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Sample records for machine vision artificial

  1. 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?

  2. Artificial vision.

    Science.gov (United States)

    Zarbin, M; Montemagno, C; Leary, J; Ritch, R

    2011-09-01

    A number treatment options are emerging for patients with retinal degenerative disease, including gene therapy, trophic factor therapy, visual cycle inhibitors (e.g., for patients with Stargardt disease and allied conditions), and cell transplantation. A radically different approach, which will augment but not replace these options, is termed neural prosthetics ("artificial vision"). Although rewiring of inner retinal circuits and inner retinal neuronal degeneration occur in association with photoreceptor degeneration in retinitis pigmentosa (RP), it is possible to create visually useful percepts by stimulating retinal ganglion cells electrically. This fact has lead to the development of techniques to induce photosensitivity in cells that are not light sensitive normally as well as to the development of the bionic retina. Advances in artificial vision continue at a robust pace. These advances are based on the use of molecular engineering and nanotechnology to render cells light-sensitive, to target ion channels to the appropriate cell type (e.g., bipolar cell) and/or cell region (e.g., dendritic tree vs. soma), and on sophisticated image processing algorithms that take advantage of our knowledge of signal processing in the retina. Combined with advances in gene therapy, pathway-based therapy, and cell-based therapy, "artificial vision" technologies create a powerful armamentarium with which ophthalmologists will be able to treat blindness in patients who have a variety of degenerative retinal diseases.

  3. Artificial vision workbench.

    Science.gov (United States)

    Frenger, P

    1997-01-01

    Machine vision is an important component of medical systems engineering. Inexpensive miniature solid state cameras are now available. This paper describes how these devices can be used as artificial retinas, to take snapshots and moving pictures in monochrome or color. Used in pairs, they produce a stereoscopic field of vision and enable depth perception. Macular and peripheral vision can be simulated electronically. This paper also presents the author's design of an artificial orbit for this synthetic eye. The orbit supports the eye, protects it, and provides attachment points for the ocular motion control system. Convergence and image fusion can be produced, and saccades simulated, along with the other ocular motions. The use of lenses, filters, irises and focusing mechanisms are also discussed. Typical camera-computer interfaces are described, including the use of "frame grabbers" and analog-to-digital image conversion. Software programs for eye positioning, image manipulation, feature extraction and object recognition are discussed, including the application of artificial neural networks.

  4. Broiler weight estimation based on machine vision and artificial neural network.

    Science.gov (United States)

    Amraei, S; Abdanan Mehdizadeh, S; Salari, S

    2017-04-01

    1. Machine vision and artificial neural network (ANN) procedures were used to estimate live body weight of broiler chickens in 30 1-d-old broiler chickens reared for 42 d. 2. Imaging was performed two times daily. To localise chickens within the pen, an ellipse fitting algorithm was used and the chickens' head and tail removed using the Chan-Vese method. 3. The correlations between the body weight and 6 physical extracted features indicated that there were strong correlations between body weight and the 5 features including area, perimeter, convex area, major and minor axis length. 5. According to statistical analysis there was no significant difference between morning and afternoon data over 42 d. 6. In an attempt to improve the accuracy of live weight approximation different ANN techniques, including Bayesian regulation, Levenberg-Marquardt, Scaled conjugate gradient and gradient descent were used. Bayesian regulation with R(2) value of 0.98 was the best network for prediction of broiler weight. 7. The accuracy of the machine vision technique was examined and most errors were less than 50 g.

  5. Artificial vision.

    Science.gov (United States)

    Humayun, M S; de Juan, E

    1998-01-01

    Outer retinal degenerations such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD) lead to blindness because of photoreceptor degeneration. To test whether controlled electrical stimulation of the remaining retinal neurons could provide form vision, we electrically stimulated the inner retinal surface with micro-electrodes inserted through the sclera/eye wall of 14 of these patients (12 RP and 2 AMD). This procedure was performed in the operating room under local anaesthesia and all responses were recorded via a video camera mounted on the surgical microscope. Electrical stimulation of the inner retinal surface elicited visual perception of a spot of light (phosphene) in all subjects. This perception was retinotopically correct in 13 of 14 patients. In a resolution test in a subject with no light perception, the patient could resolve phosphenes at 1.75 degrees centre-to-centre distance (i.e. visual acuity compatible with mobility; Snellen visual acuity of 4/200).

  6. Artificial human vision.

    Science.gov (United States)

    Dowling, Jason

    2005-01-01

    Can vision be restored to the blind? As early as 1929 it was discovered that stimulating the visual cortex of an individual led to the perception of spots of light, known as phosphenes [1] . The aim of artificial human vision systems is to attempt to utilize the perception of phosphenes to provide a useful substitute for normal vision. Currently, four locations for electrical stimulation are being investigated; behind the retina (subretinal), in front of the retina (epiretinal), the optic nerve and the visual cortex (using intra- and surface electrodes). This review discusses artificial human vision technology and requirements, and reviews the current development projects.

  7. 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...

  8. Machine vision is not computer vision

    Science.gov (United States)

    Batchelor, Bruce G.; Charlier, Jean-Ray

    1998-10-01

    The identity of Machine Vision as an academic and practical subject of study is asserted. In particular, the distinction between Machine Vision on the one hand and Computer Vision, Digital Image Processing, Pattern Recognition and Artificial Intelligence on the other is emphasized. The article demonstrates through four cases studies that the active involvement of a person who is sensitive to the broad aspects of vision system design can avoid disaster and can often achieve a successful machine that would not otherwise have been possible. This article is a transcript of the key- note address presented at the conference. Since the proceedings are prepared and printed before the conference, it is not possible to include a record of the response to this paper made by the delegates during the round-table discussion. It is hoped to collate and disseminate these via the World Wide Web after the event. (A link will be provided at http://bruce.cs.cf.ac.uk/bruce/index.html.).

  9. Egg volume prediction using machine vision technique based on pappus theorem and artificial neural network.

    Science.gov (United States)

    Soltani, Mahmoud; Omid, Mahmoud; Alimardani, Reza

    2015-05-01

    Egg size is one of the important properties of egg that is judged by customers. Accordingly, in egg sorting and grading, the size of eggs must be considered. In this research, a new method of egg volume prediction was proposed without need to measure weight of egg. An accurate and efficient image processing algorithm was designed and implemented for computing major and minor diameters of eggs. Two methods of egg size modeling were developed. In the first method, a mathematical model was proposed based on Pappus theorem. In second method, Artificial Neural Network (ANN) technique was used to estimate egg volume. The determined egg volume by these methods was compared statistically with actual values. For mathematical modeling, the R(2), Mean absolute error and maximum absolute error values were obtained as 0.99, 0.59 cm(3) and 1.69 cm(3), respectively. To determine the best ANN, R(2) test and RMSEtest were used as selection criteria. The best ANN topology was 2-28-1 which had the R(2) test and RMSEtest of 0.992 and 0.66, respectively. After system calibration, the proposed models were evaluated. The results which indicated the mathematical modeling yielded more satisfying results. So this technique was selected for egg size determination.

  10. Understanding and applying machine vision

    CERN Document Server

    Zeuch, Nello

    2000-01-01

    A discussion of applications of machine vision technology in the semiconductor, electronic, automotive, wood, food, pharmaceutical, printing, and container industries. It describes systems that enable projects to move forward swiftly and efficiently, and focuses on the nuances of the engineering and system integration of machine vision technology.

  11. Artificial intelligence and computer vision

    CERN Document Server

    Li, Yujie

    2017-01-01

    This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

  12. Artificial Vision, New Visual Modalities and Neuroadaptation

    Directory of Open Access Journals (Sweden)

    Hilmi Or

    2012-01-01

    Full Text Available To study the descriptions from which artificial vision derives, to explore the new visual modalities resulting from eye surgeries and diseases, and to gain awareness of the use of machine vision systems for both enhancement of visual perception and better understanding of neuroadaptation. Science could not define until today what vision is. However, some optical-based systems and definitions have been established considering some factors for the formation of seeing. The best known system includes Gabor filter and Gabor patch which work on edge perception, describing the visual perception in the best known way. These systems are used today in industry and technology of machines, robots and computers to provide their "seeing". These definitions are used beyond the machinery in humans for neuroadaptation in new visual modalities after some eye surgeries or to improve the quality of some already known visual modalities. Beside this, “the blindsight” -which was not known to exist until 35 years ago - can be stimulated with visual exercises. Gabor system is a description of visual perception definable in machine vision as well as in human visual perception. This system is used today in robotic vision. There are new visual modalities which arise after some eye surgeries or with the use of some visual optical devices. Also, blindsight is a different visual modality starting to be defined even though the exact etiology is not known. In all the new visual modalities, new vision stimulating therapies using the Gabor systems can be applied. (Turk J Oph thal mol 2012; 42: 61-5

  13. Machine Learning for Computer Vision

    CERN Document Server

    Battiato, Sebastiano; Farinella, Giovanni

    2013-01-01

    Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. The International Computer Vision Summer School - ICVSS was established in 2007 to provide both an objective and clear overview and an in-depth analysis of the state-of-the-art research in Computer Vision. The courses are delivered by world renowned experts in the field, from both academia and industry, and cover both theoretical and practical aspects of real Computer Vision problems. The school is organized every year by University of Cambridge (Computer Vision and Robotics Group) and University of Catania (Image Processing Lab). Different topics are covered each year. A summary of the past Computer Vision Summer Schools can be found at: http://www.dmi.unict.it/icvss This edited volume contains a selection of articles covering some of the talks and t...

  14. Machine vision theory, algorithms, practicalities

    CERN Document Server

    Davies, E R

    2005-01-01

    In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directl

  15. Diagnostics and Control of Natural Gas-Fired furnaces via Flame Image Analysis using Machine Vision & Artificial Intelligence Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Shahla Keyvan

    2005-12-01

    A new approach for the detection of real-time properties of flames is used in this project to develop improved diagnostics and controls for natural gas fired furnaces. The system utilizes video images along with advanced image analysis and artificial intelligence techniques to provide virtual sensors in a stand-alone expert shell environment. One of the sensors is a flame sensor encompassing a flame detector and a flame analyzer to provide combustion status. The flame detector can identify any burner that has not fired in a multi-burner furnace. Another sensor is a 3-D temperature profiler. One important aspect of combustion control is product quality. The 3-D temperature profiler of this on-line system is intended to provide a tool for a better temperature control in a furnace to improve product quality. In summary, this on-line diagnostic and control system offers great potential for improving furnace thermal efficiency, lowering NOx and carbon monoxide emissions, and improving product quality. The system is applicable in natural gas-fired furnaces in the glass industry and reheating furnaces used in steel and forging industries.

  16. Computer and machine vision theory, algorithms, practicalities

    CERN Document Server

    Davies, E R

    2012-01-01

    Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject. Key features include: Practical examples and case studies give the 'ins and outs' of developing real-world vision systems, giving engineers the realities of implementing the principles in practice New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision Necessary mathematics and essential theory are made approachable by careful explanations and well-il...

  17. Machine vision and the OMV

    Science.gov (United States)

    Mcanulty, M. A.

    1986-01-01

    The orbital Maneuvering Vehicle (OMV) is intended to close with orbiting targets for relocation or servicing. It will be controlled via video signals and thruster activation based upon Earth or space station directives. A human operator is squarely in the middle of the control loop for close work. Without directly addressing future, more autonomous versions of a remote servicer, several techniques that will doubtless be important in a future increase of autonomy also have some direct application to the current situation, particularly in the area of image enhancement and predictive analysis. Several techniques are presentet, and some few have been implemented, which support a machine vision capability proposed to be adequate for detection, recognition, and tracking. Once feasibly implemented, they must then be further modified to operate together in real time. This may be achieved by two courses, the use of an array processor and some initial steps toward data reduction. The methodology or adapting to a vector architecture is discussed in preliminary form, and a highly tentative rationale for data reduction at the front end is also discussed. As a by-product, a working implementation of the most advanced graphic display technique, ray-casting, is described.

  18. Insect vision as model for machine vision

    Science.gov (United States)

    Osorio, D.; Sobey, Peter J.

    1992-11-01

    The neural architecture, neurophysiology and behavioral abilities of insect vision are described, and compared with that of mammals. Insects have a hardwired neural architecture of highly differentiated neurons, quite different from the cerebral cortex, yet their behavioral abilities are in important respects similar to those of mammals. These observations challenge the view that the key to the power of biological neural computation is distributed processing by a plastic, highly interconnected, network of individually undifferentiated and unreliable neurons that has been a dominant picture of biological computation since Pitts and McCulloch's seminal work in the 1940's.

  19. Color in machine vision and its application

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Color is the phenomenon of human visual perception and the module of machine vision. Color information is widely used in the areas of virtual reality and humancomputer interaction. Color is the product of a visual environment, illumination and the human brain. Research on color information representation and its processing is typically interdisciplinary. Based on our research work on human color perception and machine color vision and its application, we summarized the hotspots of color studies in recent developments and new approaches to color vision,including basic theories and the application of color information in virtual reality, content-based image retrieval, and face recognition.

  20. Machine vision for airport runway identification

    Science.gov (United States)

    Schubert, Matthew; Moore, Andrew J.; Dolph, Chester; Woodell, Glenn

    2015-03-01

    For rigid objects and fixed scenes, current machine vision technology is capable of identifying imagery rapidly and with specificity over a modest range of camera viewpoints and scene illumination. We applied that capability to the problem of runway identification using video of sixteen runway approaches at nine locations, subject to two simplifying assumptions. First, by using approach video from just one of the several possible seasonal variations (no snow cover and full foliage), we artificially removed one source of scene variation in this study. Secondly, by not using approach video at dawn and dusk, we limited the study to two illumination variants (day and night). We did allow scene variation due to atmospheric turbidity by using approach video from rainy and foggy days in some daytime approaches. With suitable ensemble statistics to account for temporal continuity in video, we observed high location specificity (<90% Bayesian posterior probability). We also tested repeatability, i.e., identification of a given runway across multiple videos, and observed robust repeatability only if illumination (day vs. night) was the same and approach visibility was good. Both specificity and repeatability degraded in poor weather conditions. The results of this simplified study show that geolocation via real-time comparison of cockpit image sensor video to a database of runway approach imagery is feasible, as long as the database contains imagery from about the same time of day (complete daylight and nighttime, excluding dawn and dusk) and the weather is clear at the time of the flight.

  1. Two dimensional convolute integers for machine vision and image recognition

    Science.gov (United States)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  2. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  3. Machine Vision Giving Eyes to Robots. Resources in Technology.

    Science.gov (United States)

    Technology Teacher, 1990

    1990-01-01

    This module introduces machine vision, which can be used for inspection, robot guidance and part sorting. The future for machine vision will include new technology and will bring vision systems closer to the ultimate vision processor, the human eye. Includes a student quiz, outcomes, and activities. (JOW)

  4. Machine Learning Techniques in Clinical Vision Sciences.

    Science.gov (United States)

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  5. 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.

  6. Machine vision and mechatronics in practice

    CERN Document Server

    Brett, Peter

    2015-01-01

    The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine.  Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be ac...

  7. Bioinspired minimal machine multiaperture apposition vision system.

    Science.gov (United States)

    Davis, John D; Barrett, Steven F; Wright, Cameron H G; Wilcox, Michael

    2008-01-01

    Traditional machine vision systems have an inherent data bottleneck that arises because data collected in parallel must be serialized for transfer from the sensor to the processor. Furthermore, much of this data is not useful for information extraction. This project takes inspiration from the visual system of the house fly, Musca domestica, to reduce this bottleneck by employing early (up front) analog preprocessing to limit the data transfer. This is a first step toward an all analog, parallel vision system. While the current implementation has serial stages, nothing would prevent it from being fully parallel. A one-dimensional photo sensor array with analog pre-processing is used as the sole sensory input to a mobile robot. The robot's task is to chase a target car while avoiding obstacles in a constrained environment. Key advantages of this approach include passivity and the potential for very high effective "frame rates."

  8. Fresh market carrot inspection by machine vision

    Science.gov (United States)

    Howarth, M. Scott; Searcy, Stephen W.

    1991-02-01

    A machine vision system was developed to inspect fresh market carrots. It was designed to grade carrots with an axial and transverse resolution of 0. 5mmper pixel. Hardware consisted of camera digital signal processing (DSP) imaging board host computer and illumination components. Feature extraction methods detect the major defects. A Bayes classification technique was used to construct the decision function which classify carrots as acceptable or cull. The system was able to image and classify in approximately 2. 5carrots/second. 1.

  9. Probabilistic machine learning and artificial intelligence.

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-28

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  10. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  11. Machine Vision Implementation in Rapid PCB Prototyping

    Directory of Open Access Journals (Sweden)

    Yosafat Surya Murijanto

    2012-03-01

    Full Text Available Image processing, the heart of machine vision, has proven itself to be an essential part of the industries today. Its application has opened new doorways, making more concepts in manufacturing processes viable. This paper presents an application of machine vision in designing a module with the ability to extract drills and route coordinates from an un-mounted or mounted printed circuit board (PCB. The algorithm comprises pre-capturing processes, image segmentation and filtering, edge and contour detection, coordinate extraction, and G-code creation. OpenCV libraries and Qt IDE are the main tools used. Throughout some testing and experiments, it is concluded that the algorithm is able to deliver acceptable results. The drilling and routing coordinate extraction algorithm can extract in average 90% and 82% of the whole drills and routes available on the scanned PCB in a total processing time of less than 3 seconds. This is achievable through proper lighting condition, good PCB surface condition and good webcam quality. 

  12. A Machine Vision System for Ball Grid Array Package Inspection

    Institute of Scientific and Technical Information of China (English)

    XIA Nian-jiong; CAO Qi-xin; LEE Jey

    2005-01-01

    An optical inspection method of the Ball Grid Array package (BGA) was proposed by using a machine vision system. The developed machine vision system could get main critical factors for BGA quality evaluation, such as the height of solder ball, diameter, pitch and coplanarity. The experiment has proved that this system is available for BGA failure detection.

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

    Science.gov (United States)

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

    1990-01-01

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

  14. Machine-vision based optofluidic cell sorting

    DEFF Research Database (Denmark)

    Glückstad, Jesper; Bañas, Andrew

    In contemporary life science there is an increasing emphasis on sorting rare disease-indicating cells within small dilute quantities such as in the confines of optofluidic lab-on-chip devices. Our approach to this is based on the use of optical forces to isolate red blood cells detected by advanc...... the available light and creating 2D or 3D beam distributions aimed at the positions of the detected cells. Furthermore, the beam shaping freedom provided by GPC can allow optimizations in the beam’s propagation and its interaction with the laser catapulted and sorted cells....... machine vision1. This approach is gentler, less invasive and more economical compared to conventional FACS-systems. As cells are less responsive to plastic or glass objects commonly used in the optical manipulation literature2, and since laser safety would be an issue in clinical use, we develop efficient...

  15. Quantificação da falha na madeira em juntas coladas utilizando técnicas de visão artificial Measuring wood failure percentage using a machine vision system

    Directory of Open Access Journals (Sweden)

    Christovão Pereira Abrahão

    2003-02-01

    Full Text Available Com o emprego de adesivos pode-se obter um grande número de produtos derivados da madeira. Para confecção industrial de produtos de madeira colada, normas reconhecidas internacionalmente exigem que a adesão da madeira seja testada segundo procedimentos padronizados e que nos resultados destes testes seja reportado, além da resistência das juntas, o porcentual de falha na madeira. Para avaliação da falha a norma ASTM D5266-99 recomenda o emprego de uma rede de quadrículas traçada sobre um material transparente. Contudo, esta avaliação, além de demandar muito tempo, ainda é realizada com muita subjetividade. A hipótese do presente trabalho é que se pode quantificar a falha na madeira com um sistema de visão artificial, tornando o procedimento mais rápido e menos sujeito à subjetividade. Foram testados dois tipos de algoritmos de limiarização automática em imagens adquiridas com digitalizadores de mesa. Concluiu-se que a falha na madeira pode ser quantificada por limiarização automática em substituição ao método convencional das quadrículas. Os algoritmos testados apresentaram erro médio absoluto menor que 3% em relação ao sistema convencional da rede quadriculada.It is possible to obtain several products by glueing wood. Internationally approved standards require wood adhesion to be tested according to standardized procedures, including in the results, shear stress and wood failure percentages. In order to estimate wood failure percentage, the ASTM D5266-99 standard suggests the use of a grid template printed on a transparent sheet. However, this evaluation is not only time-consuming but also subjective. This work developed and tested an algorithm to quantify the flawed wood areas by using a machine vision system, a faster and less subjective procedure. Two types of automatic threshold algorithms were tested. The glued wood samples were scanned after the shear tests under compression. It was concluded that automatic

  16. Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Zheng; Ukida, H.; Niel, Kurt; Ramuhalli, Pradeep

    2015-10-01

    Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a better performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.

  17. Application of Machine Vision Technique in Weed Identification

    Institute of Scientific and Technical Information of China (English)

    LIU Zhen-heng; ZHANG Chang-li; FANG Jun-long

    2004-01-01

    This paper mainly introduces some foreign research methods and fruits about weed identification by applying machine vision. This facet researches is lack in our country, this paper could be reference for domestic studies about weed identification.

  18. Machine Vision Systems for Processing Hardwood Lumber and Logs

    Science.gov (United States)

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

    1992-01-01

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

  19. Learning surface molecular structures via machine vision

    Science.gov (United States)

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-01

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

  20. Applications of AI, machine vision and robotics

    CERN Document Server

    Boyer, Kim; Bunke, H

    1995-01-01

    This text features a broad array of research efforts in computer vision including low level processing, perceptual organization, object recognition and active vision. The volume's nine papers specifically report on topics such as sensor confidence, low level feature extraction schemes, non-parametric multi-scale curve smoothing, integration of geometric and non-geometric attributes for object recognition, design criteria for a four degree-of-freedom robot head, a real-time vision system based on control of visual attention and a behavior-based active eye vision system. The scope of the book pr

  1. Standard machine vision systems used in different industrial applications

    Science.gov (United States)

    Bruehl, Wolfgang

    1993-12-01

    Fully standardized machine vision systems won't require task specific hard- or software development. This allows short project realization times at minimized cost. This paper describes two very different applications which were realized only by menu-guided configuration of the QueCheck standard machine vision system. The first is an in-line survey of oilpump castings necessary to protect the following working machine from being damaged by castings not according to the specified geometrical measures. The second application shows the replacement of time consuming manual particle size analysis of fertilizer pellets, by a continuous analysis with a vision system. At the same time the data of the vision system can be used to optimize particle size during production.

  2. 3D vision assisted flexible robotic assembly of machine components

    Science.gov (United States)

    Ogun, Philips S.; Usman, Zahid; Dharmaraj, Karthick; Jackson, Michael R.

