that must operate quickly require high video frame rates and consequently high computational costs. Visual response latencies are lower-bound by the frame period, e.g., 20 ms for 50 Hz frame rate. This paper shows how an asynchronous neuromorphic dynamic vision sensor (DVS) silicon retina is used to build a fast self-calibrating robotic goalie, which offers high update rates and low latency at low CPU load. Independent and asynchronous per pixel illumination change events from the DVS signify moving objects and are used in software to track multiple balls. Motor actions to block the most "threatening" ball are based on measured ball positions and velocities. The goalie also sees its single-axis goalie arm and calibrates the motor output map during idle periods so that it can plan open-loop arm movements to desired visual locations. Blocking capability is about 80% for balls shot from 1 m from the goal even with the fastest-shots, and approaches 100% accuracy when the ball does not beat the limits of the servo motor to move the arm to the necessary position in time. Running with standard USB buses under a standard preemptive multitasking operating system (Windows), the goalie robot achieves median update rates of 550 Hz, with latencies of 2.2 ± 2 ms from ball movement to motor command at a peak CPU load of less than 4%. Practical observations and measurements of USB device latency are provided.

  14. Robotic Goalie with 3ms Reaction Time at 4% CPU Load Using Event-Based Dynamic Vision Sensor

    Directory of Open Access Journals (Sweden)

    Tobi eDelbruck

    2013-11-01

    Full Text Available Conventional vision-based robotic systems that must operate quickly require high video frame rates and consequently high computational costs. Visual response latencies are lower-bound by the frame period, e.g. 20 ms for 50 Hz frame rate. This paper shows how an asynchronous neuromorphic dynamic vision sensor (DVS silicon retina is used to build a fast self-calibrating robotic goalie, which offers high update rates and low latency at low CPU load. Independent and asynchronous per pixel illumination change events from the DVS signify moving objects and are used in software to track multiple balls. Motor actions to block the most threatening ball are based on measured ball positions and velocities. The goalie also sees its single-axis goalie arm and calibrates the motor output map during idle periods so that it can plan open-loop arm movements to desired visual locations. Blocking capability is about 80% for balls shot from 1m from the goal even with the fastest shots, and approaches 100% accuracy when the ball does not beat the limits of the servo motor to move the arm to the necessary position in time. Running with standard USB buses under a standard preemptive multitasking operating system (Windows, the goalie robot achieves median update rates of 550 Hz, with latencies of 2.2+/-2ms from ball movement to motor command at a peak CPU load of less than 4%. Practical observations and measurements of USB device latency are provided.

  15. Vision-based interaction

    CERN Document Server

    Turk, Matthew

    2013-01-01

    In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, there has been an increasing interest in computer vision as an input modality in the context of human-computer interaction. Such vision-based interaction can endow interactive systems with visual capabilities similar to those important to human-human interaction, in order to perceive non-verbal cues and incorporate this information in applications such

  16. Computational vision

    CERN Document Server

    Wechsler, Harry

    1990-01-01

    The book is suitable for advanced courses in computer vision and image processing. In addition to providing an overall view of computational vision, it contains extensive material on topics that are not usually covered in computer vision texts (including parallel distributed processing and neural networks) and considers many real applications.

  17. An advanced vision-based system for real-time displacement measurement of high-rise buildings

    Science.gov (United States)

    Lee, Jong-Han; Ho, Hoai-Nam; Shinozuka, Masanobu; Lee, Jong-Jae

    2012-12-01

    This paper introduces an advanced vision-based system for dynamic real-time displacement measurement of high-rise buildings using a partitioning approach. The partitioning method is based on the successive estimation of relative displacements and rotational angles at several floors using a multiple vision-based displacement measurement system. In this study, two significant improvements were made to realize the partitioning method: (1) time synchronization, (2) real-time dynamic measurement. Displacement data and time synchronization information are wirelessly transferred via a network using the TCP/IP protocol. The time synchronization process is periodically conducted by the master system to guarantee the system time at the master and slave systems are synchronized. The slave system is capable of dynamic real-time measurement and it is possible to economically expand measurement points at slave levels using commercial devices. To verify the accuracy and feasibility of the synchronized multi-point vision-based system and partitioning approach, many laboratory tests were carried out on a three-story steel frame model. Furthermore, several tests were conducted on a five-story steel frame tower equipped with a hybrid mass damper to experimentally confirm the effectiveness of the proposed system.