    2015-12-01

    Robotic assembly systems either make use of expensive fixtures to hold components in predefined locations, or the poses of the components are determined using various machine vision techniques. Vision-guided assembly robots can handle subtle variations in geometries and poses of parts. Therefore, they provide greater flexibility than the use of fixtures. However, the currently established vision-guided assembly systems use 2D vision, which is limited to three degrees of freedom. The work reported in this paper is focused on flexible automated assembly of clearance fit machine components using 3D vision. The recognition and the estimation of the poses of the components are achieved by matching their CAD models with the acquired point cloud data of the scene. Experimental results obtained from a robot demonstrating the assembly of a set of rings on a shaft show that the developed system is not only reliable and accurate, but also fast enough for industrial deployment.

  3. Machine vision based on the concept of contrast sensitivity of the human eye

    Science.gov (United States)

    Bezzubik, Vitali; Belashenkov, Nikolai; Vdovin, Gleb

    2014-09-01

    The model of contrast sensitivity function (CSF) of machine vision system, based on the CSF of the human visual system is proposed. By analogy with the human eye, we employ the concept of ganglion cell receptive field to the artificial light-sensitive elements. By further following this concept, we introduced quantative metrics of local and global contrast of digital image. We suggested that the contrast sensitivity threshold forms an iso-line in the parameter space contrast - spatial frequency. The model, implemented in a computer vision system, has been compared to the results of contrast sensitivity research, conducted directly with the human visual system, and demonstrated a good match.

  4. 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.

  5. Trends and developments in industrial machine vision: 2013

    Science.gov (United States)

    Niel, Kurt; Heinzl, Christoph

    2014-03-01

    When following current advancements and implementations in the field of machine vision there seems to be no borders for future developments: Calculating power constantly increases, and new ideas are spreading and previously challenging approaches are introduced in to mass market. Within the past decades these advances have had dramatic impacts on our lives. Consumer electronics, e.g. computers or telephones, which once occupied large volumes, now fit in the palm of a hand. To note just a few examples e.g. face recognition was adopted by the consumer market, 3D capturing became cheap, due to the huge community SW-coding got easier using sophisticated development platforms. However, still there is a remaining gap between consumer and industrial applications. While the first ones have to be entertaining, the second have to be reliable. Recent studies (e.g. VDMA [1], Germany) show a moderately increasing market for machine vision in industry. Asking industry regarding their needs the main challenges for industrial machine vision are simple usage and reliability for the process, quick support, full automation, self/easy adjustment at changing process parameters, "forget it in the line". Furthermore a big challenge is to support quality control: Nowadays the operator has to accurately define the tested features for checking the probes. There is an upcoming development also to let automated machine vision applications find out essential parameters in a more abstract level (top down). In this work we focus on three current and future topics for industrial machine vision: Metrology supporting automation, quality control (inline/atline/offline) as well as visualization and analysis of datasets with steadily growing sizes. Finally the general trend of the pixel orientated towards object orientated evaluation is addressed. We do not directly address the field of robotics taking advances from machine vision. This is actually a fast changing area which is worth an own

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

    Directory of Open Access Journals (Sweden)

    Gao Chi

    2013-05-01

    Full Text Available 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 result of the experiment certificated that the rate of garlic clove direction identification could reach to more than 97%, and it demonstrated that the research is of high feasibility and technological values.

  7. Machine Vision For Industrial Control:The Unsung Opportunity

    Science.gov (United States)

    Falkman, Gerald A.; Murray, Lawrence A.; Cooper, James E.

    1984-05-01

    Vision modules have primarily been developed to relieve those pressures newly brought into existence by Inspection (QUALITY) and Robotic (PRODUCTIVITY) mandates. Industrial Control pressure stems on the other hand from the older first industrial revolution mandate of throughput. Satisfying such pressure calls for speed in both imaging and decision making. Vision companies have, however, put speed on a backburner or ignore it entirely because most modules are computer/software based which limits their speed potential. Increasingly, the keynote being struck at machine vision seminars is that "Visual and Computational Speed Must Be Increased and Dramatically!" There are modular hardwired-logic systems that are fast but, all too often, they are not very bright. Such units: Measure the fill factor of bottles as they spin by, Read labels on cans, Count stacked plastic cups or Monitor the width of parts streaming past the camera. Many are only a bit more complex than a photodetector. Once in place, most of these units are incapable of simple upgrading to a new task and are Vision's analog to the robot industry's pick and place (RIA TYPE E) robot. Vision thus finds itself amidst the same quandries that once beset the Robot Industry of America when it tried to define a robot, excluded dumb ones, and was left with only slow machines whose unit volume potential is shatteringly low. This paper develops an approach to meeting the need of a vision system that cuts a swath into the terra incognita of intelligent, high-speed vision processing. Main attention is directed to vision for industrial control. Some presently untapped vision application areas that will be serviced include: Electronics, Food, Sports, Pharmaceuticals, Machine Tools and Arc Welding.

  8. Handbook of 3D machine vision optical metrology and imaging

    CERN Document Server

    Zhang, Song

    2013-01-01

    With the ongoing release of 3D movies and the emergence of 3D TVs, 3D imaging technologies have penetrated our daily lives. Yet choosing from the numerous 3D vision methods available can be frustrating for scientists and engineers, especially without a comprehensive resource to consult. Filling this gap, Handbook of 3D Machine Vision: Optical Metrology and Imaging gives an extensive, in-depth look at the most popular 3D imaging techniques. It focuses on noninvasive, noncontact optical methods (optical metrology and imaging). The handbook begins with the well-studied method of stereo vision and

  9. Machine vision for a selective broccoli harvesting robot

    NARCIS (Netherlands)

    Blok, Pieter M.; Barth, Ruud; Berg, Van Den Wim

    2016-01-01

    The selective hand-harvest of fresh market broccoli is labor-intensive and comprises about 35% of the total production costs. This research was conducted to determine whether machine vision can be used to detect broccoli heads, as a first step in the development of a fully autonomous selective harve

  10. Design and construction of automatic sorting station with machine vision

    Directory of Open Access Journals (Sweden)

    Oscar D. Velasco-Delgado

    2014-01-01

    Full Text Available This article presents the design, construction and testing of an automatic product sorting system in belt conveyor with machine vision that integrates Free and Open Source Software technology and Allen Bradley commercial equipment. Requirements are defined to determine features such as: mechanics of manufacturing station, an app of product sorting with machine vision and for automation system. For the app of machine vision a library is used for optical digital image processing Open CV, for the mechanical design of the manufacturing station is used the CAD tool Solid Edge and for the design and implementation of automation ISA standards are used along with an automation engineering project methodology integrating a PLC, an inverter, a Panel View and a DeviceNet Network. Performance tests are shown by classifying bottles and PVC pieces in four established types, the behavior of the integrated system is checked so as the efficiency of the same. The processing time on machine vision is 0.290 s on average for a piece of PVC, a capacity of 206 accessories per minute, for bottles was obtained a processing time of 0.267 s, a capacity of 224 bottles per minute. A maximum mechanical performance is obtained with 32 products per minute (1920 products/hour with the conveyor to 22 cm/s and 40 cm of distance between products obtaining an average error of 0.8%.

  11. 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.

  12. Measurement of seedling growth rate by machine vision

    Science.gov (United States)

    Howarth, M. Scott; Stanwood, Phillip C.

    1993-05-01

    Seed vigor and germination tests have traditionally been used to determine deterioration of seed samples. Vigor tests describe the seed potential to emerge and produce a mature crop under certain field conditions and one measure is seedling growth rate. A machine vision system was developed to measure root growth rate over the entire germination period. The machine vision measurement technique was compared to the manual growth rate technique. The vision system provided similar growth rate measurements as compared to the manual growth rate technique. The average error between the system and a manual measurement was -0.13 for the lettuce test and -0.07 for the sorghum test. This technique also provided an accurate representation of the growth rate as well as percent germination.

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

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

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

  14. 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.

  15. Research on Manufacturing Technology Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    HU Zhanqi; ZHENG Kuijing

    2006-01-01

    The concept of machine vision based manufacturing technology is proposed first, and the key algorithms used in two-dimensional and three-dimensional machining are discussed in detail. Machining information can be derived from the binary images and gray picture after processing and transforming the picture. Contour and the parallel cutting method about two-dimensional machining are proposed. Polygon approximating algorithm is used to cutting the profile of the workpiece. Fill Scanning algorithm used to machining inner part of a pocket. The improved Shape From Shading method with adaptive pre-processing is adopted to reconstruct the three-dimensional model. Layer cutting method is adopted for three-dimensional machining. The tool path is then gotten from the model, and NC code is formed subsequently. The model can be machined conveniently by the lathe, milling machine or engraver. Some examples are given to demonstrate the results of ImageCAM system, which is developed by the author to implement the algorithms previously mentioned.

  16. Machine Learning for Vision-Based Motion Analysis

    CERN Document Server

    Wang, Liang; Cheng, Li; Pietikainen, Matti

    2011-01-01

    Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second In

  17. Collection of Group Characteristics of Pleurotus Eryngii Using Machine Vision

    Science.gov (United States)

    Wang, Yunsheng; Wan, Changzhao; Yang, Juan; Chen, Jianlin; Yuan, Tao; Zhao, Jingyin

    An information collection system which was used to group characteristics of pleurotus eryngii was introduced. The group characteristics of pleurotus eryngii were quantified using machine vision in order to inspect and control the pleurotus eryngii house environment by an automated system. Its main contents include the following: collection of pleurotus eryngii image; image processing and pattern recognition. Finally, by analysing pleurotus eryngii image, the systems for group characteristics of pleurotus eryngii are proved to be greatly effective.

  18. Machine vision automated visual inspection theory, practice and applications

    CERN Document Server

    Beyerer, Jürgen; Frese, Christian

    2016-01-01

    The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

  19. Software architecture for time-constrained machine vision applications

    Science.gov (United States)

    Usamentiaga, Rubén; Molleda, Julio; García, Daniel F.; Bulnes, Francisco G.

    2013-01-01

    Real-time image and video processing applications require skilled architects, and recent trends in the hardware platform make the design and implementation of these applications increasingly complex. Many frameworks and libraries have been proposed or commercialized to simplify the design and tuning of real-time image processing applications. However, they tend to lack flexibility, because they are normally oriented toward particular types of applications, or they impose specific data processing models such as the pipeline. Other issues include large memory footprints, difficulty for reuse, and inefficient execution on multicore processors. We present a novel software architecture for time-constrained machine vision applications that addresses these issues. The architecture is divided into three layers. The platform abstraction layer provides a high-level application programming interface for the rest of the architecture. The messaging layer provides a message-passing interface based on a dynamic publish/subscribe pattern. A topic-based filtering in which messages are published to topics is used to route the messages from the publishers to the subscribers interested in a particular type of message. The application layer provides a repository for reusable application modules designed for machine vision applications. These modules, which include acquisition, visualization, communication, user interface, and data processing, take advantage of the power of well-known libraries such as OpenCV, Intel IPP, or CUDA. Finally, the proposed architecture is applied to a real machine vision application: a jam detector for steel pickling lines.

  20. VISART: Artificial vision for industrial use. A comprehensive system

    Science.gov (United States)

    Debritoalves, Sdnei

    1992-02-01

    A thorough description of a Computer Vision System applied to inspection activities is presented, all of the life-cycle stages of this system being dealt with in detail. It was conceived, designed, and implemented within the scope of an applied research, entitled (VISART) Artificial Vision for Industrial Use: A Comprehensive System. During the effort employed in the development of this work, significant contributions were incorporated to the state-of-the-art in processing of binary images. The VISART system includes resources, concepts, and inovations not yet seen in similar systems. A new terminology with technical terms nearer to those used by engineers and technicians, in industrial environments, is proposed and it might contribute for acceptance and dissemination of Vision Systems in these environments. Concepts of Group Technology have been associated to Vision Systems and they might contribute for a greater integration of the industrial process automation. A special data structure was conceived for image data storage, allowing to reduce the processing time of algorithms of industrial part features-extraction. A library with a considerable number of feature extraction algorithms, used for recognition, acceptance or rejection of industrial products under inspection, was conceived and implemented. New algorithms can be appended to this library by the user, without the necessity of reprogramming the modules of the VISART system. Within this respect lies one of the main comprisement features of VISART. It has a graphic editor which makes possible to use it in activities such as teaching and formation of skilled personnel in the area of vision. At first, this facility exempts the use of sensors, making it more economic for use in these activities. All in all, this research work is a pioneer in Brazil, and its divulgation must contribute significantly for the dissemination and growth of the computer vision area applied to inspection, in the country.

  1. Practical guide to machine vision software an introduction with LabVIEW

    CERN Document Server

    Kwon, Kye-Si

    2014-01-01

    For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabli

  2. Progress in artificial vision through suprachoroidal retinal implants

    Science.gov (United States)

    Bareket, Lilach; Barriga-Rivera, Alejandro; Zapf, Marc Patrick; Lovell, Nigel H.; Suaning, Gregg J.

    2017-08-01

    Retinal implants have proven their ability to restore visual sensation to people with degenerative retinopathy, characterized by photoreceptor cell death and the retina’s inability to sense light. Retinal bionics operate by electrically stimulating the surviving neurons in the retina, thus triggering the transfer of visual sensory information to the brain. Suprachoroidal implants were first investigated in Australia in the 1950s. In this approach, the neuromodulation hardware is positioned between the sclera and the choroid, thus providing significant surgical and safety benefits for patients, with the potential to maintain residual vision combined with the artificial input from the device. Here we review the latest advances and state of the art devices for suprachoroidal prostheses, highlight future technologies and discuss challenges and perspectives towards improved rehabilitation of vision.

  3. Artificial knowing gender and the thinking machine

    CERN Document Server

    Adam, Alison

    1998-01-01

    Artificial Knowing challenges the masculine slant in the Artificial Intelligence (AI) view of the world. Alison Adam admirably fills the large gap in science and technology studies by showing us that gender bias is inscribed in AI-based computer systems. Her treatment of feminist epistemology, focusing on the ideas of the knowing subject, the nature of knowledge, rationality and language, are bound to make a significant and powerful contribution to AI studies. Drawing from theories by Donna Haraway and Sherry Turkle, and using tools of feminist epistemology, Adam provides a sustained critique of AI which interestingly re-enforces many of the traditional criticisms of the AI project. Artificial Knowing is an esential read for those interested in gender studies, science and technology studies, and philosophical debates in AI.

  4. Volume Measurement in Solid Objects Using Artificial Vision Technique

    Science.gov (United States)

    Cordova-Fraga, T.; Martinez-Espinosa, J. C.; Bernal, J.; Huerta-Franco, R.; Sosa-Aquino, M.; Vargas-Luna, M.

    2004-09-01

    A simple system using artificial vision technique for measuring the volume of solid objects is described. The system is based on the acquisition of an image sequence of the object while it is rotating on an automated mechanism controlled by a PC. Volumes of different objects such as a sphere, a cylinder and also a carrot were measured. The proposed algorithm was developed in environment LabView 6.1. This technique can be very useful when it is applied to measure the human body for evaluating its body composition.

  5. Machine Learning Optimization of Evolvable Artificial Cells

    DEFF Research Database (Denmark)

    Caschera, F.; Rasmussen, S.; Hanczyc, M.

    2011-01-01

    can be explored. A machine learning approach (Evo-DoE) could be applied to explore this experimental space and define optimal interactions according to a specific fitness function. Herein an implementation of an evolutionary design of experiments to optimize chemical and biochemical systems based...... on a machine learning process is presented. The optimization proceeds over generations of experiments in iterative loop until optimal compositions are discovered. The fitness function is experimentally measured every time the loop is closed. Two examples of complex systems, namely a liposomal drug formulation...

  6. Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hoda Hosny Abuzied

    2012-01-01

    Full Text Available Electrochemical machining (ECM is a non-traditional machining process used mainly to cut hard or difficult to cut metals, where the application of a more traditional process is not convenient. It offers several special advantages including higher machining rate, better precision and control, and a wider range of materials that can be machined. A suitable selection of machining parameters for the ECM process relies heavily on the operator’s technologies and experience because of their numerous and diverse range. Machining parameters provided by the machine tool builder cannot meet the operator’s requirements. So, artificial neural networks were introduced as an efficient approach to predict the values of resulting surface roughness and material removal rate. Many researchers usedartificial neural networks (ANN in improvement of ECM process and also in other nontraditional machining processes as well be seen in later sections. The present study is, initiated to predict values of some of resulting process parameters such as metal removal rate(MRR, and surface roughness (Ra using artificial neural networks based on variation of certain predominant parameters of an electrochemical broaching process such as applied voltage, feed rate and electrolyte flow rate. ANN was found to be an efficient approach as it reduced time & effort required to predict material removal rate & surface roughness if they were found experimentally using trial & error method. To validate the proposed approach the predicted values of surface roughness and material removal rate were compared with a previously obtained ones from the experimental work.

  7. Machine Vision Applied to Navigation of Confined Spaces

    Science.gov (United States)

    Briscoe, Jeri M.; Broderick, David J.; Howard, Ricky; Corder, Eric L.

    2004-01-01

    The reliability of space related assets has been emphasized after the second loss of a Space Shuttle. The intricate nature of the hardware being inspected often requires a complete disassembly to perform a thorough inspection which can be difficult as well as costly. Furthermore, it is imperative that the hardware under inspection not be altered in any other manner than that which is intended. In these cases the use of machine vision can allow for inspection with greater frequency using less intrusive methods. Such systems can provide feedback to guide, not only manually controlled instrumentation, but autonomous robotic platforms as well. This paper serves to detail a method using machine vision to provide such sensing capabilities in a compact package. A single camera is used in conjunction with a projected reference grid to ascertain precise distance measurements. The design of the sensor focuses on the use of conventional components in an unconventional manner with the goal of providing a solution for systems that do not require or cannot accommodate more complex vision systems.

  8. Machine learning, computer vision, and probabilistic models in jet physics

    CERN Document Server

    CERN. Geneva; NACHMAN, Ben

    2015-01-01

    In this talk we present recent developments in the application of machine learning, computer vision, and probabilistic models to the analysis and interpretation of LHC events. First, we will introduce the concept of jet-images and computer vision techniques for jet tagging. Jet images enabled the connection between jet substructure and tagging with the fields of computer vision and image processing for the first time, improving the performance to identify highly boosted W bosons with respect to state-of-the-art methods, and providing a new way to visualize the discriminant features of different classes of jets, adding a new capability to understand the physics within jets and to design more powerful jet tagging methods. Second, we will present Fuzzy jets: a new paradigm for jet clustering using machine learning methods. Fuzzy jets view jet clustering as an unsupervised learning task and incorporate a probabilistic assignment of particles to jets to learn new features of the jet structure. In particular, we wi...

  9. Multimedia extensions to prototyping software for machine vision

    Science.gov (United States)

    Batchelor, Bruce G.; Griffiths, Eric C.; Hack, Ralf; Jones, Andrew C.

    1996-10-01

    PIP (prolog image processing) is a prototyping tool, intended to assists designers of intelligent industrial machine vision systems. This article concentrates on the multi-media extensions to PIP, including: 1) on-line HELP, which allows the user to satisfy PIP goals from within the HELP facility, 2) lighting advisor, which gives advice to a vision engineer about which lighting/viewing arrangement is appropriate to use in a given situation, 3) device control, for operating a robot work cell, 4) speech input and (simple) natural language understanding, 5) speech synthesis, 6) remote operation of PIP via a local area network, and 7) remote operation of PIP via a local area network. At the time of writing, on-line access to PIP, via the Internet, is being developed.

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

    Science.gov (United States)

    Pearson, Tom C.

    1995-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-07-01

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

  12. Engineering artificial machines from designable DNA materials for biomedical applications.

    Science.gov (United States)

    Qi, Hao; Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng; Wang, Lin

    2015-06-01

    Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications.

  13. Accurate measurement method for tube's endpoints based on machine vision

    Science.gov (United States)

    Liu, Shaoli; Jin, Peng; Liu, Jianhua; Wang, Xiao; Sun, Peng

    2017-01-01

    Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube's endpoints based on machine vision is proposed. First, reflected light on tube's surface can be removed by using photometric linearization. Then, based on the optimization model for the tube's endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube's endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  14. Accurate Measurement Method for Tube's Endpoints Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    LIU Shaoli; JIN Peng; LIU Jianhua; WANG Xiao; SUN Peng

    2017-01-01

    Tubes are used widely in aerospace vehicles,and their accurate assembly can directly affect the assembling reliability and the quality of products.It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly.However,the traditional tube inspection method is time-consuming and complex operations.Therefore,a new measurement method for a tube's endpoints based on machine vision is proposed.First,reflected light on tube's surface can be removed by using photometric linearization.Then,based on the optimization model for the tube's endpoint measurements and the principle of stereo matching,the global coordinates and the relative distance of the tube's endpoint are obtained.To confirm the feasibility,11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured.The experiment results show that the measurement repeatability accuracy is 0.167 mm,and the absolute accuracy is 0.328 mm.The measurement takes less than 1 min.The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  15. Accurate measurement method for tube's endpoints based on machine vision

    Science.gov (United States)

    Liu, Shaoli; Jin, Peng; Liu, Jianhua; Wang, Xiao; Sun, Peng

    2016-08-01

    Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube's endpoints based on machine vision is proposed. First, reflected light on tube's surface can be removed by using photometric linearization. Then, based on the optimization model for the tube's endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube's endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  16. Vision-Based People Detection System for Heavy Machine Applications

    Directory of Open Access Journals (Sweden)

    Vincent Fremont

    2016-01-01

    Full Text Available This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

  17. Introduction to Artificial Vision through Laboratory Guides Using Matlab

    Directory of Open Access Journals (Sweden)

    Verónica Londoño-Osorio

    2013-11-01

    Full Text Available This paper presents the design of two laboratory guides in artificial vision for a course which aims to introduce students to the different areas of specialization of his career. Therefore, the designed practices motivate and provide relevant content to the student, and to encourage research in the area of image processing. The first guide presents an introductory practice that explores the basic commands for image processing by programming a GUI in Matlab, and a second practice in which you use an image recognition algorithm, which compares the color characteristics of facial or objects images. The discussion of the results, challenges and recommendations for the development of each practice session are explained. The survey answers of the students are displayed. This survey allows checking their level of acceptance for the design and content of practice and motivation to continue studying in the image processing area. Finally, comparisons with laboratory guides that were designed in other universities are made.

  18. Mechanical characterization of artificial muscles with computer vision

    Science.gov (United States)

    Verdu, R.; Morales-Sanchez, Juan; Fernandez-Romero, Antonio J.; Cortes, M. T.; Otero, Toribio F.; Weruaga-Prieto, Luis

    2002-07-01

    Conducting polymers are new materials that were developed in the late 1970s as intrinsically electronic conductors at the molecular level. The presence of polymer, solvent, and ionic components reminds one of the composition of the materials chosen by nature to produce muscles, neurons, and skin in living creatures. The ability to transform electrical energy into mechanical energy through an electrochemical reaction, promoting film swelling and shrinking during oxidation or reduction, respectively, produces a macroscopic change in its volume. On specially designed bi-layer polymeric stripes this conformational change gives rise to stripe curl and bending, where the position or angle of the free end of the polymeric stripe is directly related to the degree of oxidation, or charged consumed. Study of these curvature variations has been currently performed only in a manual basis. In this paper we propose a preliminary study of the polymeric muscle electromechanical properties by using a computer vision system. The vision system required is simple: it is composed of cameras for tracking the muscle from different angles and special algorithms, based on active contours, to analyse the deformable motion. Graphical results support the validity of this approach, which opens the way for performing automatic testing on artificial muscles with commercial purposes.

  19. Applying artificial vision models to human scene understanding

    Directory of Open Access Journals (Sweden)

    Elissa Michele Aminoff

    2015-02-01

    Full Text Available How do we understand the complex patterns of neural responses that underlie scene understanding? Studies of the network of brain regions held to be scene-selective – the parahippocampal/lingual region (PPA, the retrosplenial complex (RSC, and the occipital place area (TOS – have typically focused on single visual dimensions (e.g., size, rather than the high-dimensional feature space in which scenes are likely to be neurally represented. Here we leverage well-specified artificial vision systems to explicate a more complex understanding of how scenes are encoded in this functional network. We correlated similarity matrices within three different scene-spaces arising from: 1 BOLD activity in scene-selective brain regions; 2 behavioral measured judgments of visually-perceived scene similarity; and 3 several different computer vision models. These correlations revealed: 1 models that relied on mid- and high-level scene attributes showed the highest correlations with the patterns of neural activity within the scene-selective network; 2 NEIL and SUN – the models that best accounted for the patterns obtained from PPA and TOS – were different from the GIST model that best accounted for the pattern obtained from RSC; 3 The best performing models outperformed behaviorally-measured judgments of scene similarity in accounting for neural data. One computer vision method – NEIL (Never-Ending-Image-Learner, which incorporates visual features learned as statistical regularities across web-scale numbers of scenes – showed significant correlations with neural activity in all three scene-selective regions and was one of the two models best able to account for variance in the PPA and TOS. We suggest that these results are a promising first step in explicating more fine-grained models of neural scene understanding, including developing a clearer picture of the division of labor among the components of the functional scene-selective brain network.

  20. An artificial vision solution for reusing discarded parts resulted after a manufacturing process

    Science.gov (United States)

    Cohal, V.; Cohal, A.

    2016-08-01

    The profit of a factory can be improved by reusing the discarded components produced. This paper is based on the case of a manufacturing process where rectangular metallic sheets of different sizes are produced. Using an artificial vision system, the shapes and the sizes of the produced parts can be determined. Those sheets which do not respect the requirements imposed are labeled as discarded. Instead of throwing these parts, a decision algorithm can analyze if another metallic sheet with smaller dimensions can be obtained from these. Two methods of decision are presented in this paper, considering the restriction that the sides of the new sheet has to be parallel with the axis of the coordinate system. The coordinates of each new part obtained from a discarded sheet are computed in order to be delivered to a milling machine. Details about implementing these algorithms (image processing and decision respectively) in the MATLAB environment using Image Processing Toolbox are given.

  1. 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...

  2. Using Multiple FPGA Architectures for Real-time Processing of Low-level Machine Vision Functions

    Science.gov (United States)

    Thomas H. Drayer; William E. King; Philip A. Araman; Joseph G. Tront; Richard W. Conners

    1995-01-01

    In this paper, we investigate the use of multiple Field Programmable Gate Array (FPGA) architectures for real-time machine vision processing. The use of FPGAs for low-level processing represents an excellent tradeoff between software and special purpose hardware implementations. A library of modules that implement common low-level machine vision operations is presented...

  3. Characterization of oats (Avena sativa L.) cultivars using machine vision.

    Science.gov (United States)

    Sumathi, S; Balamurugan, P

    2013-10-15

    Machine vision or image analysis is an important tool in the study of morphology of any materials. This technique has been used successfully to differentiate the eleven oats cultivars based on morphological characters. The geometry of seeds was measured through image analyzer and the variation was observed and recorded. From the recorded data, the cluster analysis was carried out and it revealed that the cultivars could be grouped into two main clusters based on similarity in the measured parameters. Cultivar Sabzar, UPO 212, OL 9 and OL 88 formed one main cluster. The another main cluster includes cv. Kent, OS 6, UPO 94, HFO 114, OS 7, HJ 8 and JHO 822 with many sub clusters. Among the cultivars HJ 8 and JHO 822 has more similarity in all measured parameters than other cultivars. Thus morphological characterization through seed image analysis was found useful to discriminate the cultivars.

  4. FUSION OF MULTI FOCUSED IMAGES USING HDWT FOR MACHINE VISION

    Directory of Open Access Journals (Sweden)

    S. Arumuga Perumal

    2011-10-01

    Full Text Available During image acquisition in machine vision, due to limited depth of field of lens, it is possible to take clear image of the objects in the scene which are in focus only. The remaining objects in the scene will be out of focus. A possible solution to bring clear images of all objects in the scene is image fusion. Image fusion is a process of combining multiple images to form the composite image with extended information content. This paper uses three band expansive higher density discrete wavelet transform to fuse two numbers of images focusing different objects in the same scene and also proposes three methods for image fusion. Experimental results on multi focused image fusion are presented in terms of root mean square, peak signal to noise ratio and quality index to illustrate the proposed fusion methods.

  5. Brake Pedal Displacement Measuring System based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Chang Wang

    2013-10-01

    Full Text Available Displacement of brake pedal was an important characteristic of driving behavior. This paper proposed a displacement measure algorithm based on machine vision. Image of brake pedal was captured by camera from left side, and images were processed in industry computer. Firstly, average smooth algorithm and wavelet transform algorithm were used to smooth the original image consecutively. Then, edge extracting method which combined Roberts’s operator with wavelet analysis was used to identify the edge of brake pedal. At last, least square method was adopted to recognize the characteristic line of brake pedal’s displacement. The experimental results demonstrated that the proposed method takes the advantages of Roberts’s operator and wavelet transform, it can obtain better measurement result as well as linear displacement sensors

  6. Machine vision inspection of rice seed based on Hough transform

    Institute of Scientific and Technical Information of China (English)

    成芳; 应义斌

    2004-01-01

    A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

  7. Machine vision inspection of rice seed based on Hough transform

    Institute of Scientific and Technical Information of China (English)

    成芳; 应义斌

    2004-01-01

    A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402,Shanyou 10, Zhongyou207, Jiayou and Ilyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

  8. Application of Machine Vision to Vehicle Automatic Collision Warning Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Jiang-feng; GAO Feng; XU Guo-yan; YAO Sheng-zhuo

    2008-01-01

    Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system(CWS) can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver's driving behavior, algorithm's warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm(CWA) model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.

  9. The Employment Effects of High-Technology: A Case Study of Machine Vision. Research Report No. 86-19.

    Science.gov (United States)

    Chen, Kan; Stafford, Frank P.

    A case study of machine vision was conducted to identify and analyze the employment effects of high technology in general. (Machine vision is the automatic acquisition and analysis of an image to obtain desired information for use in controlling an industrial activity, such as the visual sensor system that gives eyes to a robot.) Machine vision as…

  10. Environmentally Conscious Polishing System Based on Robotics and Artificial Vision

    Directory of Open Access Journals (Sweden)

    J. A. Dieste

    2015-02-01

    Full Text Available Polishing process is one of the manufacturing issues that are essential in the production flow, but it generates the major amount of defects on parts. Finishing tasks in which polishing is included are performed in the final steps of the manufacturing sequence. Any defect in these steps impliesrejection of the part, generating a big amount of scrap and generating a huge amount of energy consumption, emission, and time to manufacture and replace the rejected part. Traditionally polishing process has not evolved during the last 30 years, while other manufacturing processes have been automated and technologically improved. Finishing processes (grinding and polishing, are still manually performed, especially in freeform surface parts, but to be sustainable some development and automation have to be introduced. This research proposes a novel polishing system based on robotics and artificial vision. The application of this novel system has allowed reducing the failed parts due to finishing process down to zero percent from 28% of rejected parts with manual polishing process. The reduction in process time consumption, and amount of scrapped parts, has reduced the energy consumption up to 30% in finishing process and 20% in whole manufacturing process for an injection moulded aluminium part for automotive industry with high production volumes.

  11. Stereoscopic Machine-Vision System Using Projected Circles

    Science.gov (United States)

    Mackey, Jeffrey R.

    2010-01-01

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

  12. The Embryonics Project: a machine made of artificial cells.

    Science.gov (United States)

    Tempesti, G; Mange, D; Stauffer, A

    1999-01-01

    It is possible to trace the origins of biological inspiration in the design of electronic circuits to the very dawn of the field of computer engineering, with the work of John von Neumann in the 1940s. To his brilliance we owe not only the first methodical attempts to define the electronic equivalents of many fundamental biological process, but also the development of the first self-replicating computing machines. Unfortunately, the electronic technology of the time would not allow a physical realization of von Neumann's machines, and it was not until the introduction of new programmable circuits in the 1980s that the field of bio-inspired machines gained new momentum. In this article, we describe the Embryonics (embryonic electronics) Project, an attempt to draw inspiration from the ontogenetic processes that determine the growth of multicellular organisms in the design of new, massively parallel arrays of processors (the artificial cells). Our cells are simple processors, all based on an identical hardware structure and all containing the same program (our artificial genome), but executing different parts of the genome depending on their spatial coordinates within the array. As in living beings, the presence of the genome in every cell allows the introduction of features such as self-replication and self-repair (cicatrization). In addition, the cells are implemented using an array of programmable elements (the artificial molecules), which allows their structure to be adapted to a given application. Through the parallel operation of many of these simple processors, we hope to realize highly complex systems, the equivalent of multicellular organisms in the natural world.

  13. Artificial Molecular Machine Immobilized Surfaces: A New Platform To Construct Functional Materials.

    Science.gov (United States)

    Zhang, Qi; Qu, Da-Hui

    2016-06-17

    Artificial molecular machines have received significant attention from chemists because of their unique ability to mimic the behaviors of biological systems. Artificial molecular machines can be easily modified with functional groups to construct new types of functional molecular switches. However, practical applications of artificial molecular machines are still challenging, because the working platform of artificial molecular machines is mostly in solution. Artificial molecular machine immobilized surfaces (AMMISs) are considered a promising platform to construct functional materials. Herein, we provide a minireview of some recent advances of functional AMMISs. The functions of AMMISs are highlighted and strategies for their construction are also discussed. Furthermore, a brief perspective of the development of artificial molecular machines towards functional materials is given.

  14. 3-D measuring of engine camshaft based on machine vision

    Science.gov (United States)

    Qiu, Jianxin; Tan, Liang; Xu, Xiaodong

    2008-12-01

    The non-touch 3D measuring based on machine vision is introduced into camshaft precise measuring. Currently, because CCD 3-dimensional measuring can't meet requirements for camshaft's measuring precision, it's necessary to improve its measuring precision. In this paper, we put forward a method to improve the measuring method. A Multi-Character Match method based on the Polygonal Non-regular model is advanced with the theory of Corner Extraction and Corner Matching .This method has solved the problem of the matching difficulty and a low precision. In the measuring process, the use of the Coded marked Point method and Self-Character Match method can bring on this problem. The 3D measuring experiment on camshaft, which based on the Multi-Character Match method of the Polygonal Non-regular model, proves that the normal average measuring precision is increased to a new level less than 0.04mm in the point-clouds photo merge. This measuring method can effectively increase the 3D measuring precision of the binocular CCD.

  15. Prolog-based prototyping software for machine vision

    Science.gov (United States)

    Batchelor, Bruce G.; Hack, Ralf; Jones, Andrew C.

    1996-10-01

    Prolog image processing (PIP) is a multi-media prototyping tool, intended to assist designers of intelligent industrial machine vision systems. This is the latest in a series of prolog-based systems that have been implemented at Cardiff, specifically for this purpose. The software package provides fully integrated facilities for both interactive and programmed image processing, 'smart' documentation, guidance about which lighting/viewing set-up to use, speech/natural language input and speech output. It can also be used to control a range of electro-mechanical devices, such as lamps, cameras, lenses, pneumatic positioning mechanisms, robots, etc., via a low-cost hardware interfacing module. The software runs on a standard computer, with no predecessors in that the image processing is carried out entirely in software. This article concentrates on the design and implementation of the PIP system, and presents programs for two demonstration applications: (a) recognizing a non-picture playing card; (b) recognizing a well laid table place setting.

  16. A Machine Vision System for Quality Inspection of Pine Nuts

    Directory of Open Access Journals (Sweden)

    Ikramullah Khosa

    2016-09-01

    Full Text Available Computers and artificial intelligence have penetrated in the food industry since last decade, for intellectual automatic processing and packaging in general, and in assisting for quality inspection of the food itself in particular. The food quality assessment task becomes more challenging when it is about harmless internal examination of the ingredient, and even more when its size is also minute. In this article, a method for automatic detection, extraction and classification of raw food item is presented using x-ray image data of pine nuts. Image processing techniques are employed in developing an efficient method for automatic detection and then extraction of individual ingredient, from the source x-ray image which comprises bunch of nuts in a single frame. For data representation, statistical texture analysis is carried out and attributes are calculated from each of the sample image on the global level as features. In addition co-occurrence matrices are computed from images with four different offsets, and hence more features are extracted by using them. To find fewer meaningful characteristics, all the calculated features are organized in several combinations and then tested. Seventy percent of image data is used for training and 15% each for cross-validation and test purposes. Binary classification is performed using two state-of-the-art non-linear classifiers: Artificial Neural Network (ANN and Support Vector Machines (SVM. Performance is evaluated in terms of classification accuracy, specificity and sensitivity. ANN classifier showed 87.6% accuracy with correct recognition rate of healthy nuts and unhealthy nuts as 94% and 62% respectively. SVM classifier produced the similar accuracy achieving 86.3% specificity and 89.2% sensitivity rate. The results obtained are unique itself in terms of ingredient and promising relatively. It is also found that feature set size can be reduced up to 57% by compromising 3.5% accuracy, in combination with

  17. Potato Size and Shape Detection Using Machine Vision

    Directory of Open Access Journals (Sweden)

    Liao Guiping

    2015-01-01

    Full Text Available To reduce the error and faster classification by mechanizing in classifying the potato shape and size through machine vision using the extraction of characters procedure to identify the size, and using the shape detection procedure to identify the shape. Test results in potato size detection revealed 40/191 = 0.210mm/pixel as length scale or calibration factor (40/M where 40 is the table tennis ball size (40mm and 191 as image pixels table tennis (M; measurement results revealed that between the algorithm results and the manual measurements, the absolute error was <3mm, while the relative error rate was <4%; and the measurement results based on the ellipse axis length can accurately calculate the actual long axis and short axis of potato. Potato shape detection revealed the analysis of 228 images composed of 114 positive and 114 negatives side, only 2 have been incorrectly classified, mainly because the Extracted ratio (R of the potato image of those two positive and negative images are near 0.67, respectively 0.671887, 0.661063, 0.667604, and 0.67193. The comparison to establish a calibration system method using both basic rectangle and ellipse R ratio methods to detect the potato size and shape, revealed that the basic rectangle method has better effect in the case of fixed place. Moreover, the ellipse axis method was observed to be more stable with an error rate of 7%. Therefore it is recommended that the ellipse axis method should be used to detect the shape of potato for differentiation into round, long cylindrical, and oval shapes, with the accuracy level of 98.8%.

  18. Machine Vision for Relative Spacecraft Navigation During Approach to Docking

    Science.gov (United States)

    Chien, Chiun-Hong; Baker, Kenneth

    2011-01-01

    This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

  19. Artificial emotional model based on finite state machine

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-mei; WU Wei-guo

    2008-01-01

    According to the basic emotional theory, the artificial emotional model based on the finite state machine(FSM) was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition function was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform.And the model included three subsystems: the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input (also a state-emotion). The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

  20. Ethical, environmental and social issues for machine vision in manufacturing industry

    Science.gov (United States)

    Batchelor, Bruce G.; Whelan, Paul F.

    1995-10-01

    Some of the ethical, environmental and social issues relating to the design and use of machine vision systems in manufacturing industry are highlighted. The authors' aim is to emphasize some of the more important issues, and raise general awareness of the need to consider the potential advantages and hazards of machine vision technology. However, in a short article like this, it is impossible to cover the subject comprehensively. This paper should therefore be seen as a discussion document, which it is hoped will provoke more detailed consideration of these very important issues. It follows from an article presented at last year's workshop. Five major topics are discussed: (1) The impact of machine vision systems on the environment; (2) The implications of machine vision for product and factory safety, the health and well-being of employees; (3) The importance of intellectual integrity in a field requiring a careful balance of advanced ideas and technologies; (4) Commercial and managerial integrity; and (5) The impact of machine visions technology on employment prospects, particularly for people with low skill levels.

  1. Musca domestica inspired machine vision system with hyperacuity

    Science.gov (United States)

    Riley, Dylan T.; Harman, William M.; Tomberlin, Eric; Barrett, Steven F.; Wilcox, Michael; Wright, Cameron H. G.

    2005-05-01

    Musca domestica, the common house fly, has a simple yet powerful and accessible vision system. Cajal indicated in 1885 the fly's vision system is the same as in the human retina. The house fly has some intriguing vision system features such as fast, analog, parallel operation. Furthermore, it has the ability to detect movement and objects at far better resolution than predicted by photoreceptor spacing, termed hyperacuity. We are investigating the mechanisms behind these features and incorporating them into next generation vision systems. We have developed a prototype sensor that employs a fly inspired arrangement of photodetectors sharing a common lens. The Gaussian shaped acceptance profile of each sensor coupled with overlapped sensor field of views provide the necessary configuration for obtaining hyperacuity data. The sensor is able to detect object movement with far greater resolution than that predicted by photoreceptor spacing. We have exhaustively tested and characterized the sensor to determine its practical resolution limit. Our tests coupled with theory from Bucklew and Saleh (1985) indicate that the limit to the hyperacuity response may only be related to target contrast. We have also implemented an array of these prototype sensors which will allow for two - dimensional position location. These high resolution, low contrast capable sensors are being developed for use as a vision system for an autonomous robot and the next generation of smart wheel chairs. However, they are easily adapted for biological endoscopy, downhole monitoring in oil wells, and other applications.

  2. Hand gesture recognition system based in computer vision and machine learning

    OpenAIRE

    Trigueiros, Paulo; Ribeiro, António Fernando; Reis, L.P.

    2015-01-01

    "Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19" Hand gesture recognition is a natural way of human computer interaction and an area of very active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Hum...

  3. Computer vision and machine learning with RGB-D sensors

    CERN Document Server

    Shao, Ling; Kohli, Pushmeet

    2014-01-01

    This book presents an interdisciplinary selection of cutting-edge research on RGB-D based computer vision. Features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption and obtain accurate action classification; presents an approach for 3D object retrieval and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist t

  4. The systematic development of a machine vision based milking robot.

    NARCIS (Netherlands)

    Gouws, J.

    1993-01-01

    Agriculture involves unique interactions between man, machines, and various elements from nature. Therefore the implementation of advanced technology in agriculture holds different challenges than in other sectors of the economy. This dissertation stems from research into the application of advanced

  5. Machine Vision Automation for Ground Control Tele-Robotics Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This project seeks to advance ground based tele-robotic capabilities with the development of natural feature target tracking technology with the use of machine...

  6. Measuring Leaf Motion of Tomato by Machine Vision

    NARCIS (Netherlands)

    Henten, van E.J.; Marx, G.E.H.; Hofstee, J.W.; Hemming, J.; Sarlikioti, V.

    2012-01-01

    For a better understanding of growth and development of tomato plants in three dimensional space, tomato plants were monitored using a computer vision system. It is commonly known that leaves of tomato plants do not have a fixed position and orientation during the day; they move in response to chang

  7. On-line estimation of laser-drilled hole depth using a machine vision method.

    Science.gov (United States)

    Ho, Chao-Ching; He, Jun-Jia; Liao, Te-Ying

    2012-01-01

    The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time. Therefore, a low cost on-line inspection system is developed to increase productivity. All of the processing work was performed in air under standard atmospheric conditions and gas assist was used. A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented. The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence. This research provides a novel machine vision-based method for estimating the depths of laser-drilled holes in real time.

  8. On-Line Estimation of Laser-Drilled Hole Depth Using a Machine Vision Method

    Directory of Open Access Journals (Sweden)

    Te-Ying Liao

    2012-07-01

    Full Text Available The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time. Therefore, a low cost on-line inspection system is developed to increase productivity. All of the processing work was performed in air under standard atmospheric conditions and gas assist was used. A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented. The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence. This research provides a novel machine vision-based method for estimating the depths of laser-drilled holes in real time.

  9. 75 FR 71146 - In the Matter of Certain Machine Vision Software, Machine Vision Systems, and Products Containing...

    Science.gov (United States)

    2010-11-22

    ..., California; Techno Soft Systemnics, Inc. (``Techno Soft'') of Japan; Fuji Machine Manufacturing Co., Ltd. of... the investigation as to Amistar based on a consent order and settlement agreement, and as to...

  10. Application of Artificial Intelligence Methods of Tool Path Optimization in CNC Machines: A Review

    Directory of Open Access Journals (Sweden)

    Khashayar Danesh Narooei

    2014-08-01

    Full Text Available Today, in most of metal machining process, Computer Numerical Control (CNC machine tools have been very popular due to their efficiencies and repeatability to achieve high accuracy positioning. One of the factors that govern the productivity is the tool path travel during cutting a work piece. It has been proved that determination of optimal cutting parameters can enhance the machining results to reach high efficiency and minimum the machining cost. In various publication and articles, scientist and researchers adapted several Artificial Intelligence (AI methods or hybrid method for tool path optimization such as Genetic Algorithms (GA, Artificial Neural Network (ANN, Artificial Immune Systems (AIS, Ant Colony Optimization (ACO and Particle Swarm Optimization (PSO. This study presents a review of researches in tool path optimization with different types of AI methods that show the capability of using different types of optimization methods in CNC machining process.

  11. Machine vision-based high-resolution weed mapping and patch-sprayer performance simulation

    NARCIS (Netherlands)

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

    1999-01-01

    An experimental machine vision-based patch-sprayer was developed. This sprayer was primarily designed to do real-time weed density estimation and variable herbicide application rate control. However, the sprayer also had the capability to do high-resolution weed mapping if proper mapping techniques

  12. 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...

  13. Gall mite inspection on dormant black currant buds using machine vision

    DEFF Research Database (Denmark)

    Nielsen, M. R.; Stigaard Laursen, Morten; Jonassen, M. S.

    2013-01-01

    This paper presents a novel machine vision-based approach detecting and mapping gall mite infection in dormant buds on black currant bushes. A vehicle was fitted with four cameras and RTK-GPS. Results compared automatic detection to human decisions based on the images, and by mapping the results ...

  14. Machine vision analysis for industrial beet color change kinetics and total soluble solid content

    Science.gov (United States)

    A machine vision system (MVS) for the measurement of color change kinetics in crushed industrial beet to evaluate the total soluble solid content (°Brix) was developed in this study. It is expected that higher the °Brix faster the color change and modeling this color change kinetics helps in assessi...