  18. Vision-aided system for obtaining a required weight by efficient choice of irregular fragments

    Directory of Open Access Journals (Sweden)

    Francisco Sánchez Niño

    2017-04-01

    Full Text Available There are some situations when it is necessary to weigh, with high accuracy and high precision, a required amount of material using heterogeneous and irregular pieces. As an example, in the laboratory, when preparing a liquid phase epitaxial growth, each of the materials that constitute the liquid phase must have an exact weight, within micrograms, given by the phase diagrams. The sources of the materials usually are small polycrystalline pieces of irregular shapes and random weights. Normally the weighing is done by interchanging the small irregular pieces of different sizes according to the criteria of the operator until the given weight is obtained. This is a long and tedious process and since each liquid solution requires several components, and a different liquid phase is needed for each layer, very often weighing it takes several hours. This operative process is prone to errors. To ease this kind of processes, a vision-assisted system has been developed. It consists of a webcam, an analytical balance and a PC. To use this assembly the operator only needs to put sequentially the pieces of the material in the analytical balance. When the required weight can be obtained by a combination of some of the pieces added to the analytic balance, the PC notifies the operator and signals the selected pieces in the screen. With the help of this system, the weighing accuracy has been improved and the time required to accomplish the process has been dramatically reduced.

  19. Smart tissue anastomosis robot (STAR): a vision-guided robotics system for laparoscopic suturing.

    Science.gov (United States)

    Leonard, Simon; Wu, Kyle L; Kim, Yonjae; Krieger, Axel; Kim, Peter C W

    2014-04-01

    This paper introduces the smart tissue anastomosis robot (STAR). Currently, the STAR is a proof-of-concept for a vision-guided robotic system featuring an actuated laparoscopic suturing tool capable of executing running sutures from image-based commands. The STAR tool is designed around a commercially available laparoscopic suturing tool that is attached to a custom-made motor stage and the STAR supervisory control architecture that enables a surgeon to select and track incisions and the placement of stitches. The STAR supervisory-control interface provides two modes: A manual mode that enables a surgeon to specify the placement of each stitch and an automatic mode that automatically computes equally-spaced stitches based on an incision contour. Our experiments on planar phantoms demonstrate that the STAR in either mode is more accurate, up to four times more consistent and five times faster than surgeons using state-of-the-art robotic surgical system, four times faster than surgeons using manual Endo360(°)®, and nine times faster than surgeons using manual laparoscopic tools.

  20. Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants

    Directory of Open Access Journals (Sweden)

    Pedro J. Navarro

    2016-05-01

    Full Text Available Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We present a system based on machine learning (ML algorithms and computer vision intended to solve the automatic phenotype data analysis in plant material. We developed a growth-chamber able to accommodate species of various sizes. Night image acquisition requires near infrared lightning. For the ML process, we tested three different algorithms: k-nearest neighbour (kNN, Naive Bayes Classifier (NBC, and Support Vector Machine. Each ML algorithm was executed with different kernel functions and they were trained with raw data and two types of data normalisation. Different metrics were computed to determine the optimal configuration of the machine learning algorithms. We obtained a performance of 99.31% in kNN for RGB images and a 99.34% in SVM for NIR. Our results show that ML techniques can speed up phenomic data analysis. Furthermore, both RGB and NIR images can be segmented successfully but may require different ML algorithms for segmentation.

  1. Grain classifier with computer vision using adaptive neuro-fuzzy inference system.

    Science.gov (United States)

    Sabanci, Kadir; Toktas, Abdurrahim; Kayabasi, Ahmet

    2017-09-01

    A computer vision-based classifier using an adaptive neuro-fuzzy inference system (ANFIS) is designed for classifying wheat grains into bread or durum. To train and test the classifier, images of 200 wheat grains (100 for bread and 100 for durum) are taken by a high-resolution camera. Visual feature data of the grains related to dimension (#4), color (#3) and texture (#5) as inputs of the classifier are mainly acquired for each grain using image processing techniques (IPTs). In addition to these main data, nine features are reproduced from the main features to ensure a varied population. Thus four sub-sets including categorized features of reproduced data are constituted to examine their effects on the classification. In order to simplify the classifier, the most effective visual features on the results are investigated. The data sets are compared with each other regarding classification accuracy. A simplified classifier having seven selected features is achieved with the best results. In the testing process, the simplified classifier computes the output with 99.46% accuracy and assorts the wheat grains with 100% accuracy. A system which classifies wheat grains with higher accuracy is designed. The proposed classifier integrated to industrial applications can automatically classify a variety of wheat grains. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  2. Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants.

    Science.gov (United States)

    Navarro, Pedro J; Pérez, Fernando; Weiss, Julia; Egea-Cortines, Marcos

    2016-05-05

    Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We present a system based on machine learning (ML) algorithms and computer vision intended to solve the automatic phenotype data analysis in plant material. We developed a growth-chamber able to accommodate species of various sizes. Night image acquisition requires near infrared lightning. For the ML process, we tested three different algorithms: k-nearest neighbour (kNN), Naive Bayes Classifier (NBC), and Support Vector Machine. Each ML algorithm was executed with different kernel functions and they were trained with raw data and two types of data normalisation. Different metrics were computed to determine the optimal configuration of the machine learning algorithms. We obtained a performance of 99.31% in kNN for RGB images and a 99.34% in SVM for NIR. Our results show that ML techniques can speed up phenomic data analysis. Furthermore, both RGB and NIR images can be segmented successfully but may require different ML algorithms for segmentation.

  3. A New High-Speed Foreign Fiber Detection System with Machine Vision

    Directory of Open Access Journals (Sweden)

    Zhiguo Chen

    2010-01-01

    Full Text Available A new high-speed foreign fiber detection system with machine vision is proposed for removing foreign fibers from raw cotton using optimal hardware components and appropriate algorithms designing. Starting from a specialized lens of 3-charged couple device (CCD camera, the system applied digital signal processor (DSP and field-programmable gate array (FPGA on image acquisition and processing illuminated by ultraviolet light, so as to identify transparent objects such as polyethylene and polypropylene fabric from cotton tuft flow by virtue of the fluorescent effect, until all foreign fibers that have been blown away safely by compressed air quality can be achieved. An image segmentation algorithm based on fast wavelet transform is proposed to identify block-like foreign fibers, and an improved canny detector is also developed to segment wire-like foreign fibers from raw cotton. The procedure naturally provides color image segmentation method with region growing algorithm for better adaptability. Experiments on a variety of images show that the proposed algorithms can effectively segment foreign fibers from test images under various circumstances.

  4. Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

    Science.gov (United States)

    Kasabov, Nikola; Scott, Nathan Matthew; Tu, Enmei; Marks, Stefan; Sengupta, Neelava; Capecci, Elisa; Othman, Muhaini; Doborjeh, Maryam Gholami; Murli, Norhanifah; Hartono, Reggio; Espinosa-Ramos, Josafath Israel; Zhou, Lei; Alvi, Fahad Bashir; Wang, Grace; Taylor, Denise; Feigin, Valery; Gulyaev, Sergei; Mahmoud, Mahmoud; Hou, Zeng-Guang; Yang, Jie

    2016-06-01

    The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this is presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM. Copyright © 2015 Elsevier Ltd. All rights reserved.

  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

  6. Sound stream segregation: a neuromorphic approach to solve the ‘cocktail party problem’ in real-time

    Directory of Open Access Journals (Sweden)

    Chetan Singh Thakur

    2015-09-01

    Full Text Available 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

  7. Object tracking with stereo vision

    Science.gov (United States)

    Huber, Eric

    1994-01-01

    A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking.

  8. A vision for an ultra-high resolution integrated water cycle observation and prediction system

    Science.gov (United States)

    Houser, P. R.

    2013-05-01

    biomass would improve soil-moisture retrieval by avoiding the need for auxiliary vegetation information. This multivariable water-cycle observation system must be integrated with high-resolution, application relevant prediction systems to optimize their information content and utility is addressing critical water cycle issues. One such vision is a real-time ultra-high resolution locally-moasiced global land modeling and assimilation system, that overlays regional high-fidelity information over a baseline global land prediction system. Such a system would provide the best possible local information for use in applications, while integrating and sharing information globally for diagnosing larger water cycle variability. In a sense, this would constitute a hydrologic telecommunication system, where the best local in-situ gage, Doppler radar, and weather station can be shared internationally, and integrated in a consistent manner with global observation platforms like the multivariable water cycle mission. To realize such a vision, large issues must be addressed, such as international data sharing policy, model-observation integration approaches that maintain local extremes while achieving global consistency, and methods for establishing error estimates and uncertainty.