  15. 3D Machine Vision and Additive Manufacturing: Concurrent Product and Process Development

    Science.gov (United States)

    Ilyas, Ismet P.

    2013-06-01

    The manufacturing environment rapidly changes in turbulence fashion. Digital manufacturing (DM) plays a significant role and one of the key strategies in setting up vision and strategic planning toward the knowledge based manufacturing. An approach of combining 3D machine vision (3D-MV) and an Additive Manufacturing (AM) may finally be finding its niche in manufacturing. This paper briefly overviews the integration of the 3D machine vision and AM in concurrent product and process development, the challenges and opportunities, the implementation of the 3D-MV and AM at POLMAN Bandung in accelerating product design and process development, and discusses a direct deployment of this approach on a real case from our industrial partners that have placed this as one of the very important and strategic approach in research as well as product/prototype development. The strategic aspects and needs of this combination approach in research, design and development are main concerns of the presentation.

  16. Research and application of visual location technology for solder paste printing based on machine vision

    Institute of Scientific and Technical Information of China (English)

    Luosi WEI; Zongxia JIAO

    2009-01-01

    A location system is very important for solder paste printing in the process of surface mount technology (SMT). Using machine vision technology to complete the location mission is new and very efficient. This paper presents an integrated visual location system for solder paste printing based on machine vision. The working principle of solder paste printing is introduced and then the design and implementation of the visual location system are described. In the system, two key techniques are completed by secondary development based on VisionPro.One is accurate image location solved by the pattern-based location algorithms of PatMax. The other one is camera calibration that is achieved by image warping technology through the checkerboard plate. Moreover, the system can provide good performances such as high image locating accuracy with 1/40 sub-pixels, high anti-jamming, and high-speed location of objects whose appearance is rotated, scaled, and/or stretched.

  17. Electrical Stimulation of the Retina to Produce Artificial Vision.

    Science.gov (United States)

    Weiland, James D; Walston, Steven T; Humayun, Mark S

    2016-10-14

    Retinal prostheses aim to restore vision to blind individuals suffering from retinal diseases such as retinitis pigmentosa and age-related macular degeneration. These devices function by electrically stimulating surviving retinal neurons, whose activation is interpreted by the brain as a visual percept. Many prostheses are currently under development. They are categorized as epiretinal, subretinal, and suprachoroidal prostheses on the basis of the placement of the stimulating microelectrode array. Each can activate ganglion cells through direct or indirect stimulation. The response of retinal neurons to these modes of stimulation are discussed in detail and are placed in context of the visual percept they are likely to evoke. This article further reviews challenges faced by retinal prosthesis and discusses potential solutions to address them.

  18. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  19. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  20. Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

    Directory of Open Access Journals (Sweden)

    Luis Pérez

    2016-03-01

    Full Text Available In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.

  1. Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

    Science.gov (United States)

    Pérez, Luis; Rodríguez, Íñigo; Rodríguez, Nuria; Usamentiaga, Rubén; García, Daniel F.

    2016-01-01

    In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works. PMID:26959030

  2. Design of Experimentation, Artificial Neural Network Simulation and Optimization for Integrated Bamboo Processing Machine

    Directory of Open Access Journals (Sweden)

    P. G. Mehar

    2015-11-01

    Full Text Available In this research work experimentation on integrated bamboo processing machine for splitting and slicing of bamboo has been carried out. This paper presents the experimental investigation of some parameters of integrated bamboo processing machine. In this research paper simulation of experimental data using artificial neural network is carried out. An attempt of minimum-maximum principle has been made to optimize by range bound process for maximizing production rate of integrated bamboo processing machine.

  3. A New Color Constancy Model for Machine Vision

    Institute of Scientific and Technical Information of China (English)

    TAO Linmi; XU Guangyou

    2001-01-01

    Both physiological and psychological evidences suggest that the human visual system analyze images in neural subsystems tuned to different attributes of the stimulus. Color module and lightness module are such subsystems. Under this general result, a new physical model of trichromatic system has been developed to deal with the color constancy of computer vision. A normal color image is split into two images: the gray scale image and the equal lightness color image for the two modules. Relatively, a two-dimensional descriptor is applied to describe the property of surface reflectance in the equal lightness color image. This description of surface spectral reflectance has the property of color constancy. Image segmentation experiments based on color property of object show that the presented model is effective.

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

    Science.gov (United States)

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

    2017-03-14

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

  5. 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.

  6. 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.

  7. Desarrollo de un caso practico de aprendizaje combinando vision artificial y un brazo robot

    OpenAIRE

    Pallejà Cabrè, Tomàs; Teixidó Cairol, Mercè; Font Calafell, Davinia; Tresánchez Ribes, Marcel; Palacín Roca, Jordi

    2013-01-01

    This work describes a learning case developed in the University of Lleida, Spain. This proposal is addressed to third course engineering students that must combine knowledge from artificial vision and robotic control to complete an automation task. The objective is the detection of a small object placed randomly on a surface to recollect and store it with a robotic arm. The educational results of this experience have shown that the development of a learning case based on the combination of ar...

  8. An Early Underwater Artificial Vision Model in Ocean Investigations via Independent Component Analysis

    Science.gov (United States)

    Nian, Rui; Liu, Fang; He, Bo

    2013-01-01

    Underwater vision is one of the dominant senses and has shown great prospects in ocean investigations. In this paper, a hierarchical Independent Component Analysis (ICA) framework has been established to explore and understand the functional roles of the higher order statistical structures towards the visual stimulus in the underwater artificial vision system. The model is inspired by characteristics such as the modality, the redundancy reduction, the sparseness and the independence in the early human vision system, which seems to respectively capture the Gabor-like basis functions, the shape contours or the complicated textures in the multiple layer implementations. The simulation results have shown good performance in the effectiveness and the consistence of the approach proposed for the underwater images collected by autonomous underwater vehicles (AUVs). PMID:23863855

  9. An Early Underwater Artificial Vision Model in Ocean Investigations via Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Bo He

    2013-07-01

    Full Text Available Underwater vision is one of the dominant senses and has shown great prospects in ocean investigations. In this paper, a hierarchical Independent Component Analysis (ICA framework has been established to explore and understand the functional roles of the higher order statistical structures towards the visual stimulus in the underwater artificial vision system. The model is inspired by characteristics such as the modality, the redundancy reduction, the sparseness and the independence in the early human vision system, which seems to respectively capture the Gabor-like basis functions, the shape contours or the complicated textures in the multiple layer implementations. The simulation results have shown good performance in the effectiveness and the consistence of the approach proposed for the underwater images collected by autonomous underwater vehicles (AUVs.

  10. Internet of Things and Artificial Vision, Performance and Applications: Literature Review

    Directory of Open Access Journals (Sweden)

    Vanessa Alvear-Puertas

    2017-02-01

    Full Text Available Internet of Things (or also known as IoT is one of the technologies most named today because of the ability it envisages to connect all kinds of devices to the Internet. If to the potentialities of IoT we add another technology of high impact as It is the Artificial Vision we have a wide field of innovative applications, where the processing of images and video in real time allow the visualization of large amounts of data on the Internet. The main applications developed with IoT and Artificial Vision can be implemented in education, medicine, intelligent buildings, surveillance systems of people and vehicles, among others. This type of applications improves the quality of life of users, however, for their development an infrastructure is required that allows the convergence of different protocols and devices, but in a special way that can handle the different phases of the acquisition of images. In this work, a review of the beginnings, concepts, technologies and applications related to the Artificial Vision with the Internet of Things has been carried out to be able to understand in a precise way the impact of its application in daily life.

  11. A review of RGB-LED based mixed-color illumination system for machine vision and microscopy

    Science.gov (United States)

    Hou, Lexin; Wang, Hexin; Xu, Min

    2016-09-01

    The theory and application of RGB-LED based mixed-color illumination system for use in machine vision and optical microscopy systems are presented. For machine vision system, relationship of various color sources and output image sharpness is discussed. From the viewpoint of gray scale images, evaluation and optimization methods of optimal illumination for machine vision are concluded. The image quality under monochromatic and mixed color illumination is compared. For optical microscopy system, demand of light source is introduced and design thoughts of RGB-LED based mixed-color illumination system are concluded. The problems need to be solved in this field are pointed out.

  12. Prediction of shelled shrimp weight by machine vision.

    Science.gov (United States)

    Pan, Peng-min; Li, Jian-ping; Lv, Gu-lai; Yang, Hui; Zhu, Song-ming; Lou, Jian-zhong

    2009-08-01

    The weight of shelled shrimp is an important parameter for grading process. The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness. In this paper, a multivariate prediction model containing area, perimeter, length, and width was established. A new calibration algorithm for extracting length of shelled shrimp was proposed, which contains binary image thinning, branch recognition and elimination, and length reconstruction, while its width was calculated during the process of length extracting. The model was further validated with another set of images from 30 shelled shrimps. For a comparison purpose, artificial neural network (ANN) was used for the shrimp weight predication. The ANN model resulted in a better prediction accuracy (with the average relative error at 2.67%), but took a tenfold increase in calculation time compared with the weight-area-perimeter (WAP) model (with the average relative error at 3.02%). We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.

  13. Prediction of shelled shrimp weight by machine vision

    Institute of Scientific and Technical Information of China (English)

    Peng-min PAN; Jian-ping LI; Gu-lai LV; Hui YANG; Song-ming ZHU; Jian-zhong LOU

    2009-01-01

    The weight of shelled shrimp is an important parameter for grading process. The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness. In this paper, a multivariate prediction model containing area, perimeter, length, and width was established. A new calibration algorithm for extracting length of shelled shrimp was proposed, which contains binary image thinning, branch recognition and elimination, and length reconstruction, while its width was calculated during the process of length extracting. The model was further validated with another set of images from 30 shelled shrimps. For a comparison purpose, artificial neural network (ANN) was used for the shrimp weight predication. The ANN model resulted in a better prediction accuracy (with the average relative error at 2.67%), but took a tenfold increase in calculation time compared with the weight-area-perimeter (WAP) model (with the average relative error at 3.02%). We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.

  14. A two-level real-time vision machine combining coarse and fine grained parallelism

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Kjær-Nielsen, Anders; Pauwels, Karl;

    2010-01-01

    In this paper, we describe a real-time vision machine having a stereo camera as input generating visual information on two different levels of abstraction. The system provides visual low-level and mid-level information in terms of dense stereo and optical flow, egomotion, indicating areas...... a factor 90 and a reduction of latency of a factor 26 compared to processing on a single CPU--core. Since the vision machine provides generic visual information it can be used in many contexts. Currently it is used in a driver assistance context as well as in two robotic applications....... with independently moving objects as well as a condensed geometric description of the scene. The system operates at more than 20 Hz using a hybrid architecture consisting of one dual--GPU card and one quad-core CPU. The different processing stages of visual information have rather different characteristics...

  15. Quantifying nonhomogeneous colors in agricultural materials. Part II: comparison of machine vision and sensory panel evaluations.

    Science.gov (United States)

    Balaban, M O; Aparicio, J; Zotarelli, M; Sims, C

    2008-11-01

    The average colors of mangos and apples were measured using machine vision. A method to quantify the perception of nonhomogeneous colors by sensory panelists was developed. Three colors out of several reference colors and their perceived percentage of the total sample area were selected by untrained panelists. Differences between the average colors perceived by panelists and those from the machine vision were reported as DeltaE values (color difference error). Effects of nonhomogeneity of color, and using real samples or their images in the sensory panels on DeltaE were evaluated. In general, samples with more nonuniform colors had higher DeltaE values, suggesting that panelists had more difficulty in evaluating more nonhomogeneous colors. There was no significant difference in DeltaE values between the real fruits and their screen image, therefore images can be used to evaluate color instead of the real samples.

  16. Enhanced Machine Vision System for Ripe Fruit Detection Based on Robotic Harvesting

    Directory of Open Access Journals (Sweden)

    R. Thendral

    2015-04-01

    Full Text Available The proposed work intends to provide an efficient algorithm for the instruction of an automatic robot arm to choose the ripe fruits on the tree. Steps involved in this study are recognizing and locating the ripe fruits from the leaf and branch portions by using an efficient machine vision algorithm. Initially, discrete wavelet transform is used for better preserving of edges and fine details in the given input image. Then RGB, HSV, L*a*b* and YIQ color spaces were studied to segment the ripe fruits from the surrounding objects. Finally, the results showed that ‘I’ component of the YIQ color space has the best criterion for recognizing the fruit from the foliage. The fruit segmentation based on machine vision has an occlusion problem. In this proposed method these problems are also examined.

  17. Principles of image processing in machine vision systems for the color analysis of minerals

    Science.gov (United States)

    Petukhova, Daria B.; Gorbunova, Elena V.; Chertov, Aleksandr N.; Korotaev, Valery V.

    2014-09-01

    At the moment color sorting method is one of promising methods of mineral raw materials enrichment. This method is based on registration of color differences between images of analyzed objects. As is generally known the problem with delimitation of close color tints when sorting low-contrast minerals is one of the main disadvantages of color sorting method. It is can be related with wrong choice of a color model and incomplete image processing in machine vision system for realizing color sorting algorithm. Another problem is a necessity of image processing features reconfiguration when changing the type of analyzed minerals. This is due to the fact that optical properties of mineral samples vary from one mineral deposit to another. Therefore searching for values of image processing features is non-trivial task. And this task doesn't always have an acceptable solution. In addition there are no uniform guidelines for determining criteria of mineral samples separation. It is assumed that the process of image processing features reconfiguration had to be made by machine learning. But in practice it's carried out by adjusting the operating parameters which are satisfactory for one specific enrichment task. This approach usually leads to the fact that machine vision system unable to estimate rapidly the concentration rate of analyzed mineral ore by using color sorting method. This paper presents the results of research aimed at addressing mentioned shortcomings in image processing organization for machine vision systems which are used to color sorting of mineral samples. The principles of color analysis for low-contrast minerals by using machine vision systems are also studied. In addition, a special processing algorithm for color images of mineral samples is developed. Mentioned algorithm allows you to determine automatically the criteria of mineral samples separation based on an analysis of representative mineral samples. Experimental studies of the proposed algorithm

  18. Online tomato sorting based on shape, maturity, size, and surface defects using machine vision

    OpenAIRE

    ARJENAKI, Omid Omidi; MOGHADDAM, Parviz Ahmadi; MOTLAGH, Asad Moddares

    2013-01-01

    Online sorting of tomatoes according to their features is an important postharvest procedure. The purpose of this research was to develop an efficient machine vision-based experimental sorting system for tomatoes. Relevant sorting parameters included shape (oblong and circular), size (small and large), maturity (color), and defects. The variables defining shape, maturity, and size of the tomatoes were eccentricity, average of color components, and 2-D pixel area, respectively. Tomato defects ...

  19. Using an FPGA-Based Processing Platform in an Industrial Machine Vision System

    OpenAIRE

    King, William E

    1998-01-01

    This thesis describes the development of a commercial machine vision system as a case study for utilizing the Modular Reprogrammable Real-time Processing Hardware (MORRPH) board. The commercial system described in this thesis is based on a prototype system that was developed as a test-bed for developing the necessary concepts and algorithms. The prototype system utilized color linescan cameras, custom framegrabbers, and standard PCs to color-sort red oak parts (staves). When a furniture ma...

  20. Real-time machine vision FPGA implementation for microfluidic monitoring on Lab-on-Chips.

    Science.gov (United States)

    Sotiropoulou, Calliope-Louisa; Voudouris, Liberis; Gentsos, Christos; Demiris, Athanasios M; Vassiliadis, Nikolaos; Nikolaidis, Spyridon

    2014-04-01

    A machine vision implementation on a field-programmable gate array (FPGA) device for real-time microfluidic monitoring on Lab-On-Chips is presented in this paper. The machine vision system is designed to follow continuous or plug flows, for which the menisci of the fluids are always visible. The system discriminates between the front or "head" of the flow and the back or "tail" and is able to follow flows with a maximum speed of 20 mm/sec in circular channels of a diameter of 200 μm (corresponding to approx. 60 μl/sec ). It is designed to be part of a complete Point-of-Care system, which will be portable and operate in non-ideal laboratory conditions. Thus, it is able to cope with noise due to lighting conditions and small LoC displacements during the experiment execution. The machine vision system can be used for a variety of LoC devices, without the need for fiducial markers (such as redundancy patterns) for its operation. The underlying application requirements called for a complete hardware implementation. The architecture uses a variety of techniques to improve performance and minimize memory access requirements. The system input is 8 bit grayscale uncompressed video of up to 1 Mpixel resolution. The system uses an operating frequency of 170 Mhz and achieves a computational time of 13.97 ms (worst case), which leads to a throughput of 71.6 fps for 1 Mpixel video resolution.

  1. 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.

  2. Machine Vision System Design Method%机器视觉系统的设计方法

    Institute of Scientific and Technical Information of China (English)

    王运哲; 白雁兵; 张博

    2011-01-01

    文章主要介绍了机器视觉系统的概念和发展历程,介绍了机器视觉的组成和基本原理,从工业摄像机、镜头、光源、图像采集卡几方面详细阐述了机器视觉系统的设计要点、分类、选型。%The article introduces the conception and the developmental process of machine vision system, the component and fundamental theory of machine vision, expatiates on main points of designing machine vision system, classifying, choosing type, enumerates the most of manufacturers in the field of machine vision system in china.

  3. Design of Experimentation, Artificial Neural Network Simulation and Optimization for Integrated Bamboo Processing Machine

    OpenAIRE

    P. G. Mehar; Dr.A.V.Vanalkar

    2015-01-01

    In this research work experimentation on integrated bamboo processing machine for splitting and slicing of bamboo has been carried out. This paper presents the experimental investigation of some parameters of integrated bamboo processing machine. In this research paper simulation of experimental data using artificial neural network is carried out. An attempt of minimum-maximum principle has been made to optimize by range bound process for maximizing production rate of integrated b...

  4. New urea-absorbing polymers for artificial kidney machines

    Science.gov (United States)

    Mueller, W. A.; Hsu, G. C.; Marsh, H. E., Jr.

    1975-01-01

    Etherified polymer is made from modified cellulose derivative which is reacted with periodate. It will absorb 2 grams of urea per 100 grams of polymer. Indications are that polymers could be used to help remove uremic wastes in artificial kidneys, or they could be administered orally as therapy for uremia.

  5. Applying Artificial Neural Network to Predict Semiconductor Machine Outliers

    Directory of Open Access Journals (Sweden)

    Keng-Chieh Yang

    2013-01-01

    Full Text Available Advanced semiconductor processes are produced by very sophisticated and complex machines. The demand of higher precision for the monitoring system is becoming more vital when the devices are shrunk into smaller sizes. The high quality and high solution checking mechanism must rely on the advanced information systems, such as fault detection and classification (FDC. FDC can timely detect the deviations of the machine parameters when the parameters deviate from the original value and exceed the range of the specification. This study adopts backpropagation neural network model and gray relational analysis as tools to analyze the data. This study uses FDC data to detect the semiconductor machine outliers. Data collected for network training are in three different intervals: 6-month period, 3-month period, and one-month period. The results demonstrate that 3-month period has the best result. However, 6-month period has the worst result. The findings indicate that machine deteriorates quickly after continuous use for 6 months. The equipment engineers and managers can take care of this phenomenon and make the production yield better.

  6. Extreme Learning Machine and Moving Least Square Regression Based Solar Panel Vision Inspection

    Directory of Open Access Journals (Sweden)

    Heng Liu

    2017-01-01

    Full Text Available In recent years, learning based machine intelligence has aroused a lot of attention across science and engineering. Particularly in the field of automatic industry inspection, the machine learning based vision inspection plays a more and more important role in defect identification and feature extraction. Through learning from image samples, many features of industry objects, such as shapes, positions, and orientations angles, can be obtained and then can be well utilized to determine whether there is defect or not. However, the robustness and the quickness are not easily achieved in such inspection way. In this work, for solar panel vision inspection, we present an extreme learning machine (ELM and moving least square regression based approach to identify solder joint defect and detect the panel position. Firstly, histogram peaks distribution (HPD and fractional calculus are applied for image preprocessing. Then an ELM-based defective solder joints identification is discussed in detail. Finally, moving least square regression (MLSR algorithm is introduced for solar panel position determination. Experimental results and comparisons show that the proposed ELM and MLSR based inspection method is efficient not only in detection accuracy but also in processing speed.

  7. A Review of Machine-Vision-Based Analysis of Wireless Capsule Endoscopy Video

    Directory of Open Access Journals (Sweden)

    Yingju Chen

    2012-01-01

    Full Text Available Wireless capsule endoscopy (WCE enables a physician to diagnose a patient's digestive system without surgical procedures. However, it takes 1-2 hours for a gastroenterologist to examine the video. To speed up the review process, a number of analysis techniques based on machine vision have been proposed by computer science researchers. In order to train a machine to understand the semantics of an image, the image contents need to be translated into numerical form first. The numerical form of the image is known as image abstraction. The process of selecting relevant image features is often determined by the modality of medical images and the nature of the diagnoses. For example, there are radiographic projection-based images (e.g., X-rays and PET scans, tomography-based images (e.g., MRT and CT scans, and photography-based images (e.g., endoscopy, dermatology, and microscopic histology. Each modality imposes unique image-dependent restrictions for automatic and medically meaningful image abstraction processes. In this paper, we review the current development of machine-vision-based analysis of WCE video, focusing on the research that identifies specific gastrointestinal (GI pathology and methods of shot boundary detection.

  8. Growing adaptive machines combining development and learning in artificial neural networks

    CERN Document Server

    Bredeche, Nicolas; Doursat, René

    2014-01-01

    The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

  9. Computer Vision and Machine Learning for Autonomous Characterization of AM Powder Feedstocks

    Science.gov (United States)

    DeCost, Brian L.; Jain, Harshvardhan; Rollett, Anthony D.; Holm, Elizabeth A.

    2017-03-01

    By applying computer vision and machine learning methods, we develop a system to characterize powder feedstock materials for metal additive manufacturing (AM). Feature detection and description algorithms are applied to create a microstructural scale image representation that can be used to cluster, compare, and analyze powder micrographs. When applied to eight commercial feedstock powders, the system classifies powder images into the correct material systems with greater than 95% accuracy. The system also identifies both representative and atypical powder images. These results suggest the possibility of measuring variations in powders as a function of processing history, relating microstructural features of powders to properties relevant to their performance in AM processes, and defining objective material standards based on visual images. A significant advantage of the computer vision approach is that it is autonomous, objective, and repeatable.

  10. Computer Vision and Machine Learning for Autonomous Characterization of AM Powder Feedstocks

    Science.gov (United States)

    DeCost, Brian L.; Jain, Harshvardhan; Rollett, Anthony D.; Holm, Elizabeth A.