  9. Virtual expansion of the technical vision system for smart vehicles based on multi-agent cooperation model

    Science.gov (United States)

    Krapukhina, Nina; Senchenko, Roman; Kamenov, Nikolay

    2017-12-01

    Road safety and driving in dense traffic flows poses some challenges in receiving information about surrounding moving object, some of which can be in the vehicle's blind spot. This work suggests an approach to virtual monitoring of the objects in a current road scene via a system with a multitude of cooperating smart vehicles exchanging information. It also describes the intellectual agent model, and provides methods and algorithms of identifying and evaluating various characteristics of moving objects in video flow. Authors also suggest ways for integrating the information from the technical vision system into the model with further expansion of virtual monitoring for the system's objects. Implementation of this approach can help to expand the virtual field of view for a technical vision system.

  10. Application of the Modular Automated Reconfigurable Assembly System (MARAS) concept to adaptable vision gauging and parts feeding

    Science.gov (United States)

    By, Andre Bernard; Caron, Ken; Rothenberg, Michael; Sales, Vic

    1994-01-01

    This paper presents the first phase results of a collaborative effort between university researchers and a flexible assembly systems integrator to implement a comprehensive modular approach to flexible assembly automation. This approach, named MARAS (Modular Automated Reconfigurable Assembly System), has been structured to support multiple levels of modularity in terms of both physical components and system control functions. The initial focus of the MARAS development has been on parts gauging and feeding operations for cylinder lock assembly. This phase is nearing completion and has resulted in the development of a highly configurable system for vision gauging functions on a wide range of small components (2 mm to 100 mm in size). The reconfigurable concepts implemented in this adaptive Vision Gauging Module (VGM) are now being extended to applicable aspects of the singulating, selecting, and orienting functions required for the flexible feeding of similar mechanical components and assemblies.

  11. Machine Vision Handbook

    CERN Document Server

    2012-01-01

    The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

  12. A vision-based tool for the control of hydraulic structures in sewer systems

    Science.gov (United States)

    Nguyen, L.; Sage, D.; Kayal, S.; Jeanbourquin, D.; Rossi, L.

    2009-04-01

    monitoring software has the following requirements: visual analysis of particular hydraulic behavior, automatic vision-based flow measurements, automatic alarm system for particular events (overflows, risk of flooding, etc), database for data management (images, events, measurements, etc.), ability to be controlled remotely. The software is implemented in modular server/client architecture under LabVIEW development system. We have conducted conclusive in situ tests in various sewers configurations (CSOs, storm-water sewerage, WWTP); they have shown the ability of the HydroPix to perform accurate monitoring of hydraulic structures. Visual information demonstrated a better understanding of the flow behavior in complex and difficult environment.

  13. Mechatronic Development and Vision Feedback Control of a Nanorobotics Manipulation System inside SEM for Nanodevice Assembly

    Directory of Open Access Journals (Sweden)

    Zhan Yang

    2016-09-01

    Full Text Available Carbon nanotubes (CNT have been developed in recent decades for nanodevices such as nanoradios, nanogenerators, carbon nanotube field effect transistors (CNTFETs and so on, indicating that the application of CNTs for nanoscale electronics may play a key role in the development of nanotechnology. Nanorobotics manipulation systems are a promising method for nanodevice construction and assembly. For the purpose of constructing three-dimensional CNTFETs, a nanorobotics manipulation system with 16 DOFs was developed for nanomanipulation of nanometer-scale objects inside the specimen chamber of a scanning electron microscope (SEM. Nanorobotics manipulators are assembled into four units with four DOFs (X-Y-Z-θ individually. The rotational one is actuated by a picomotor. That means a manipulator has four DOFs including three linear motions in the X, Y, Z directions and a 360-degree rotational one (X-Y-Z-θ stage, θ is along the direction rotating with X or Y axis. Manipulators are actuated by picomotors with better than 30 nm linear resolution and <1 micro-rad rotary resolution. Four vertically installed AFM cantilevers (the axis of the cantilever tip is vertical to the axis of electronic beam of SEM served as the end-effectors to facilitate the real-time observation of the operations. A series of kinematic derivations of these four manipulators based on the Denavit-Hartenberg (D-H notation were established. The common working space of the end-effectors is 2.78 mm by 4.39 mm by 6 mm. The manipulation strategy and vision feedback control for multi-manipulators operating inside the SEM chamber were been discussed. Finally, application of the designed nanorobotics manipulation system by successfully testing of the pickup-and-place manipulation of an individual CNT onto four probes was described. The experimental results have shown that carbon nanotubes can be successfully picked up with this nanorobotics manipulation system.