    2016-12-01

    By applying computer vision and machine learning methods, we develop a system to characterize powder feedstock materials for metal additive manufacturing (AM). Feature detection and description algorithms are applied to create a microstructural scale image representation that can be used to cluster, compare, and analyze powder micrographs. When applied to eight commercial feedstock powders, the system classifies powder images into the correct material systems with greater than 95% accuracy. The system also identifies both representative and atypical powder images. These results suggest the possibility of measuring variations in powders as a function of processing history, relating microstructural features of powders to properties relevant to their performance in AM processes, and defining objective material standards based on visual images. A significant advantage of the computer vision approach is that it is autonomous, objective, and repeatable.

  11. Study on the Fruit Grading Recognition System Based on Machine Vision

    Directory of Open Access Journals (Sweden)

    Huan Ma

    2015-07-01

    Full Text Available The study proposed that the current development of fruit industry requires the fast and efficient methods to test the varieties of fruits, which can combine the image processing and computer machine vision technology together to be applied in the field of fruit varieties detection, so as to be consistent with this new trend. At present, the determination of these traits were mainly depended on visual grading and manual measurement, which existed the problems such as: slow speed, low accuracy and poor objectivity and so on.

  12. Potential application of machine vision technology to saffron (Crocus sativus L.) quality characterization.

    Science.gov (United States)

    Kiani, Sajad; Minaei, Saeid

    2016-12-01

    Saffron quality characterization is an important issue in the food industry and of interest to the consumers. This paper proposes an expert system based on the application of machine vision technology for characterization of saffron and shows how it can be employed in practical usage. There is a correlation between saffron color and its geographic location of production and some chemical attributes which could be properly used for characterization of saffron quality and freshness. This may be accomplished by employing image processing techniques coupled with multivariate data analysis for quantification of saffron properties. Expert algorithms can be made available for prediction of saffron characteristics such as color as well as for product classification.

  13. On-line welding quality inspection system for steel pipe based on machine vision

    Science.gov (United States)

    Yang, Yang

    2017-05-01

    In recent years, high frequency welding has been widely used in production because of its advantages of simplicity, reliability and high quality. In the production process, how to effectively control the weld penetration welding, ensure full penetration, weld uniform, so as to ensure the welding quality is to solve the problem of the present stage, it is an important research field in the field of welding technology. In this paper, based on the study of some methods of welding inspection, a set of on-line welding quality inspection system based on machine vision is designed.

  14. Tensor Voting A Perceptual Organization Approach to Computer Vision and Machine Learning

    CERN Document Server

    Mordohai, Philippos

    2006-01-01

    This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California. It is not written as a historical recount of the work, since the sequence of the presentation is not in chronological order. It aims at presenting an approach to a wide range of problems in computer vision and machine learning that is data-driven, local and requires a minimal number of assumptions. The tensor voting framework combines these properties and provides a unified perceptual organiza

  15. Development a Vision Based Seam Tracking System for None Destructive Testing Machines

    Directory of Open Access Journals (Sweden)

    Nasser moradi

    2013-04-01

    Full Text Available The automatic weld seam tracking is an important challenge in None Destructive Testing (NDT systems for welded pipe inspection. In this Study, a machine vision based seam tracker, is developed and implemented, instead of old electro-mechanical system. A novel algorithm based on the weld image centered is presented, to reduce Environment conditions and improve the seam tracking accuracy. The weld seam images are taken by a camera arranged ahead of the machine and the centered is extracted as a parameter to detect the weld position, and offset between this point and central axis is computed and used as control parameter of servomotors. Adaptive multi step segmentation t technique is employed to increase the probable of real edge of the welds and improve the line fitting accuracy. This new approach offers some important technical advantages over the existing solutions to weld seam detection: Its based on natural light and does not need any auxiliary light. The adaptive threshold segmentation technique applied, decrease Environmental lighting condition. Its accurate and stable in real time NDT testing machines. After a series of experiments in real industrial environment, it is demonstrated that accuracy of this method can improve the quality of NDT machines. The average tracking error is 1.5 pixels approximately 0.25mm..

  16. Support vector machines applications

    CERN Document Server

    Guo, Guodong

    2014-01-01

    Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

  17. Spherical rotary piston machine as an artificial heart.

    Science.gov (United States)

    Wipf, S L

    1991-01-01

    A positive displacement pump with six rotary pistons was proposed as an artificial heart. The pump's design was characterized by high symmetry and compactness. Thus, a spherical volume of 4 1/4 inch diameter sufficed for a pump delivering 10 L/min at 120 pulses/min with the pistons turning at 30 rpm. The pistons and four connecting gears were the only moving parts. The pump functions in two separate halves as left and right ventricles, with two of the six pistons each having inlet and outlet passages, and one of them replacing mitral and pulmonary valves with the other, tricuspid and aortic valves. The function of the intraventricular septum was provided by the other four pistons whose interiors also accommodated driving motors each capable of 0.4 Nm torque for a combined power of 5 watts. There were no stagnant regions in the pumping volume, and at all internal surfaces in contact with blood, there was periodic shear stress not exceeding approximately 300 Pa.

  18. [Development of a new position-recognition system for robotic radiosurgery systems using machine vision].

    Science.gov (United States)

    Mohri, Issai; Umezu, Yoshiyuki; Fukunaga, Junnichi; Tane, Hiroyuki; Nagata, Hironori; Hirashima, Hideaki; Nakamura, Katsumasa; Hirata, Hideki

    2014-08-01

    CyberKnife(®) provides continuous guidance through radiography, allowing instantaneous X-ray images to be obtained; it is also equipped with 6D adjustment for patient setup. Its disadvantage is that registration is carried out just before irradiation, making it impossible to perform stereo-radiography during irradiation. In addition, patient movement cannot be detected during irradiation. In this study, we describe a new registration system that we term "Machine Vision," which subjects the patient to no additional radiation exposure for registration purposes, can be set up promptly, and allows real-time registration during irradiation. Our technique offers distinct advantages over CyberKnife by enabling a safer and more precise mode of treatment. "Machine Vision," which we have designed and fabricated, is an automatic registration system that employs three charge coupled device cameras oriented in different directions that allow us to obtain a characteristic depiction of the shape of both sides of the fetal fissure and external ears in a human head phantom. We examined the degree of precision of this registration system and concluded it to be suitable as an alternative method of registration without radiation exposure when displacement is less than 1.0 mm in radiotherapy. It has potential for application to CyberKnife in clinical treatment.

  19. Vision-Based Perception and Classification of Mosquitoes Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Masataka Fuchida

    2017-01-01

    Full Text Available The need for a novel automated mosquito perception and classification method is becoming increasingly essential in recent years, with steeply increasing number of mosquito-borne diseases and associated casualties. There exist remote sensing and GIS-based methods for mapping potential mosquito inhabitants and locations that are prone to mosquito-borne diseases, but these methods generally do not account for species-wise identification of mosquitoes in closed-perimeter regions. Traditional methods for mosquito classification involve highly manual processes requiring tedious sample collection and supervised laboratory analysis. In this research work, we present the design and experimental validation of an automated vision-based mosquito classification module that can deploy in closed-perimeter mosquito inhabitants. The module is capable of identifying mosquitoes from other bugs such as bees and flies by extracting the morphological features, followed by support vector machine-based classification. In addition, this paper presents the results of three variants of support vector machine classifier in the context of mosquito classification problem. This vision-based approach to the mosquito classification problem presents an efficient alternative to the conventional methods for mosquito surveillance, mapping and sample image collection. Experimental results involving classification between mosquitoes and a predefined set of other bugs using multiple classification strategies demonstrate the efficacy and validity of the proposed approach with a maximum recall of 98%.

  20. Nondestructive and rapid detection of potato black heart based on machine vision technology

    Science.gov (United States)

    Tian, Fang; Peng, Yankun; Wei, Wensong

    2016-05-01

    Potatoes are one of the major food crops in the world. Potato black heart is a kind of defect that the surface is intact while the tissues in skin become black. This kind of potato has lost the edibleness, but it's difficult to be detected with conventional methods. A nondestructive detection system based on the machine vision technology was proposed in this study to distinguish the normal and black heart of potatoes according to the different transmittance of them. The detection system was equipped with a monochrome CCD camera, LED light sources for transmitted illumination and a computer. Firstly, the transmission images of normal and black heart potatoes were taken by the detection system. Then the images were processed by algorithm written with VC++. As the transmitted light intensity was influenced by the radial dimension of the potato samples, the relationship between the grayscale value and the potato radial dimension was acquired by analyzing the grayscale value changing rule of the transmission image. Then proper judging condition was confirmed to distinguish the normal and black heart of potatoes after image preprocessing. The results showed that the nondestructive system built coupled with the processing methods was accessible for the detection of potato black heart at a considerable accuracy rate. The transmission detection technique based on machine vision is nondestructive and feasible to realize the detection of potato black heart.

  1. Machine Vision Analysis of Characteristics and Image Information Base Construction for Hybrid Rice Seed

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Incompletely closed glumes, germination on panicle and disease ara thrae important factors causing poor seed quality of hybrid rice. To determine how many and which categories should be classified to meet the demand for seed in rice production, the effects of various degrees of incompletely closed glumes, germination on panicle and disease on germination percentage at the harvest and after storage for six months were studied by standard germination percentage test. Six categories of seeds with germ (germinated seeds), severe disease, incompletely closed glumes, spot disease, fine fissure and normal seeds were inspected and then treated separately. Images of the five hybrid rice seed (Jinyou 402, Shanyou 10, Zhongyou 27, Jiayou 99 and Ⅱ you 3207) were acquired with a self-developed machine vision system. Each image could be processed to get the feature values of seed region such as length, width, ratio of length to width, araa, solidity and hue. Then all the images of normal seeds were calculated to draw the feature value ranges of each hybrid rice variety. Finally, an image information base that stores typical images and related feature values of each variety was established. This image information base can help us to identify the classification limit of characteristics, and provide the reference of the threshold selection. The management of large numbers of pictures and the addition of new varieties have been supported. The research laid a foundation for extracting image features of hybrid rice seed, which is a key approach to futura quality inspection with machine vision.

  2. Technique for Calibration of Chassis components based on encoding marks and machine Vision metrology

    Institute of Scientific and Technical Information of China (English)

    SONG Li-mei; ZHANG Chun-bo; WEI Yi-ying; CHEN Hua-wei

    2011-01-01

    @@ A novel technique for calibrating crucial parameters of chassis components is proposed, which utilizes the machine vision metrology to measure 3D coordinates of the center of a component's hole for assembling in the 3D world coordinate system.In the measurement, encoding marks with special patterns will be assembled on the chassis component associated with cross drone and staff gauge located near the chassis.The geometry and coordinates of the cross drone consist of two planes orthogonal to each other and the staff gauge is in 3D space with high precision.A few images are taken by a highresolution camera in different orientations and perspectives.The 3D coordinates of 5 key points on the encoding marks will be calculated by the machine vision technique and those of the center of the holes to be calibrated will be calculated by the deduced algorithm in this paper.Experimental results show that the algorithm and the technique can satisfy the precision requirement when the components are assembled, and the average measurement precision provided by the algorithm is 0.0174 mm.

  3. Infrared machine vision system for the automatic detection of olive fruit quality.

    Science.gov (United States)

    Guzmán, Elena; Baeten, Vincent; Pierna, Juan Antonio Fernández; García-Mesa, José A

    2013-11-15

    External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.

  4. Implementation of a Vision System for a Landmine Detecting Robot Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Roger Achkar

    2012-09-01

    Full Text Available Landmines, specifically anti-tank mines, cluster bombs, and unexploded ordnance form a serious problem in many countries. Several landmine sweeping techniques are used for minesweeping. This paper presents the design and the implementation of the vision system of an autonomous robot for landmines localization. The proposed work develops state-of-the-art techniques in digital image processing for pre-processing captured images of the contaminated area. After enhancement, Artificial Neural Network (ANN is used in order to identify, recognize and classify the landmines’ make and model. The Back-Propagation algorithm is used for training the network. The proposed work proved to be able to identify and classify different types of landmines under various conditions (rotated landmine, partially covered landmine with a success rate of up to 90%.

  5. Implementation of a Vision System for a Landmine Detecting Robot Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Roger Achkar

    2012-10-01

    Full Text Available Landmines, specifically anti-tank mines, cluster bombs, and unexploded ordnance form a serious problemin many countries. Several landmine sweeping techniques are used for minesweeping. This paper presentsthe design and the implementation of the vision system of an autonomous robot for landmines localization.The proposed work develops state-of-the-art techniques in digital image processing for pre-processingcaptured images of the contaminated area. After enhancement, Artificial Neural Network (ANN is used inorder to identify, recognize and classify the landmines’ make and model. The Back-Propagation algorithmis used for training the network. The proposed work proved to be able to identify and classify different typesof landmines under various conditions (rotated landmine, partially covered landmine with a success rateof up to 90%.

  6. Artificial Vision in 3D Perspective. For Object Detection On Planes, Using Points Clouds.

    Directory of Open Access Journals (Sweden)

    Catalina Alejandra Vázquez Rodriguez

    2014-02-01

    Full Text Available In this paper, we talk about an algorithm of artificial vision for the robot Golem - II + with which to analyze the environment the robot, for the detection of planes and objects in the scene through point clouds, which were captured with kinect device, possible objects and quantity, distance and other characteristics. Subsequently the "clusters" are grouped to identify whether they are located on the same surface, in order to calculate the distance and the slope of the planes relative to the robot, and finally each object separately analyzed to see if it is possible to take them, if they are empty surfaces, may leave objects on them, long as feasible considering a distance, ignoring false positives as the walls and floor, which for these purposes are not of interest since it is not possible to place objects on the walls and floor are out of range of the robot's arms.

  7. Application of Artificial Vision in flow redirection during filling of Liquid Composite Molding processes

    Science.gov (United States)

    Montés, N.; Sanchez, F.; García, J. A.; Falcó, A.; Tornero, J.; Chinesta, F.

    2007-04-01

    The control techniques applied in Liquid Composite Molding processes have been extensively worked out by many different research groups abroad. In this work, the original use of artificial vision technology in order to redirect the flow path during mold filling appears as a major objective of online control strategy. In this study, a process performance index developed in a previous work is used to define the mold gate opening sequence. The Vacuum Assisted Resin Transfer Molding (VARTM) and Vacuum Assisted Resin Infusion (VARI) have been selected as the main processes of study. The expert system will make use of numerical simulation in order to obtain a previous physical understanding of the flow behaviour in different manufacturing conditions. Some examples of the installation are presented and discussed.

  8. 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.

  9. 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.

  10. Computer vision-based method for classification of wheat grains using artificial neural network.

    Science.gov (United States)

    Sabanci, Kadir; Kayabasi, Ahmet; Toktas, Abdurrahim

    2017-06-01

    A simplified computer vision-based application using artificial neural network (ANN) depending on multilayer perceptron (MLP) for accurately classifying wheat grains into bread or durum is presented. The images of 100 bread and 100 durum wheat grains are taken via a high-resolution camera and subjected to pre-processing. The main visual features of four dimensions, three colors and five textures are acquired using image-processing techniques (IPTs). A total of 21 visual features are reproduced from the 12 main features to diversify the input population for training and testing the ANN model. The data sets of visual features are considered as input parameters of the ANN model. The ANN with four different input data subsets is modelled to classify the wheat grains into bread or durum. The ANN model is trained with 180 grains and its accuracy tested with 20 grains from a total of 200 wheat grains. Seven input parameters that are most effective on the classifying results are determined using the correlation-based CfsSubsetEval algorithm to simplify the ANN model. The results of the ANN model are compared in terms of accuracy rate. The best result is achieved with a mean absolute error (MAE) of 9.8 × 10(-6) by the simplified ANN model. This shows that the proposed classifier based on computer vision can be successfully exploited to automatically classify a variety of grains. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  11. New Trends in Computing Anticipatory Systems : Emergence of Artificial Conscious Intelligence with Machine Learning Natural Language

    Science.gov (United States)

    Dubois, Daniel M.

    2008-10-01

    This paper deals with the challenge to create an Artificial Intelligence System with an Artificial Consciousness. For that, an introduction to computing anticipatory systems is presented, with the definitions of strong and weak anticipation. The quasi-anticipatory systems of Robert Rosen are linked to open-loop controllers. Then, some properties of the natural brain are presented in relation to the triune brain theory of Paul D. MacLean, and the mind time of Benjamin Libet, with his veto of the free will. The theory of the hyperincursive discrete anticipatory systems is recalled in view to introduce the concept of hyperincursive free will, which gives a similar veto mechanism: free will as unpredictable hyperincursive anticipation The concepts of endo-anticipation and exo-anticipation are then defined. Finally, some ideas about artificial conscious intelligence with natural language are presented, in relation to the Turing Machine, Formal Language, Intelligent Agents and Mutli-Agent System.

  12. Fast and intuitive programming of adaptive laser cutting of lace enabled by machine vision

    Science.gov (United States)

    Vaamonde, Iago; Souto-López, Álvaro; García-Díaz, Antón

    2015-07-01

    A machine vision system has been developed, validated, and integrated in a commercial laser robot cell. It permits an offline graphical programming of laser cutting of lace. The user interface allows loading CAD designs and aligning them with images of lace pieces. Different thread widths are discriminated to generate proper cutting program templates. During online operation, the system aligns CAD models of pieces and lace images, pre-checks quality of lace cuts and adapts laser parameters to thread widths. For pieces detected with the required quality, the program template is adjusted by transforming the coordinates of every trajectory point. A low-cost lace feeding system was also developed for demonstration of full process automation.

  13. Image processing with genetic algorithm in a raisin sorting system based on machine vision

    Science.gov (United States)

    Abbasgholipour, Mahdi; Alasti, Behzad Mohammadi; Abbasgholipour, Vahdi; Derakhshan, Ali; Abbasgholipour, Mohammad; Rahmatfam, Sharmin; Rahmatfam, Sheyda; Habibifar, Rahim

    2012-04-01

    This study was undertaken to develop machine vision-based raisin detection technology. Supervised color image segmentation using a Permutation-coded Genetic Algorithm (GA) identifying regions in Hue-Saturation-Intensity (HSI) color space (GAHSI) for desired and undesired raisin detection was successfully implemented. Images were captured to explore the possibility of using GAHSI to locate desired raisin and undesired raisin regions in color space simultaneously. In this research, images were processed separately using three segmentation method, K-Means clustering in L*a*b* color space and GAHSI for single image, GA for single image in Red-Green-Blue (RGB) color space (GARGB). The GAHSI results provided evidence for the existence and separability of such regions. When compared with cluster analysis-based segmentation results, the GAHSI method showed no significant difference.

  14. Development of an automatic weld surface appearance inspection system using machine vision

    Institute of Scientific and Technical Information of China (English)

    Lin Sanbao; Fu Xibin; Fan Chenglei; Yang Chunli; Luo Lu

    2009-01-01

    In this paper, an automatic inspection system for weld surface appearance using machine vision has been developed to recognize weld surface defects such as porosities, cracks, etc. It can replace conventional manual visual inspection method, which is tedious, time-consuming, subjective, experience-depended, and sometimes biased. The system consists of a CCD camera, a self-designed annular light source, a sensor controller, a frame grabbing card, a computer and so on. After acquiring weld surface appearance images using CCD, the images are preprocessed using median filtering and a series of image enhancement algorithms. Then a dynamic threshold and morphology algorithms are applied to segment defect object. Finally, defect features information is obtained by eight neighborhoods boundary chain code algorithm. Experimental results show that the developed system is capable of inspecting most surface defects such as porosities, cracks with high reliability and accuracy.

  15. A real-time surface inspection system for precision steel balls based on machine vision

    Science.gov (United States)

    Chen, Yi-Ji; Tsai, Jhy-Cherng; Hsu, Ya-Chen

    2016-07-01

    Precision steel balls are one of the most fundament components for motion and power transmission parts and they are widely used in industrial machinery and the automotive industry. As precision balls are crucial for the quality of these products, there is an urgent need to develop a fast and robust system for inspecting defects of precision steel balls. In this paper, a real-time system for inspecting surface defects of precision steel balls is developed based on machine vision. The developed system integrates a dual-lighting system, an unfolding mechanism and inspection algorithms for real-time signal processing and defect detection. The developed system is tested under feeding speeds of 4 pcs s-1 with a detection rate of 99.94% and an error rate of 0.10%. The minimum detectable surface flaw area is 0.01 mm2, which meets the requirement for inspecting ISO grade 100 precision steel balls.

  16. Development of a machine vision system for a real-time precision sprayer

    Science.gov (United States)

    Bossu, Jérémie; Gée, Christelle; Truchetet, Frédéric

    2007-01-01

    In the context of precision agriculture, we have developed a machine vision system for a real time precision sprayer. From a monochrome CCD camera located in front of the tractor, the discrimination between crop and weeds is obtained with an image processing based on spatial information using a Gabor filter. This method allows to detect the periodic signals from the non periodic one and it enables to enhance the crop rows whereas weeds have patchy distribution. Thus, weed patches were clearly identified by a blob-coloring method. Finally, we use a pinhole model to transform the weed patch coordinates image in world coordinates in order to activate the right electro-pneumatic valve of the sprayer at the right moment.

  17. Using machine vision and data mining techniques to identify cell properties via microfluidic flow analysis

    Science.gov (United States)

    Horowitz, Geoffrey; Bowie, Samuel; Liu, Anna; Stone, Nicholas; Sulchek, Todd; Alexeev, Alexander

    2016-11-01

    In order to quickly identify the wide range of mechanistic properties that are seen in cell populations, a coupled machine vision and data mining analysis is developed to examine high speed videos of cells flowing through a microfluidic device. The microfluidic device contains a microchannel decorated with a periodical array of diagonal ridges. The ridges compress flowing cells that results in complex cell trajectory and induces cell cross-channel drift, both depend on the cell intrinsic mechanical properties that can be used to characterize specific cell lines. Thus, the cell trajectory analysis can yield a parameter set that can serve as a unique identifier of a cell's membership to a specific cell population. By using the correlations between the cell populations and measured cell trajectories in the ridged microchannel, mechanical properties of individual cells and their specific populations can be identified via only information captured using video analysis. Financial support provided by National Science Foundation (NSF) Grant No. CMMI 1538161.

  18. Deep learning-based artificial vision for grasp classification in myoelectric hands

    Science.gov (United States)

    Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

    2017-06-01

    Objective. Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. Approach. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at {{5}\\circ} intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. Main results. The classification accuracy in the offline tests reached 85 % for the seen and 75 % for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of 84 % in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb UltraTM prosthetic hand and a motion controlTM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to 88 % . In addition, we show that with training, subjects’ performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. Significance. The proposed design constitutes a substantial

  19. Machine vision method for online surface inspection of easy open can ends

    Science.gov (United States)

    Mariño, Perfecto; Pastoriza, Vicente; Santamaría, Miguel

    2006-10-01

    Easy open can end manufacturing process in the food canning sector currently makes use of a manual, non-destructive testing procedure to guarantee can end repair coating quality. This surface inspection is based on a visual inspection made by human inspectors. Due to the high production rate (100 to 500 ends per minute) only a small part of each lot is verified (statistical sampling), then an automatic, online, inspection system, based on machine vision, has been developed to improve this quality control. The inspection system uses a fuzzy model to make the acceptance/rejection decision for each can end from the information obtained by the vision sensor. In this work, the inspection method is presented. This surface inspection system checks the total production, classifies the ends in agreement with an expert human inspector, supplies interpretability to the operators in order to find out the failure causes and reduce mean time to repair during failures, and allows to modify the minimum can end repair coating quality.