  14. A real-time vision-based hand gesture interaction system for virtual EAST

    Energy Technology Data Exchange (ETDEWEB)

    Wang, K.R., E-mail: wangkr@mail.ustc.edu.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Xiao, B.J.; Xia, J.Y. [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); University of Science and Technology of China, Hefei, Anhui (China); Li, Dan [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Luo, W.L. [709th Research Institute, Shipbuilding Industry Corporation (China)

    2016-11-15

    Highlights: • Hand gesture interaction is first introduced to EAST model interaction. • We can interact with EAST model by a bared hand and a web camera. • We can interact with EAST model with a distance to screen. • Interaction is free, direct and effective. - Abstract: The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

  15. Mechatronic Development and Vision Feedback Control of a Nanorobotics Manipulation System inside SEM for Nanodevice Assembly.

    Science.gov (United States)

    Yang, Zhan; Wang, Yaqiong; Yang, Bin; Li, Guanghui; Chen, Tao; Nakajima, Masahiro; Sun, Lining; Fukuda, Toshio

    2016-09-14

    Carbon nanotubes (CNT) have been developed in recent decades for nanodevices such as nanoradios, nanogenerators, carbon nanotube field effect transistors (CNTFETs) and so on, indicating that the application of CNTs for nanoscale electronics may play a key role in the development of nanotechnology. Nanorobotics manipulation systems are a promising method for nanodevice construction and assembly. For the purpose of constructing three-dimensional CNTFETs, a nanorobotics manipulation system with 16 DOFs was developed for nanomanipulation of nanometer-scale objects inside the specimen chamber of a scanning electron microscope (SEM). Nanorobotics manipulators are assembled into four units with four DOFs (X-Y-Z-θ) individually. The rotational one is actuated by a picomotor. That means a manipulator has four DOFs including three linear motions in the X, Y, Z directions and a 360-degree rotational one (X-Y-Z-θ stage, θ is along the direction rotating with X or Y axis). Manipulators are actuated by picomotors with better than 30 nm linear resolution and <1 micro-rad rotary resolution. Four vertically installed AFM cantilevers (the axis of the cantilever tip is vertical to the axis of electronic beam of SEM) served as the end-effectors to facilitate the real-time observation of the operations. A series of kinematic derivations of these four manipulators based on the Denavit-Hartenberg (D-H) notation were established. The common working space of the end-effectors is 2.78 mm by 4.39 mm by 6 mm. The manipulation strategy and vision feedback control for multi-manipulators operating inside the SEM chamber were been discussed. Finally, application of the designed nanorobotics manipulation system by successfully testing of the pickup-and-place manipulation of an individual CNT onto four probes was described. The experimental results have shown that carbon nanotubes can be successfully picked up with this nanorobotics manipulation system.

  16. Computer vision-guided robotic system for electrical power lines maintenance

    Science.gov (United States)

    Tremblay, Jack; Laliberte, T.; Houde, Regis; Pelletier, Michel; Gosselin, Clement M.; Laurendeau, Denis

    1995-12-01

    The paper presents several modules of a computer vision assisted robotic system for the maintenance of live electrical power lines. The basic scene of interest is composed of generic components such as a crossarm, a power line and a porcelain insulator. The system is under the supervision of an operator which validates each subtask. The system uses a 3D range finder mounted at the end effector of a 6 dof manipulator for the acquisition of range data on the scene. Since more than one view is required to obtain enough information on the scene, a view integration procedure is applied to the data in order to merge the information in a single reference frame. A volumetric description of the scene, in this case an octree, is built using the range data. The octree is transformed into an occupancy grid which is used for avoiding collisions between the manipulator and the components of the scene during the line manipulation step. The collision avoidance module uses the occupancy grid to create a discrete electrostatic potential field representing the various goals (e.g. objects of interest) and obstacles in the scene. The algorithm takes into account the articular limits of the robot and uses a redundant manipulator to ensure that the collision avoidance constraints do not compete with the task which is to reach a given goal with the end-effector. A pose determination algorithm called Iterative Closest Point is presented. The algorithm allows to compute the pose of the various components of the scene and allows the robot to manipulate these components safely. The system has been tested on an actual scene. The manipulation was successfully implemented using a synchronized geometry range finder mounted on a PUMA 760 robot manipulator under the control of Cartool.