  20. Algorithm for Modeling Wire Cut Electrical Discharge Machine Parameters using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    G.Sankara Narayanan

    2014-03-01

    Full Text Available Unconventional machining process finds lot of application in aerospace and precision industries. It is preferred over other conventional methods because of the advent of composite and high strength to weight ratio materials, complex parts and also because of its high accuracy and precision. Usually in unconventional machine tools, trial and error method is used to fix the values of process parameters which increase the production time and material wastage. A mathematical model functionally relating process parameters and operating parameters of a wire cut electric discharge machine (WEDM is developed incorporating Artificial neural network (ANN and the work piece material is SKD11 tool steel. This is accomplished by training a feed forward neural network with back propagation learning Levenberg-Marquardt algorithm. The required data used for training and testing the ANN are obtained by conducting trial runs in wire cut electric discharge machine in a small scale industry from South India. The programs for training and testing the neural network are developed, using matlab 7.0.1 package. In this work, we have considered the parameters such as thickness, time and wear as the input values and from that the values of the process parameters are related and a algorithm is arrived. Hence, the proposed algorithm reduces the time taken by trial runs to set the input process parameters of WEDM and thus reduces the production time along with reduction in material wastage. Thus the cost of machining processes is reduced and thereby increases the overall productivity.

  1. A machine vision system for micro-EDM based on linux

    Science.gov (United States)

    Guo, Rui; Zhao, Wansheng; Li, Gang; Li, Zhiyong; Zhang, Yong

    2006-11-01

    Due to the high precision and good surface quality that it can give, Electrical Discharge Machining (EDM) is potentially an important process for the fabrication of micro-tools and micro-components. However, a number of issues remain unsolved before micro-EDM becomes a reliable process with repeatable results. To deal with the difficulties in micro electrodes on-line fabrication and tool wear compensation, a micro-EDM machine vision system is developed with a Charge Coupled Device (CCD) camera, with an optical resolution of 1.61μm and an overall magnification of 113~729. Based on the Linux operating system, an image capturing program is developed with the V4L2 API, and an image processing program is exploited by using OpenCV. The contour of micro electrodes can be extracted by means of the Canny edge detector. Through the system calibration, the micro electrodes diameter can be measured on-line. Experiments have been carried out to prove its performance, and the reasons of measurement error are also analyzed.

  2. Research on automatic inspection system for defects on precise optical surface based on machine vision

    Institute of Scientific and Technical Information of China (English)

    WANG Xue; XIE Zhi-jiang

    2006-01-01

    In manufacture of precise optical products, it is important to inspect and classify the potential defects existing on the products' surfaces after precise machining in order to obtain high quality in both functionality and aesthetics. The existing methods for detecting and classifying defects all are low accuracy or efficiency or high cost in inspection process. In this paper, a new inspection system based on machine vision has been introduced, which uses automatic focusing and image mosaic technologies to rapidly acquire distinct surface image, and employs Case-Based Reasoning(CBR)method in defects classification. A modificatory fuzzy similarity algorithm in CBR has been adopted for more quick and robust need of pattern recognition in practice inspection. Experiments show that the system can inspect surface diameter of 500mm in half an hour with resolving power of 0.8μm diameter according to digs or 0.5μm transverse width according to scratches. The proposed inspection principles and methods not only have meet manufacturing requirements of precise optical products, but also have great potential applications in other fields of precise surface inspection.

  3. A Novel Approach to Automatic Road-Accident Detection using Machine Vision Techniques

    Directory of Open Access Journals (Sweden)

    Vaishnavi Ravindran

    2016-11-01

    Full Text Available In this paper, a novel approach for automatic road accident detection is proposed. The approach is based on detecting damaged vehicles from footage received from surveillance cameras installed in roads and highways which would indicate the occurrence of a road accident. Detection of damaged cars falls under the category of object detection in the field of machine vision and has not been achieved so far. In this paper, a new supervised learning method comprising of three different stages which are combined into a single framework in a serial manner which successfully detects damaged cars from static images is proposed. The three stages use five support vector machines trained with Histogram of gradients (HOG and Gray level co-occurrence matrix (GLCM features. Since damaged car detection has not been attempted, two datasets of damaged cars - Damaged Cars Dataset-1 (DCD-1 and Damaged Cars Dataset-2 (DCD-2 – was compiled for public release. Experiments were conducted on DCD-1 and DCD-2 which differ based on the distance at which the image is captured and the quality of the images. The accuracy of the system is 81.83% for DCD-1 captured at approximately 2 meters with good quality and 64.37% for DCD-2 captured at approximately 20 meters with poor quality.

  4. Quality indexing by machine vision during fermentation in black tea manufacturing

    Science.gov (United States)

    Borah, S.; Bhuyan, M.

    2003-04-01

    Although the organoleptic method of tea testing has been traditionally used for quality monitoring, an alternative way by machine vision may be advantageous. Although, the three main quality descriptors estimate the overall quality of made-tea, viz., strength, briskness and brightness of tea liquor, the exact colour detection in fermenting process leads to a good quality-monitoring tool. The use of digital image processing technique for this purpose is reported to play an effective role towards the production of good quality tea though it is not the only quality determining parameter. In this paper, it has been tried to compare the contribution of the chemical constituents towards the final product with the visual appearance in the processing stage by imaging. The use of machine intelligence supports the process somewhat invariantly in comparison to the human decision and colorimetric approach. The captured images are processed for colour matching with a standard image database using HSI colour model. The application of colour dissimilarity and perceptron learning for the standard images and the test images is ensured. Moreover, the performance of the system is being tried to correlate with the decision made by the organoleptic panel assigned for the tea testing and chemical test results on the final product. However, it should be noted that the optimized result could be achieved only when the other quality parameters such as withering, flavour (aroma) detection, drying status etc. are properly maintained.

  5. Multi-functional dielectric elastomer artificial muscles for soft and smart machines

    Science.gov (United States)

    Anderson, Iain A.; Gisby, Todd A.; McKay, Thomas G.; O'Brien, Benjamin M.; Calius, Emilio P.

    2012-08-01

    Dielectric elastomer (DE) actuators are popularly referred to as artificial muscles because their impressive actuation strain and speed, low density, compliant nature, and silent operation capture many of the desirable physical properties of muscle. Unlike conventional robots and machines, whose mechanisms and drive systems rapidly become very complex as the number of degrees of freedom increases, groups of DE artificial muscles have the potential to generate rich motions combining many translational and rotational degrees of freedom. These artificial muscle systems can mimic the agonist-antagonist approach found in nature, so that active expansion of one artificial muscle is taken up by passive contraction in the other. They can also vary their stiffness. In addition, they have the ability to produce electricity from movement. But departing from the high stiffness paradigm of electromagnetic motors and gearboxes leads to new control challenges, and for soft machines to be truly dexterous like their biological analogues, they need precise control. Humans control their limbs using sensory feedback from strain sensitive cells embedded in muscle. In DE actuators, deformation is inextricably linked to changes in electrical parameters that include capacitance and resistance, so the state of strain can be inferred by sensing these changes, enabling the closed loop control that is critical for a soft machine. But the increased information processing required for a soft machine can impose a substantial burden on a central controller. The natural solution is to distribute control within the mechanism itself. The octopus arm is an example of a soft actuator with a virtually infinite number of degrees of freedom (DOF). The arm utilizes neural ganglia to process sensory data at the local "arm" level and perform complex tasks. Recent advances in soft electronics such as the piezoresistive dielectric elastomer switch (DES) have the potential to be fully integrated with actuators

  6. Artificial immune algorithm implementation for optimized multi-axis sculptured surface CNC machining

    Science.gov (United States)

    Fountas, N. A.; Kechagias, J. D.; Vaxevanidis, N. M.

    2016-11-01

    This paper presents the results obtained by the implementation of an artificial immune algorithm to optimize standard multi-axis tool-paths applied to machine free-form surfaces. The investigation for its applicability was based on a full factorial experimental design addressing the two additional axes for tool inclination as independent variables whilst a multi-objective response was formulated by taking into consideration surface deviation and tool path time; objectives assessed directly from computer-aided manufacturing environment A standard sculptured part was developed by scratch considering its benchmark specifications and a cutting-edge surface machining tool-path was applied to study the effects of the pattern formulated when dynamically inclining a toroidal end-mill and guiding it towards the feed direction under fixed lead and tilt inclination angles. The results obtained form the series of the experiments were used for the fitness function creation the algorithm was about to sequentially evaluate. It was found that the artificial immune algorithm employed has the ability of attaining optimal values for inclination angles facilitating thus the complexity of such manufacturing process and ensuring full potentials in multi-axis machining modelling operations for producing enhanced CNC manufacturing programs. Results suggested that the proposed algorithm implementation may reduce the mean experimental objective value to 51.5%

  7. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  8. Fault diagnosis based on support vector machines with parameter optimisation by artificial immunisation algorithm

    Science.gov (United States)

    Yuan, Shengfa; Chu, Fulei

    2007-04-01

    Support vector machines (SVM) is a new general machine-learning tool based on the structural risk minimisation principle that exhibits good generalisation when fault samples are few, it is especially fit for classification, forecasting and estimation in small-sample cases such as fault diagnosis, but some parameters in SVM are selected by man's experience, this has hampered its efficiency in practical application. Artificial immunisation algorithm (AIA) is used to optimise the parameters in SVM in this paper. The AIA is a new optimisation method based on the biologic immune principle of human being and other living beings. It can effectively avoid the premature convergence and guarantees the variety of solution. With the parameters optimised by AIA, the total capability of the SVM classifier is improved. The fault diagnosis of turbo pump rotor shows that the SVM optimised by AIA can give higher recognition accuracy than the normal SVM.

  9. Application of artificial neural network with extreme learning machine for economic growth estimation

    Science.gov (United States)

    Milačić, Ljubiša; Jović, Srđan; Vujović, Tanja; Miljković, Jovica

    2017-01-01

    The purpose of this research is to develop and apply the artificial neural network (ANN) with extreme learning machine (ELM) to forecast gross domestic product (GDP) growth rate. The economic growth forecasting was analyzed based on agriculture, manufacturing, industry and services value added in GDP. The results were compared with ANN with back propagation (BP) learning approach since BP could be considered as conventional learning methodology. The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Based on results, it was shown that ANN with ELM learning methodology can be applied effectively in applications of GDP forecasting.

  10. Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

    Science.gov (United States)

    Islam, Kh Tohidul; Raj, Ram Gopal

    2017-01-01

    Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

  11. Biological model of vision for an artificial system that learns to perceive its environment

    Energy Technology Data Exchange (ETDEWEB)

    Blackburn, M.R.; Nguyen, H.G.

    1989-06-01

    The objective is to design an artificial vision system for use in robotics applications. Because the desired performance is equivalent to that achieved by nature, the authors anticipate that the objective will be accomplished most efficiently through modeling aspects of the neuroanatomy and neurophysiology of the biological visual system. Information enters the biological visual system through the retina and is passed to the lateral geniculate and optic tectum. The lateral geniculate nucleus (LGN) also receives information from the cerebral cortex and the result of these two inflows is returned to the cortex. The optic tectum likewise receives the retinal information in a context of other converging signals and organizes motor responses. A computer algorithm is described which implements models of the biological visual mechanisms of the retina, thalamic lateral geniculate and perigeniculate nuclei, and primary visual cortex. Motion and pattern analyses are performed in parallel and interact in the cortex to construct perceptions. We hypothesize that motion reflexes serve as unconditioned pathways for the learning and recall of pattern information. The algorithm demonstrates this conditioning through a learning function approximating heterosynaptic facilitation.

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

    Science.gov (United States)

    1972-01-01

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

  13. 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

  14. Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation.

    Science.gov (United States)

    Dominguez Veiga, Jose Juan; O'Reilly, Martin; Whelan, Darragh; Caulfield, Brian; Ward, Tomas E

    2017-08-04

    Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the

  15. A distortion-correction method for workshop machine vision measurement system

    Science.gov (United States)

    Chen, Ruwen; Huang, Ren; Zhang, Zhisheng; Shi, Jinfei; Chen, Zixin

    2008-12-01

    The application of machine vision measurement system is developing rapidly in industry for its non-contact, high speed, and automation characteristics. However, there are nonlinear distortions in the images which are vital to measuring precision, for the object dimensions are determined by the image properties. People are interested in this problem and put forward some physical model based correction methods which are widely applied in engineering. However, these methods are difficult to be realized in workshop for the images are non-repetitive interfered by the coupled dynamic factors, which means the real imaging is a stochastic process. A new nonlinear distortion correction method based on a VNAR model (Volterra series based nonlinear auto-regressive time series model) is proposed to describe the distorted image edge series. The model parameter vectors are achieved by the laws of data. The distortion-free edges are obtained after model filtering and the image dimensions are transformed to measuring dimensions. Experimental results show that the method is reliable and can be applied to engineering.

  16. 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.

  17. X-ray-based machine vision system for distal locking of intramedullary nails.

    Science.gov (United States)

    Juneho, F; Bouazza-Marouf, K; Kerr, D; Taylor, A J; Taylor, G J S

    2007-05-01

    In surgical procedures for femoral shaft fracture treatment, current techniques for locking the distal end of intramedullary nails, using two screws, rely heavily on the use of two-dimensional X-ray images to guide three-dimensional bone drilling processes. Therefore, a large number of X-ray images are required, as the surgeon uses his/her skills and experience to locate the distal hole axes on the intramedullary nail. The long-term effects of X-ray radiation and their relation to different types of cancer still remain uncertain. Therefore, there is a need to develop a surgical technique that can limit the use of X-rays during the distal locking procedure. A robotic-assisted orthopaedic surgery system has been developed at Loughborough University to assist orthopaedic surgeons by reducing the irradiation involved in such operations. The system simplifies the current approach as it uses only two near-orthogonal X-ray images to determine the drilling trajectory of the distal locking holes, thereby considerably reducing irradiation to both the surgeon and patient. Furthermore, the system uses robust machine vision features to reduce the surgeon's interaction with the system, thus reducing the overall operating time. Laboratory test results have shown that the proposed system is very robust in the presence of variable noise and contrast in the X-ray images.

  18. Colour Model for Outdoor Machine Vision for Tropical Regions and its Comparison with the CIE Model

    Energy Technology Data Exchange (ETDEWEB)

    Sahragard, Nasrolah; Ramli, Abdul Rahman B [Institute of Advanced Technology, Universiti Putra Malaysia 43400 Serdang, Selangor (Malaysia); Marhaban, Mohammad Hamiruce [Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia 43400 Serdang, Selangor (Malaysia); Mansor, Shattri B, E-mail: sahragard@yahoo.com [Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia 43400 Serdang, Selangor (Malaysia)

    2011-02-15

    Accurate modeling of daylight and surface reflectance are very useful for most outdoor machine vision applications specifically those which are based on color recognition. Existing daylight CIE model has drawbacks that limit its ability to predict the color of incident light. These limitations include lack of considering ambient light, effects of light reflected off the ground, and context specific information. Previously developed color model is only tested for a few geographical places in North America and its accountability is under question for other places in the world. Besides, existing surface reflectance models are not easily applied to outdoor images. A reflectance model with combined diffuse and specular reflection in normalized HSV color space could be used to predict color. In this paper, a new daylight color model showing the color of daylight for a broad range of sky conditions is developed which will suit weather conditions of tropical places such as Malaysia. A comparison of this daylight color model and daylight CIE model will be discussed. The colors of matte and specular surfaces have been estimated by use of the developed color model and surface reflection function in this paper. The results are shown to be highly reliable.

  19. 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.

  20. Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

    Science.gov (United States)

    Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

    2017-05-01

    Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

  1. Histogram of Intensity Feature Extraction for Automatic Plastic Bottle Recycling System Using Machine Vision

    Directory of Open Access Journals (Sweden)

    Suzaimah Ramli

    2008-01-01

    Full Text Available Currently, many recycling activities adopt manual sorting for plastic recycling that relies on plant personnel who visually identify and pick plastic bottles as they travel along the conveyor belt. These bottles are then sorted into the respective containers. Manual sorting may not be a suitable option for recycling facilities of high throughput. It has also been noted that the high turnover among sorting line workers had caused difficulties in achieving consistency in the plastic separation process. As a result, an intelligent system for automated sorting is greatly needed to replace manual sorting system. The core components of machine vision for this intelligent sorting system is the image recognition and classification. In this research, the overall plastic bottle sorting system is described. Additionally, the feature extraction algorithm used is discussed in detail since it is the core component of the overall system that determines the success rate. The performance of the proposed feature extractions were evaluated in terms of classification accuracy and result obtained showed an accuracy of more than 80%.

  2. Machine Vision Based Measurement of Dynamic Contact Angles in Microchannel Flows

    Institute of Scientific and Technical Information of China (English)

    Valtteri Heiskanen; Kalle Marjanen; Pasi Kallio

    2008-01-01

    When characterizing flows in miniaturized channels, the determination of the dynamic contact angle is important. By measuring the dynamic contact angle, the flow properties of the flowing liquid and the effect of material properties on the flow can be characterized. A machine vision based system to measure the contact angle of front or rear menisci of a moving liquid plug is described in this article. In this research, transparent flow channels fabricated on thermoplastic polymer and scaled with an adhesive tape are used. The transparency of the channels enables image based monitoring and measurement of flow variables, including the dynamic contact angle. It is shown that the dynamic angle can be measured from a liquid flow in a channel using the image based measurement system. An image processing algorithm has been developed in a MATLAB environment. Im-ages are taken using a CCD camera and the channels are illuminated using a custom made ring light. Two fitting methods, a circle and two parabolas, are experimented and the results are compared in the measurement of the dynamic contact angles.

  3. The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2015-01-01

    Full Text Available Ebola virus disease (EVD distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, in recent years, computational experiments based on artificial society appeared, providing a new approach to study the propagation of EVD and analyze the corresponding interventions. Therefore, the rationality of artificial society is the key to the accuracy and reliability of experiment results. Individuals’ behaviors along with travel mode directly affect the propagation among individuals. Firstly, artificial Beijing is reconstructed based on geodemographics and machine learning is involved to optimize individuals’ behaviors. Meanwhile, Ebola course model and propagation model are built, according to the parameters in West Africa. Subsequently, propagation mechanism of EVD is analyzed, epidemic scenario is predicted, and corresponding interventions are presented. Finally, by simulating the emergency responses of Chinese government, the conclusion is finally drawn that Ebola is impossible to outbreak in large scale in the city of Beijing.

  4. Machine vision assisted analysis of structure-localization relationships in a combinatorial library of prospective bioimaging probes

    OpenAIRE

    Shedden, Kerby; Li, Qian; Liu, Fangyi; Chang, Young Tae; Rosania, Gus R.

    2009-01-01

    With a combinatorial library of bioimaging probes, it is now possible to use machine vision to analyze the contribution of different building blocks of the molecules to their cell-associated visual signals. For athis purpose, cell-permeant, fluorescent styryl molecules were synthesized by condensation of 168 aldehyde with 8 pyridinium/quinolinium building blocks. Images of cells incubated with fluorescent molecules were acquired with a high content screening instrument. Chemical and image fea...

  5. "Machine" consciousness and "artificial" thought: an operational architectonics model guided approach.

    Science.gov (United States)

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Neves, Carlos F H

    2012-01-05

    Instead of using low-level neurophysiology mimicking and exploratory programming methods commonly used in the machine consciousness field, the hierarchical operational architectonics (OA) framework of brain and mind functioning proposes an alternative conceptual-theoretical framework as a new direction in the area of model-driven machine (robot) consciousness engineering. The unified brain-mind theoretical OA model explicitly captures (though in an informal way) the basic essence of brain functional architecture, which indeed constitutes a theory of consciousness. The OA describes the neurophysiological basis of the phenomenal level of brain organization. In this context the problem of producing man-made "machine" consciousness and "artificial" thought is a matter of duplicating all levels of the operational architectonics hierarchy (with its inherent rules and mechanisms) found in the brain electromagnetic field. We hope that the conceptual-theoretical framework described in this paper will stimulate the interest of mathematicians and/or computer scientists to abstract and formalize principles of hierarchy of brain operations which are the building blocks for phenomenal consciousness and thought. Copyright © 2010 Elsevier B.V. All rights reserved.

  6. A machine vision approach to seam tracking in real-time in PAW of large-diameter stainless steel tube

    Institute of Scientific and Technical Information of China (English)

    葛景国; 朱政强; 何德孚; 陈立功

    2004-01-01

    Manual monitoring and seam tracking through watching weld pool images in real-time, by naked eyes or by industrial TV, are experience-depended, subjective, labor intensive, and sometimes biased. So it is necessary to realize the automation of computer-aided seam tracking. A PAW (plasma arc welding) seam tracking system was developed, which senses the molten pool and the seam in one frame by a vision sensor, and then detects the seam deviation to adjust the work piece motion adaptively to the seam position sensed by vision sensor. A novel molten pool area image-processing algorithm based on machine vision was proposed. The algorithm processes each image at the speed of 20 frames/second in real-time to extract three feature variables to get the seam deviation. It is proved experimentally that the algorithm is very fast and effective. Issues related to the algorithm are also discussed.

  7. Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review

    Directory of Open Access Journals (Sweden)

    Mario Sansone

    2013-01-01

    Full Text Available Computer systems for Electrocardiogram (ECG analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units or in prompt detection of dangerous events (e.g., ventricular fibrillation. Together with clinical applications (arrhythmia detection and heart rate variability analysis, ECG is currently being investigated in biometrics (human identification, an emerging area receiving increasing attention. Methodologies for clinical applications can have both differences and similarities with respect to biometrics. This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification. Considering the vast literature in the field and the limited space of this review, we dedicated a detailed discussion only to a few classifiers (Artificial Neural Networks and Support Vector Machines because of their popularity; however, other techniques such as Hidden Markov Models and Kalman Filtering will be also mentioned.

  8. Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Kuan-Cheng Lin

    2014-01-01

    Full Text Available Because of the advances in Internet technology, the applications of the Internet of Things have become a crucial topic. The number of mobile devices used globally substantially increases daily; therefore, information security concerns are increasingly vital. The botnet virus is a major threat to both personal computers and mobile devices; therefore, a method of botnet feature characterization is proposed in this study. The proposed method is a classified model in which an artificial fish swarm algorithm and a support vector machine are combined. A LAN environment with several computers which has infected by the botnet virus was simulated for testing this model; the packet data of network flow was also collected. The proposed method was used to identify the critical features that determine the pattern of botnet. The experimental results indicated that the method can be used for identifying the essential botnet features and that the performance of the proposed method was superior to that of genetic algorithms.

  9. IDENTIFICATION OF ERYTHEMATO-SQUAMOUS SKIN DISEASES USING EXTREME LEARNING MACHINE AND ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Sunday Olusanya Olatunji

    2013-10-01

    Full Text Available In this work, a new identification model, based on extreme learning machine (ELM, to better identify Erythemato – Squamous skin diseases have been proposed and implemented and the results compared to that of the classical artificial neural network (ANN. ELMs provide solutions to single- and multi- hidden layer feed-forward neural networks. ELMs can achieve high learning speed, good generalization performance, and ease of implementation. Experimental results indicated that ELM outperformed the classical ANN in all fronts both for the training and testing cases. The effect of varying size of training and testing set on the performance of classifiers were also investigated in this study. The proposed classifier demonstrated to be a viable tool in this germane field of medical diagnosis as indicated by its high accuracy and consistency of result.

  10. Artificial Neural Networks and Support Vector Machines for Water Demand Time Series Forecasting

    CERN Document Server

    Msiza, Ishmael S; Nelwamondo, Fulufhelo Vincent

    2007-01-01

    Water plays a pivotal role in many physical processes, and most importantly in sustaining human life, animal life and plant life. Water supply entities therefore have the responsibility to supply clean and safe water at the rate required by the consumer. It is therefore necessary to implement mechanisms and systems that can be employed to predict both short-term and long-term water demands. The increasingly growing field of computational intelligence techniques has been proposed as an efficient tool in the modelling of dynamic phenomena. The primary objective of this paper is to compare the efficiency of two computational intelligence techniques in water demand forecasting. The techniques under comparison are the Artificial Neural Networks (ANNs) and the Support Vector Machines (SVMs). In this study it was observed that the ANNs perform better than the SVMs. This performance is measured against the generalisation ability of the two.

  11. A Comparison between Regression, Artificial Neural Networks and Support Vector Machines for Predicting Stock Market Index

    Directory of Open Access Journals (Sweden)

    Alaa F. Sheta

    2015-07-01

    Full Text Available Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take correct actions to develop a better economy. The inability to predict fluctuation of the stock market might cause serious profit loss. The challenge is that we always deal with dynamic market which is influenced by many factors. They include political, financial and reserve occasions. Thus, stable, robust and adaptive approaches which can provide models have the capability to accurately predict stock index are urgently needed. In this paper, we explore the use of Artificial Neural Networks (ANNs and Support Vector Machines (SVM to build prediction models for the S&P 500 stock index. We will also show how traditional models such as multiple linear regression (MLR behave in this case. The developed models will be evaluated and compared based on a number of evaluation criteria.

  12. Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hong-liang; ZOU Zhong; LI Jie; CHEN Xiang-tao

    2008-01-01

    Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificial neural network(ANN) and the support vector machine(SVM) respectively. And the recognition experiments were carried out by using flame image data sampled from an alumina rotary kiln to evaluate their effectiveness. The results show that the two recognition methods can achieve good results, which verify the effectiveness of the shape descriptor. The highest recognition rate is 88.83% for SVM and 87.38% for ANN, which means that the performance of the SVM is better than that of the ANN.

  13. Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

    Science.gov (United States)

    Chen, Chau-Kuang

    2010-01-01

    Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

  14. Tracking Control of a Leg Rehabilitation Machine Driven by Pneumatic Artificial Muscles Using Composite Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Ming-Kun Chang

    2014-01-01

    Full Text Available It is difficult to achieve excellent tracking performance for a two-joint leg rehabilitation machine driven by pneumatic artificial muscles (PAMs because the system has a coupling effect, highly nonlinear and time-varying behavior associated with gas compression, and the nonlinear elasticity of bladder containers. This paper therefore proposes a T-S fuzzy theory with supervisory control in order to overcome the above problems. The T-S fuzzy theory decomposes the model of a nonlinear system into a set of linear subsystems. In this manner, the controller in the T-S fuzzy model is able to use simple linear control techniques to provide a systematic framework for the design of a state feedback controller. Then the LMI Toolbox of MATLAB can be employed to solve linear matrix inequalities (LMIs in order to determine controller gains based on the Lyapunov direct method. Moreover, the supervisory control can overcome the coupling effect for a leg rehabilitation machine. Experimental results show that the proposed controller can achieve excellent tracking performance, and guarantee robustness to system parameter uncertainties.

  15. Parametric Optimization of Nd:YAG Laser Beam Machining Process Using Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Rajarshi Mukherjee

    2013-01-01

    Full Text Available Nd:YAG laser beam machining (LBM process has a great potential to manufacture intricate shaped microproducts with its unique characteristics. In practical applications, such as drilling, grooving, cutting, or scribing, the optimal combination of Nd:YAG LBM process parameters needs to be sought out to provide the desired machining performance. Several mathematical techniques, like Taguchi method, desirability function, grey relational analysis, and genetic algorithm, have already been applied for parametric optimization of Nd:YAG LBM processes, but in most of the cases, suboptimal or near optimal solutions have been reached. This paper focuses on the application of artificial bee colony (ABC algorithm to determine the optimal Nd:YAG LBM process parameters while considering both single and multiobjective optimization of the responses. A comparative study with other population-based algorithms, like genetic algorithm, particle swarm optimization, and ant colony optimization algorithm, proves the global applicability and acceptability of ABC algorithm for parametric optimization. In this algorithm, exchange of information amongst the onlooker bees minimizes the search iteration for the global optimal and avoids generation of suboptimal solutions. The results of two sample paired t-tests also demonstrate its superiority over the other optimization algorithms.

  16. Monthly evaporation forecasting using artificial neural networks and support vector machines

    Science.gov (United States)

    Tezel, Gulay; Buyukyildiz, Meral

    2016-04-01

    Evaporation is one of the most important components of the hydrological cycle, but is relatively difficult to estimate, due to its complexity, as it can be influenced by numerous factors. Estimation of evaporation is important for the design of reservoirs, especially in arid and semi-arid areas. Artificial neural network methods and support vector machines (SVM) are frequently utilized to estimate evaporation and other hydrological variables. In this study, usability of artificial neural networks (ANNs) (multilayer perceptron (MLP) and radial basis function network (RBFN)) and ɛ-support vector regression (SVR) artificial intelligence methods was investigated to estimate monthly pan evaporation. For this aim, temperature, relative humidity, wind speed, and precipitation data for the period 1972 to 2005 from Beysehir meteorology station were used as input variables while pan evaporation values were used as output. The Romanenko and Meyer method was also considered for the comparison. The results were compared with observed class A pan evaporation data. In MLP method, four different training algorithms, gradient descent with momentum and adaptive learning rule backpropagation (GDX), Levenberg-Marquardt (LVM), scaled conjugate gradient (SCG), and resilient backpropagation (RBP), were used. Also, ɛ-SVR model was used as SVR model. The models were designed via 10-fold cross-validation (CV); algorithm performance was assessed via mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R 2). According to the performance criteria, the ANN algorithms and ɛ-SVR had similar results. The ANNs and ɛ-SVR methods were found to perform better than the Romanenko and Meyer methods. Consequently, the best performance using the test data was obtained using SCG(4,2,2,1) with R 2 = 0.905.

  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. Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system.

    Science.gov (United States)

    Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari Hormozi, Shahram; Wah, Teh Ying; Aghabozorgi, Saeed; Pourhoseingholi, Mohamad Amin; Olariu, Teodora

    2015-04-01

    Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis. Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows. With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients. There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for

  19. 机器视觉的构造及应用%A Summary of the Construction and Application of Machine Vision

    Institute of Scientific and Technical Information of China (English)

    徐仲勋; 黄科程

    2015-01-01

    文章介绍了机器视觉在处理图像时的几种方法以及目标跟踪的原理,分析了机器视觉在农业、工业、医学等领域的实际应用情况,探讨了现阶段机器视觉在各个领域存在的一些问题和解决的方法,最后对机器视觉技术的应用和发展前景做了展望。%This paper introduces the concept of machine vision, structure, expounds the developing situation, such as light source, optical lens, camera, etc. This paper introduces the application of machine vision in the several methods of processing the image. Machine vision were analyzed in the agricultural, industrial, medical and other fields of application. Discusses the present some problems of machine vision in various fields and the solution method. Finally, the application of machine vision technology and development prospects were discussed.

  20. An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Hong-Hai Tran

    2014-01-01

    Full Text Available Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach—autotuning support vector machine—is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM algorithm is utilized to classify grouting activities into two classes: success and  failure. Meanwhile, the differential evolution (DE optimization algorithm is employed to identify the optimal tuning parameters of the SVM algorithm, namely, the penalty parameter and the kernel function parameter. The integration of the SVM and DE algorithms allows the newly established method to operate automatically without human prior knowledge or tedious processes for parameter setting. An experiment using a set of in situ data samples demonstrates that the newly established method can produce an outstanding prediction performance.

  1. DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks.

    Science.gov (United States)

    Kim, Lok-Won

    2017-03-08

    Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs. The implemented RBM ANN accelerator (integrating 1024 x 1024 network size, using 128 input cases per batch, and running at a 303-MHz clock frequency) integrated in a state-of-the art field-programmable gate array (FPGA) (Xilinx Virtex 7 XC7V-2000T) provides a computational performance of 301-billion connection-updates-per-second and about 193 times higher performance than a software solution running on general purpose processors. Most importantly, the architecture enables over 4 times (12 times in batch learning) higher performance compared with a previous work when both are implemented in an FPGA device (XC2VP70).

  2. A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

    Directory of Open Access Journals (Sweden)

    Gaochao Xu

    2013-01-01

    Full Text Available Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

  3. Response surface and artificial neural network prediction model and optimization for surface roughness in machining

    Directory of Open Access Journals (Sweden)

    Ashok Kumar Sahoo

    2015-04-01

    Full Text Available The present paper deals with the development of prediction model using response surface methodology and artificial neural network and optimizes the process parameter using 3D surface plot. The experiment has been conducted using coated carbide insert in machining AISI 1040 steel under dry environment. The coefficient of determination value for RSM model is found to be high (R2 = 0.99 close to unity. It indicates the goodness of fit for the model and high significance of the model. The percentage of error for RSM model is found to be only from -2.63 to 2.47. The maximum error between ANN model and experimental lies between -1.27 and 0.02 %, which is significantly less than the RSM model. Hence, both the proposed RSM and ANN prediction model sufficiently predict the surface roughness, accurately. However, ANN prediction model seems to be better compared with RSM model. From the 3D surface plots, the optimal parametric combination for the lowest surface roughness is d1-f1-v3 i.e. depth of cut of 0.1 mm, feed of 0.04 mm/rev and cutting speed of 260 m/min respectively.

  4. Investigation into the use of smartphone as a machine vision device for engineering metrology and flaw detection, with focus on drilling

    Science.gov (United States)

    Razdan, Vikram; Bateman, Richard

    2015-05-01

    This study investigates the use of a Smartphone and its camera vision capabilities in Engineering metrology and flaw detection, with a view to develop a low cost alternative to Machine vision systems which are out of range for small scale manufacturers. A Smartphone has to provide a similar level of accuracy as Machine Vision devices like Smart cameras. The objective set out was to develop an App on an Android Smartphone, incorporating advanced Computer vision algorithms written in java code. The App could then be used for recording measurements of Twist Drill bits and hole geometry, and analysing the results for accuracy. A detailed literature review was carried out for in-depth study of Machine vision systems and their capabilities, including a comparison between the HTC One X Android Smartphone and the Teledyne Dalsa BOA Smart camera. A review of the existing metrology Apps in the market was also undertaken. In addition, the drilling operation was evaluated to establish key measurement parameters of a twist Drill bit, especially flank wear and diameter. The methodology covers software development of the Android App, including the use of image processing algorithms like Gaussian Blur, Sobel and Canny available from OpenCV software library, as well as designing and developing the experimental set-up for carrying out the measurements. The results obtained from the experimental set-up were analysed for geometry of Twist Drill bits and holes, including diametrical measurements and flaw detection. The results show that Smartphones like the HTC One X have the processing power and the camera capability to carry out metrological tasks, although dimensional accuracy achievable from the Smartphone App is below the level provided by Machine vision devices like Smart cameras. A Smartphone with mechanical attachments, capable of image processing and having a reasonable level of accuracy in dimensional measurement, has the potential to become a handy low-cost Machine vision

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

    Science.gov (United States)

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

    2009-12-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Davis, J D [Applied Research Laboratories, University of Texas, 10000 Burnet Rd, Austin, TX 78757 (United States); Barrett, S F; Wright, C H G [Electrical and Computer Engineering, University of Wyoming, Dept 3295 1000 E. University Ave, Laramie, WY 82071 (United States); Wilcox, M, E-mail: steveb@uwyo.ed [Department of Biology, United States Air Force Academy, CO 80840 (United States)

    2009-12-15

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

  7. Measuring the modulation-transfer function of radiation-tolerant machine-vision system using the sum of harmonic components of different frequency

    Science.gov (United States)

    Perezyabov, Oleg A.; Maltseva, Nadezhda K.; Ilinski, Aleksandr V.

    2017-05-01

    There are a number of robotic systems that are used for nuclear power plant maintenance and it is important to ensure the necessary safety level. The machine-vision systems are applied for this purpose. There are special requirements for the image quality of these systems. To estimate the resolution of a video-system one should determine the impact of the system on the special test pattern. In this paper we describe the procedure of determining the number of the modulation transfer function values of the radiation-tolerant machine-vision systems using the test pattern, containing the sum of the harmonic functions of different frequency.

  8. Application of generalized Hough transform for detecting sugar beet plant from weed using machine vision method

    Directory of Open Access Journals (Sweden)

    A Bakhshipour Ziaratgahi

    2017-05-01

    Full Text Available Introduction Sugar beet (Beta vulgaris L. as the second most important world’s sugar source after sugarcane is one of the major industrial crops. The presence of weeds in sugar beet fields, especially at early growth stages, results in a substantial decrease in the crop yield. It is very important to efficiently eliminate weeds at early growing stages. The first step of precision weed control is accurate detection of weeds location in the field. This operation can be performed by machine vision techniques. Hough transform is one of the shape feature extraction methods for object tracking in image processing which is basically used to identify lines or other geometrical shapes in an image. Generalized Hough transform (GHT is a modified version of the Hough transform used not only for geometrical forms, but also for detecting any arbitrary shape. This method is based on a pattern matching principle that uses a set of vectors of feature points (usually object edge points to a reference point to construct a pattern. By comparing this pattern with a set pattern, the desired shape is detected. The aim of this study was to identify the sugar beet plant from some common weeds in a field using the GHT. Materials and Methods Images required for this study were taken at the four-leaf stage of sugar beet as the beginning of the critical period of weed control. A shelter was used to avoid direct sunlight and prevent leaf shadows on each other. The obtained images were then introduced to the Image Processing Toolbox of MATLAB programming software for further processing. Green and Red color components were extracted from primary RGB images. In the first step, binary images were obtained by applying the optimal threshold on the G-R images. A comprehensive study of several sugar beet images revealed that there is a unique feature in sugar beet leaves which makes them differentiable from the weeds. The feature observed in all sugar beet plants at the four

  9. Simulation of artificial vision: II. Eccentric reading of full-page text and the learning of this task.

    Science.gov (United States)

    Sommerhalder, Jörg; Rappaz, Benjamin; de Haller, Raoul; Fornos, Angélica Pérez; Safran, Avinoam B; Pelizzone, Marco

    2004-01-01

    Reading of isolated words in conditions mimicking artificial vision has been found to be a difficult but feasible task. In particular at relatively high eccentricities, a significant adaptation process was required to reach optimal performances [Vision Res. 43 (2003) 269]. The present study addressed the task of full-page reading, including page navigation under control of subject's own eye movements. Conditions of artificial vision mimicking a retinal implant were simulated by projecting stimuli with reduced information content (lines of pixelised text) onto a restricted and eccentric area of the retina. Three subjects, naïve to the task, were trained for almost two months (about 1 h/day) to read full-page texts. Subjects had to use their own eye movements to displace a 10 degrees x 7 degrees viewing window, stabilised at 15 degrees eccentricity in their lower visual field. Initial reading scores were very low for two subjects (about 13% correctly read words), and astonishingly high for the third subject (86% correctly read words). However, all of them significantly improved their performance with time, reaching close to perfect reading scores (ranging from 86% to 98% correct) at the end of the training process. Reading rates were as low as 1-5 words/min at the beginning of the experiment and increased significantly with time to 14-28 words/min. Qualitative text understanding was also estimated. We observed that reading scores of at least 85% correct were necessary to achieve 'good' text understanding. Gaze position recordings, made during the experimental sessions, demonstrated that the control of eye movements, especially the suppression of reflexive vertical saccades, constituted an important part of the overall adaptive learning process. Taken together, these results suggest that retinal implants might restore full-page text reading abilities to blind patients. About 600 stimulation contacts, distributed on an implant surface of 3 x 2 mm2, appear to be a

  10. Artificial vision: needs, functioning, and testing of a retinal electronic prosthesis.

    Science.gov (United States)

    Chader, Gerald J; Weiland, James; Humayun, Mark S

    2009-01-01

    Hundreds of thousands around the world have poor vision or no vision at all due to inherited retinal degenerations (RDs) like retinitis pigmentosa (RP). Similarly, millions suffer from vision loss due to age-related macular degeneration (AMD). In both of these allied diseases, the primary target for pathology is the retinal photoreceptor cells that dysfunction and die. Secondary neurons though are relatively spared. To replace photoreceptor cell function, an electronic prosthetic device can be used such that retinal secondary neurons receive a signal that simulates an external visual image. The composite device has a miniature video camera mounted on the patient's eyeglasses, which captures images and passes them to a microprocessor that converts the data to an electronic signal. This signal, in turn, is transmitted to an array of electrodes placed on the retinal surface, which transmits the patterned signal to the remaining viable secondary neurons. These neurons (ganglion, bipolar cells, etc.) begin processing the signal and pass it down the optic nerve to the brain for final integration into a visual image. Many groups in different countries have different versions of the device, including brain implants and retinal implants, the latter having epiretinal or subretinal placement. The device furthest along in development is an epiretinal implant sponsored by Second Sight Medical Products (SSMP). Their first-generation device had 16 electrodes with human testing in a Phase 1 clinical trial beginning in 2002. The second-generation device has 60+ electrodes and is currently in Phase 2/3 clinical trial. Increased numbers of electrodes are planned for future versions of the device. Testing of the device's efficacy is a challenge since patients admitted into the trial have little or no vision. Thus, methods must be developed that accurately and reproducibly record small improvements in visual function after implantation. Standard tests such as visual acuity, visual

  11. A Research Review of Effect of Artificial Lighting on Color Vision%人工照明对色觉影响的研究综述

    Institute of Scientific and Technical Information of China (English)

    胡韵萩; 严永红

    2016-01-01

    Color vision is one of the important vision functions of human .The paper summarizes the internal and oversea studying achievement about the effect of artificial lighting on color vision .The research found that color vision comes from reaction of wavelengths of light on retina , which transforms information into electrochemical signal and deliveries it to cerebral visual cortex by color channel .The variation of color vision is related to spectrum , color temperature and illuminance .Furthermore color vision changes with age and gender .In the future , the results of color vision research will provide suggestions for artificial lighting study , and create healthy artificial lighting environment by in-depth study .%色觉是人眼视功能之一, 其重要性不可忽视. 对国内外人工照明对色觉影响的研究成果进行了综述, 研究发现, 色觉由不同波长的光作用于视网膜, 外界信息转换为电化学信号, 通过色觉通路传送至大脑视皮层而形成. 光谱、 色温、 照度, 均与色觉的变化有关, 不同的人工照明环境下, 人的辨色能力也有不同. 除此之外, 人的辨色能力也与自身的年龄和性别有关. 色觉研究相关成果将为未来的人工照明环境研究提供建议, 并通过深入分析研究以得到更优的人工照明环境.

  12. A Starter's Guide to Artificial Intelligence.

    Science.gov (United States)

    McConnell, Barry A.; McConnell, Nancy J.

    1988-01-01

    Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

  13. Machine vision process monitoring on a poultry processing kill line: results from an implementation

    Science.gov (United States)

    Usher, Colin; Britton, Dougl; Daley, Wayne; Stewart, John

    2005-11-01

    Researchers at the Georgia Tech Research Institute designed a vision inspection system for poultry kill line sorting with the potential for process control at various points throughout a processing facility. This system has been successfully operating in a plant for over two and a half years and has been shown to provide multiple benefits. With the introduction of HACCP-Based Inspection Models (HIMP), the opportunity for automated inspection systems to emerge as viable alternatives to human screening is promising. As more plants move to HIMP, these systems have the great potential for augmenting a processing facilities visual inspection process. This will help to maintain a more consistent and potentially higher throughput while helping the plant remain within the HIMP performance standards. In recent years, several vision systems have been designed to analyze the exterior of a chicken and are capable of identifying Food Safety 1 (FS1) type defects under HIMP regulatory specifications. This means that a reliable vision system can be used in a processing facility as a carcass sorter to automatically detect and divert product that is not suitable for further processing. This improves the evisceration line efficiency by creating a smaller set of features that human screeners are required to identify. This can reduce the required number of screeners or allow for faster processing line speeds. In addition to identifying FS1 category defects, the Georgia Tech vision system can also identify multiple "Other Consumer Protection" (OCP) category defects such as skin tears, bruises, broken wings, and cadavers. Monitoring this data in an almost real-time system allows the processing facility to address anomalies as soon as they occur. The Georgia Tech vision system can record minute-by-minute averages of the following defects: Septicemia Toxemia, cadaver, over-scald, bruises, skin tears, and broken wings. In addition to these defects, the system also records the length and

  14. An Automated Recognition of Fake or Destroyed Indian Currency Notes in Machine Vision

    Directory of Open Access Journals (Sweden)

    Sanjana

    2012-04-01

    Full Text Available Almost every country in the world face the problem of counterfeitcurrency notes, but in India the problem is acute as the country ishit hard by this evil practice. Fake notes in India in denominationsof Rs.100, 500 and 1000 are being flooded into the system. Inorder to deal with such type of problems, an automated recognitionof currency notes in introduced by with the help of featureextraction, classification based in SVM, Neural Nets, and heuristicapproach. This technique is also subjected with the computervision where all processing with the image is done by machine.The machine is fitted with a CDD camera which will scan theimage of the currency note considering the dimensions of thebanknote and software will process the image segments with thehelp of SVM and character recognition methods. ANN is alsointroduced in this paper to train the data and classify the segmentsusing its datasets. To implement this design we are dealing withMATLAB Tool.