  17. Tomato grading system using machine vision technology and neuro-fuzzy networks (ANFIS

    Directory of Open Access Journals (Sweden)

    H Izadi

    2016-04-01

    Full Text Available Introduction: The quality of agricultural products is associated with their color, size and health, grading of fruits is regarded as an important step in post-harvest processing. In most cases, manual sorting inspections depends on available manpower, time consuming and their accuracy could not be guaranteed. Machine Vision is known to be a useful tool for external features measurement (e.g. size, shape, color and defects and in recent century, Machine Vision technology has been used for shape sorting. The main purpose of this study was to develop new method for tomato grading and sorting using Neuro-fuzzy system (ANFIS and to compare the accuracies of the ANFIS predicted results with those suggested by a human expert. Materials and Methods: In this study, a total of 300 image of tomatoes (Rev ground was randomly harvested, classified in 3 ripeness stage, 3 sizes and 2 health. The grading and sorting mechanism consisted of a lighting chamber (cloudy sky, lighting source and a digital camera connected to a computer. The images were recorded in a special chamber with an indirect radiation (cloudy sky with four florescent lampson each sides and camera lens was entire to lighting chamber by a hole which was only entranced to outer and covered by a camera lens. Three types of features were extracted from final images; Shap, color and texture. To receive these features, we need to have images both in color and binary format in procedure shown in Figure 1. For the first group; characteristics of the images were analysis that could offer information an surface area (S.A., maximum diameter (Dmax, minimum diameter (Dmin and average diameters. Considering to the importance of the color in acceptance of food quality by consumers, the following classification was conducted to estimate the apparent color of the tomato; 1. Classified as red (red > 90% 2. Classified as red light (red or bold pink 60-90% 3. Classified as pink (red 30-60% 4. Classified as Turning

  18. Color machine vision system for process control in the ceramics industry

    Science.gov (United States)

    Penaranda Marques, Jose A.; Briones, Leoncio; Florez, Julian

    1997-08-01

    This paper is focused on the design of a machine vision system to solve a problem found in the manufacturing process of high quality polished porcelain tiles. This consists of sorting the tiles according to the criteria 'same appearance to the human eye' or in other words, by color and visual texture. In 1994 this problem was tackled and led to a prototype which became fully operational at production scale in a manufacturing plant, named Porcelanatto, S.A. The system has evolved and has been adapted to meet the particular needs of this manufacturing company. Among the main issues that have been improved, it is worth pointing out: (1) improvement to discern subtle variations in color or texture, which are the main features of the visual appearance; (2) inspection time reduction, as a result of algorithm optimization and the increasing computing power. Thus, 100 percent of the production can be inspected, reaching a maximum of 120 tiles/sec.; (3) adaptation to the different types and models of tiles manufactured. The tiles vary not only in their visible patterns but also in dimensions, formats, thickness and allowances. In this sense, one major problem has been reaching an optimal compromise: The system must be sensitive enough to discern subtle variations in color, but at the same time insensitive thickness variations in the tiles. The following parts have been used to build the system: RGB color line scan camera, 12 bits per channel, PCI frame grabber, PC, fiber optic based illumination and the algorithm which will be explained in section 4.

  19. Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

    Directory of Open Access Journals (Sweden)

    Simon eFriedmann

    2013-09-01

    Full Text Available In this study, we propose and analyze in simulations a new, highly flexible method of imple-menting synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. Thestudy focuses on globally modulated STDP, as a special use-case of this method. Flexibility isachieved by embedding a general-purpose processor dedicated to plasticity into the wafer. Toevaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spiketrain learning task. A single layer of neurons is trained to fire at specific points in time withonly the reward as feedback. This model is simulated to measure its performance, i.e. the in-crease in received reward after learning. Using this performance as baseline, we then simulatethe model with various constraints imposed by the proposed implementation and compare theperformance. The simulated constraints include discretized synaptic weights, a restricted inter-face between analog synapses and embedded processor, and mismatch of analog circuits. Wefind that probabilistic updates can increase the performance of low-resolution weights, a simpleinterface between analog synapses and processor is sufficient for learning, and performance isinsensitive to mismatch. Further, we consider communication latency between wafer and theconventional control computer system that is simulating the environment. This latency increasesthe delay, with which the reward is sent to the embedded processor. Because of the time continu-ous operation of the analog synapses, delay can cause a deviation of the updates as compared tothe not delayed situation. We find that for highly accelerated systems latency has to be kept to aminimum. This study demonstrates the suitability of the proposed implementation to emulatethe selected reward modulated STDP learning rule. It is therefore an ideal candidate for imple-mentation in an upgraded version of the wafer-scale system developed within the BrainScaleSproject.

  20. Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review

    OpenAIRE

    CUBERO GARCÍA, SERGIO; Lee, Won Suk; Aleixos Borrás, María Nuria; Albert Gil, Francisco Eugenio; BLASCO IVARS, JOSE

    2016-01-01

    Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing not...