  15. A Planar-Dimensions Machine Vision Measurement Method Based on Lens Distortion Correction

    Directory of Open Access Journals (Sweden)

    Qiucheng Sun

    2013-01-01

    Full Text Available Lens distortion practically presents in a real optical imaging system causing nonuniform geometric distortion in the images and gives rise to additional errors in the vision measurement. In this paper, a planar-dimensions vision measurement method is proposed by improving camera calibration, in which the lens distortion is corrected on the pixel plane of image. The method can be divided into three steps: firstly, the feature points, only in the small central region of the image, are used to get a more accurate perspective projection model; secondly, rather than defining a uniform model, the smoothing spline function is used to describe the lens distortion in the measurement region of image, and two correction functions can be obtained by fitting two deviation surfaces; finally, a measurement method for planar dimensions is proposed, in which accurate magnification factor of imaging system can be obtained by using the correction functions. The effectiveness of the method is demonstrated by applying the proposed method to the test of measuring shaft diameter. Experimental data prove that the accurate planar-dimensions measurements can be performed using the proposed method even if images are deformed by lens distortion.

  16. Artificial immune system based on adaptive clonal selection for feature selection and parameters optimisation of support vector machines

    Science.gov (United States)

    Sadat Hashemipour, Maryam; Soleimani, Seyed Ali

    2016-01-01

    Artificial immune system (AIS) algorithm based on clonal selection method can be defined as a soft computing method inspired by theoretical immune system in order to solve science and engineering problems. Support vector machine (SVM) is a popular pattern classification method with many diverse applications. Kernel parameter setting in the SVM training procedure along with the feature selection significantly impacts on the classification accuracy rate. In this study, AIS based on Adaptive Clonal Selection (AISACS) algorithm has been used to optimise the SVM parameters and feature subset selection without degrading the SVM classification accuracy. Several public datasets of University of California Irvine machine learning (UCI) repository are employed to calculate the classification accuracy rate in order to evaluate the AISACS approach then it was compared with grid search algorithm and Genetic Algorithm (GA) approach. The experimental results show that the feature reduction rate and running time of the AISACS approach are better than the GA approach.

  17. Prediction of Tourism Demand in Iran by Using Artificial Neural Network (ANN and Supporting Vector Machine (SVR

    Directory of Open Access Journals (Sweden)

    Seyedehelham Sadatiseyedmahalleh

    2016-02-01

    Full Text Available This research examines and proves this effectiveness connected with artificial neural networks (ANNs as an alternative approach to the use of Support Vector Machine (SVR in the tourism research. This method can be used for the tourism industry to define the turism’s demands in Iran. The outcome reveals the use of ANNs in tourism research might result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand evaluation is needed to establish and validate the effects.

  18. Integrating human factors and artificial intelligence in the development of human-machine cooperation

    NARCIS (Netherlands)

    Maanen, P.P. van; Lindenberg, J.; Neericx, M.A.

    2005-01-01

    Increasing machine intelligence leads to a shift from a mere interactive to a much more complex cooperative human-machine relation requiring a multidisciplinary development approach. This paper presents a generic multidisciplinary cognitive engineering method CE+ for the integration of human factors

  19. Theory research of seam recognition and welding torch pose control based on machine vision

    Science.gov (United States)

    Long, Qiang; Zhai, Peng; Liu, Miao; He, Kai; Wang, Chunyang

    2017-03-01

    At present, the automation requirement of the welding become higher, so a method of the welding information extraction by vision sensor is proposed in this paper, and the simulation with the MATLAB has been conducted. Besides, in order to improve the quality of robot automatic welding, an information retrieval method for welding torch pose control by visual sensor is attempted. Considering the demands of welding technology and engineering habits, the relative coordinate systems and variables are strictly defined, and established the mathematical model of the welding pose, and verified its feasibility by using the MATLAB simulation in the paper, these works lay a foundation for the development of welding off-line programming system with high precision and quality.

  20. 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.

  1. CARACTERIZACIÓN DE CAFÉ CEREZA EMPLEANDO TÉCNICAS DE VISIÓN ARTIFICIAL AN ARTIFICIAL VISION SYSTEM FOR CLASSIFICATION OF COFFEE BEANS

    Directory of Open Access Journals (Sweden)

    Zulma Liliana Sandoval Niño

    2007-12-01

    Full Text Available Se desarrolló un sistema de visión artificial para la clasificación de frutos de café en once categorías dependiendo de su estado de madurez. Para la descripción de la forma, el color y la textura de cada fruto de café se extrajeron 208 características. La reducción del conjunto de características de 208 a 9 se hizo con base en los resultados de dos métodos de selección de características, uno univariado y otro multivariado. Las características seleccionadas corresponden a 4 características de textura, 3 de color y 2 de forma. Este conjunto final de características se evaluó en dos técnicas de clasificación: Bayesiano y redes neuronales. Con el clasificador Bayesiano se obtuvo un error de clasificación del 5,43% y requirió un tiempo de clasificación de 5,5 ms, mientras que usando redes neuronales el error de clasificación fue de 7,46%, pero disminuyó el tiempo de clasificación a 0,8 ms.An artificial vision system for classification of coffee beans, in eleven categories, according to its state of maturity was developed. The description of the coffee beans was done by using 208 characteristics (form, color and texture characteristics. The reduction of the set of characteristics from 208 to 9 was done by using two methods of characteristic selection. The final set of characteristics is composed by 4 texture characteristics, 3 color characteristics and 2 shape characteristics. This final set was evaluated in two classifiers: The Bayesian and a neuronal networks classifier. The classification error obtained by the Bayesian classifier was 5,43%, it required 5,5 ms for the classification process, while the error obtained by neuronal networks classifier was 7,46% and the classification time decreased to 0,8 ms.

  2. The Bottle of Beverage Label Detection Device Based on Machine Vision%基于机器视觉的饮料瓶标签检测设备

    Institute of Scientific and Technical Information of China (English)

    张树君; 辛莹莹; 陈大千

    2014-01-01

    In the packaging testing industry, consumers pay attention to the quality of the products.How to realize the bottles and efficient full label detection is the important problems facing with the beverage industry. Basing on the above problem, The company developed to test the beverage bottle label of special equipment, the control system by TM258LD42DT,the main characteristic is to be able to elaborate testing (for example the tag of beverage bottle high or low, the tag such as crease, labels), and the equipment of detection have the high efficiency (its detection precision can be achieved 4 mm × 4 mm). This machine has the following functions, for example, the machine-vision detection for tag,the historical data display,the abnormal situation alarm and taking out of the unqualified bottle. And these functions used in the high-speed automatic production line , replace the artificial detection, improve the quality of the testing efficiency and testing,provide the basis for developing the more superior performance model.%在包装检测行业,产品的质量引起了广大消费者的关注。如何实现饮料瓶高效的全标签检测是饮料行业面临的重要问题。基于上述问题,研发了对饮料瓶标签进行检测的专用设备,其控制系统采用的是TM258LD42DT,主要特点是能够精细的检测缺陷(如饮料瓶上标签的高低、标签的破损、标签的折皱等现象),而且设备的检测效率高(其检测精度可达到4 mm×4 mm)。它是集机器视觉的标签检测、历史数据显示、异常情况报警和不合格瓶子的剔除等功能为一体,运用在高速自动化生产线上,代替了人工检测,提高了检测的效率和检测的质量,为开发性能更优越的机型提供基础。

  3. EDITORIAL: The Eye and the Chip: World Congress on Artificial Vision 2004

    Science.gov (United States)

    Hessburg, Philip C.; Rizzo, Joseph

    2005-03-01

    The Eye and the Chip meeting, hosted every other year by the Detroit Institute of Ophthalmology, is a collegial exercise designed to move forward the day when neuro-prosthetic devices afford some level of useful vision to persons now blind from a variety of causes. Our guiding principles are to have an all-inclusive meeting and to permit ample time for discussion among the researchers. Given the growing body of researchers in this exciting field and the significant progress that has been made, our last two meetings of the Eye and the Chip have required three days each to accommodate all who attended. The Eye and the Chip meeting has been successful because of adherence to these guiding principles and to the fact that all three meetings have attracted at least two team members from every research group in the world that is working on developing a visual prosthetic. The model used by the Detroit Institute of Ophthalmology is one used previously in the early days of intraocular lens implantation work. It empowers those sophisticated in the art, working in the field, to interface effectively with research leaders they may or may not have met, who are also heavily involved in the work. Each member of the invited faculty is given a precisely controlled 20-minute period of time to present work of his/her academic department or corporate research laboratory. Following this, there is a full 10-minute discussion with questions coming from the 34 members of the invited faculty, as well as from attendees from the general public, press, engineering, ophthalmology, etc. Often, insights unfold in these discussion periods that are not only of profound significance scientifically, but absolutely fascinating in their contributions to understanding and to the art. We have encouraged patients to attend. The contributions of the patients have helped keep the presentations better grounded. The patients reasonably ask if the researchers understand their needs, and the responses from the

  4. 机器视觉在除草机器人中的应用%Application of Machine Vision in Weeding Robot

    Institute of Scientific and Technical Information of China (English)

    李谦; 蔡晓华

    2014-01-01

    随着农业自动化技术和农业机器人技术的发展,许多国家和企业开始致力于机器视觉除草机器人的试验与研究。为此,在介绍机器视觉技术系统的基础上,结合除草机器人苗草识别的试验,讨论了机器视觉系统在除草机器人中的应用,详细分析了基于机器视觉的苗草识别系统,并优化其系统的硬件、软件结构、功能以及原理等。%With the development of agricultural automation technology and robotics ,many countries and enterprises begin to dedicated to the experimental research of machine vision weeding robot .On the basis of machine vision technology sys-tem introduced in this paper ,combine with the Identification of the Blade of grass test ,th application of machine vision system in the weeding robot was discussed .and analyzed the recognition system of weeding grass based on machine vi-sion.And optimize the structure of hardware and software of the system .Function and principle , etc.

  5. An artificial vision-based control system for automatic heliostat positioning offset correction in a central receiver solar power plant

    Energy Technology Data Exchange (ETDEWEB)

    Berenguel, M. [Universidad de Almeria, Dept. de Lenguajes y Computacion, La Canada Almeria (Spain); Rubio, F.R.; Lara, P.J.; Arahal, M.R.; Camacho, E.F.; Lopez, M. [Universidad de Sevilla, Dept. de Ingenieria de Sistemas y Automatica, Sevilla (Spain); Valverde, A. [Plataforma Solar de Almeria (PSA-CIEMAT), Tabernas (Almeria) (Spain)

    2004-07-01

    This paper presents the development of a simplified and automatic heliostat positioning offset correction control system using artificial vision techniques and common CCD devices. The heliostats of a solar power plant reflect solar radiation onto a receiver (in this case, a volumetric receiver) placed at the top of a tower in order to provide a desired energy flux distribution correlated with the coolant flow (in this case air mass flow) through the receiver, usually in an open loop control configuration. There exist error sources that increase the complexity of the control system, some of which are systematic ones, mainly due to tolerances, wrong mirror facets alignment (optical errors), errors due to the approximations made when calculating the solar position, etc., that produce errors (offsets) in the heliostat orientation (aiming point). The approximation adopted in this paper is based on the use of a B/W CCD camera to correct these deviations in an automatic way imitating the same procedure followed by the operators. The obtained images are used to estimate the distance between the sunbeam centroid projected by the heliostats and a target placed on the tower, this distance thus is used for low accuracy offset correction purposes. Basic threshold-based image processing techniques are used for automatic correction. (Author)

  6. Artificial agents, good care, and modernity.

    Science.gov (United States)

    Coeckelbergh, Mark

    2015-08-01

    When is it ethically acceptable to use artificial agents in health care? This article articulates some criteria for good care and then discusses whether machines as artificial agents that take over care tasks meet these criteria. Particular attention is paid to intuitions about the meaning of 'care', 'agency', and 'taking over', but also to the care process as a labour process in a modern organizational and financial-economic context. It is argued that while there is in principle no objection to using machines in medicine and health care, the idea of them functioning and appearing as 'artificial agents' is problematic and attends us to problems in human care which were already present before visions of machine care entered the stage. It is recommended that the discussion about care machines be connected to a broader discussion about the impact of technology on human relations in the context of modernity.

  7. Application of machine vision in inspecting stem and shape of fruits

    Science.gov (United States)

    Ying, Yibin; Jing, Hansong; Tao, Yang; Jin, Juanqin; Ibarra, Juan G.; Chen, Zhikuan

    2000-12-01

    The shape and the condition of stem are important features in classification of Huanghua pears. As the commonly used thinning and erosion-dilation algorithm in judging the presence of the stem is too slow, a new fast algorithm was put forward. Compared with other part of the pear, the stem is obviously thin and long, with the help of various sized templates, the judgment of whether the stem is present was easily made, meanwhile the stem head and the intersection point of stem bottom and pear were labeled. Furthermore, after the slopes of the tangential line of stem head and tangential line of stem bottom were found, the included angle of these two lines was calculated. It was found that the included angle of the broken stem was obviously different from that of the good stem. After the analysis of 53 pictures of pears, the accuracy to judge whether the stem is present is 100% and whether the stem is good reaches 93%. Also, the algorithm is of robustness and can be made invariant to translation and rotation Meanwhile, the method to describe the shape of irregular fruits was studied. Fourier transformation and inverse Fourier transformation pair were adopted to describe the shape of Huanghua pears, and the algorithm for shape identification, which was based on artificial neural network, was developed. The first sixteen harmonic components of the Fourier descriptor were enough to represent the primary shape of pear, and the identification accuracy could reach 90% by applying the Fourier descriptor in combination with artificial neural network.

  8. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  9. A new optical flat surface measurement method based on machine vision and deflectometry

    Science.gov (United States)

    Kewei, E.; Li, Dahai; Yang, Lijie; Guo, Guangrao; Li, Mengyang; Wang, Xuemin; Zhang, Tao; Xiong, Zhao

    2016-10-01

    Phase Measuring Deflectometry(PMD) is a non-contact, high dynamic-range and full-field metrology which becomes a serious competitor to interferometry. However, the accuracy of deflectometry metrology is strongly influenced by the level of the calibrations. Our paper presents a calibration-based PMD method to test optical flat surface with a high accuracy. In our method, a pin-hole camera was set next to the LCD screen which is used to project sinusoidal fringes to the test flat. And the test flat was placed parallel to the direction of the LCD screen, which makes the geometry calibration process are simplified. The photogrammetric methods used in computer vision science was used to calibrate the pin-hole camera by using a checker pattern shown on another LCD display at six different orientations, the intrinsic parameters can be obtained by processing the obtained image of checker patterns. Further, by making the last orientation of checker pattern is aligned at the same position as the test optical flat, the algorithms used in this paper can obtain the mapping relationship between the CCD pixels and the subaperture coordinates on the test optical flat. We test a optical flat with a size of 50mm in diameter using our setup and algorithm. Our experimental results of optical flat figure from low to high order aberrations show a good agreement with that from the Fizeau interferometer.

  10. On the Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Sengupta, S K; Poland, D; Futterman, J A H

    2003-01-10

    The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this next stage. These features can be more representative of human settlements, and also more time consuming to extract from the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band and panchromatic images, and compare it with the straight-forward processing of the entire image.

  11. A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers.

    Science.gov (United States)

    Lee, Yu-Hao; Hsieh, Ya-Ju; Shiah, Yung-Jong; Lin, Yu-Huei; Chen, Chiao-Yun; Tyan, Yu-Chang; GengQiu, JiaCheng; Hsu, Chung-Yao; Chen, Sharon Chia-Ju

    2017-04-01

    To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-sectional analysis to evaluate the meditation experience with 2 artificial intelligence techniques: artificial neural network and support vector machine. Within this analysis system, 3 features of the electroencephalography alpha spectrum and variant normalizing scaling are manipulated as the evaluating variables for the detection of accuracy. Thereafter, by modulating the sliding window (the period of the analyzed data) and shifting interval of the window (the time interval to shift the analyzed data), the effect of immediate analysis for the 2 methods is compared. This analysis system is performed on 3 meditation groups, categorizing their meditation experiences in 10-year intervals from novice to junior and to senior. After an exhausted calculation and cross-validation across all variables, the high accuracy rate >98% is achievable under the criterion of 0.5-minute sliding window and 2 seconds shifting interval for both methods. In a word, the minimum analyzable data length is 0.5 minute and the minimum recognizable temporal resolution is 2 seconds in the decision of meditative classification. Our proposed classifier of the meditation experience promotes a rapid evaluation system to distinguish meditation experience and a beneficial utilization of artificial techniques for the big-data analysis.

  12. Computer vision and machine learning for robust phenotyping in genome-wide studies

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R. V. Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K.

    2017-01-01

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

  13. Computer vision and machine learning for robust phenotyping in genome-wide studies.

    Science.gov (United States)

    Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

    2017-03-08

    Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

  14. Towards Sustainable Green Production: Exploring Automated Grading for Oil Palm Fresh Fruit Bunches (FFB Using Machine Vision and Spectral Analysis

    Directory of Open Access Journals (Sweden)

    Muhammad Makky

    2013-01-01

    Full Text Available Over the last decade, Indonesian palm oil industry has become a leading producer of the world, and been able to generatenotable foreign export reserves. In spite of this, problems still persist in this industry, including low productivity due to mishandling of raw material in post-harvest operations. One of the prime causes of this is manual grading/sorting of fresh fruit bunches, which is prone to error and misjudgement, as well as subjectivity. High demand of oil palm establishes its high price in world market, which drives the industry to expand its plantation area to increase production. Ultimately, it compromise forests and agricultural land, resulting stagnation or decline in several food products. Alternatively, before expanding plantation extent, oil extraction productivity of existing plantation can be improved by carefully selecting appropriate FFBs for post-harvest processing through introduction of automation. The use of machine vision and spectral analysis has shown to assist productivity of agricultural processing industry. This study employs automation technology for FFB grading in oil palm mills, resulting in improved raw material quality, thereby increasing the oil extraction productivity, and simultaneously contributing to partly release the pressure of deforestation by maintaining green agricultural areas.

  15. DEVELOPMENT OF A PROXIMAL MACHINE VISION SYSTEM FOR OFF-SEASON WEED MAPPING IN BROADACRE NO-TILLAGE FALLOWS

    Directory of Open Access Journals (Sweden)

    H. Liu

    2013-01-01

    Full Text Available Weeds are among the most significant and costly environmental threats in Australian agriculture. Weeds compete with crop plants for moisture, nutrients and sunlight and can have a detrimental impact on crop yields and quality if uncontrolled. The distribution, size, density and species of the weeds are often heterogeneous in the cropping land. Instead of uniformly spray the same type of herbicide to the whole farm land, selective spray can reduce the herbicide usage therefore can reduce the serious problems of herbicide resistance, soil damage and food safety. This study describes a weed mapping method which could be used for broadacre no-tillage fallow weed management. The weed maps have the potential to be used as powerful herbicide prescription maps for spot spray. The weed mapping is realized by the machine vision technologies which including image acquisition, image stitching and photomosaic processing. The sampling points are continuous and the interpolation methods are used at the minimum levels. The experiment result shows that this weed mapping method can map weed under limited conditions.

  16. A noninvasive technique for real-time detection of bruises in apple surface based on machine vision

    Science.gov (United States)

    Zhao, Juan; Peng, Yankun; Dhakal, Sagar; Zhang, Leilei; Sasao, Akira

    2013-05-01

    Apple is one of the highly consumed fruit item in daily life. However, due to its high damage potential and massive influence on taste and export, the quality of apple has to be detected before it reaches the consumer's hand. This study was aimed to develop a hardware and software unit for real-time detection of apple bruises based on machine vision technology. The hardware unit consisted of a light shield installed two monochrome cameras at different angles, LED light source to illuminate the sample, and sensors at the entrance of box to signal the positioning of sample. Graphical Users Interface (GUI) was developed in VS2010 platform to control the overall hardware and display the image processing result. The hardware-software system was developed to acquire the images of 3 samples from each camera and display the image processing result in real time basis. An image processing algorithm was developed in Opencv and C++ platform. The software is able to control the hardware system to classify the apple into two grades based on presence/absence of surface bruises with the size of 5mm. The experimental result is promising and the system with further modification can be applicable for industrial production in near future.

  17. 机器视觉电动缝纫机关键技术研究%A Study on Key Technologies of Electric Sewing Machine Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    崔群; 白顺科

    2014-01-01

    This article introduces the machine vision electric sewing machine,which is an intelligent electric sewing machine based on machine vision and numerical control tool. This machine can recognize and localize all of the sewing pieces of cloth on working table through the image sensors,can grab the sewing pieces of cloth by folding arm manipulator and can complete the accurate and reliable feeding work. So,the form clamp would be removed,and the manual work could be reduced.%研究了一种基于机器视觉和数控技术的工业智能缝纫设备的关键技术。该设备通过图像传感器对工作台上摆放的缝片进行识别与定位,通过送料机械手实现缝片的抓取并实现精确、快速、可靠地缝片的送料,以抛弃目前电动缝纫机的模板夹具,并实现减少操作工干预。

  18. Michelson interferometer experiment based on machine vision%基于 LabVIEW机器视觉的迈克耳孙干涉仪实验

    Institute of Scientific and Technical Information of China (English)

    王建中; 黄林; 唐一文

    2014-01-01

    基于机器视觉设计了迈克耳孙干涉仪实验,采用机器视觉技术替代人眼对目标(干涉圆环)进行分析与测量,可有效避免因视觉疲劳而造成的测量错误。%Based on the machine vision ,the Michelson interferometer was put forward to consider-ably reducing the measurement errors due to visual fatigue in experimental analysis and measure-ments .The interference ring in Michelson interferometer was measured via the machine vision tech-nology ,without observing by naked eyes .

  19. Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning.

    Science.gov (United States)

    Gramatikov, Boris I

    2017-04-27

    Reliable detection of central fixation and eye alignment is essential in the diagnosis of amblyopia ("lazy eye"), which can lead to blindness. Our lab has developed and reported earlier a pediatric vision screener that performs scanning of the retina around the fovea and analyzes changes in the polarization state of light as the scan progresses. Depending on the direction of gaze and the instrument design, the screener produces several signal frequencies that can be utilized in the detection of central fixation. The objective of this study was to compare artificial neural networks with classical statistical methods, with respect to their ability to detect central fixation reliably. A classical feedforward, pattern recognition, two-layer neural network architecture was used, consisting of one hidden layer and one output layer. The network has four inputs, representing normalized spectral powers at four signal frequencies generated during retinal birefringence scanning. The hidden layer contains four neurons. The output suggests presence or absence of central fixation. Backpropagation was used to train the network, using the gradient descent algorithm and the cross-entropy error as the performance function. The network was trained, validated and tested on a set of controlled calibration data obtained from 600 measurements from ten eyes in a previous study, and was additionally tested on a clinical set of 78 eyes, independently diagnosed by an ophthalmologist. In the first part of this study, a neural network was designed around the calibration set. With a proper architecture and training, the network provided performance that was comparable to classical statistical methods, allowing perfect separation between the central and paracentral fixation data, with both the sensitivity and the specificity of the instrument being 100%. In the second part of the study, the neural network was applied to the clinical data. It allowed reliable separation between normal subjects

  20. Artificial Intelligence and Literary Creativity Inside the Mind of Brutus a Storytelling Machine

    CERN Document Server

    Bringsjord, Selmer

    1999-01-01

    Is human creativity a wall that AI can never scale? Many people are happy to admit that experts in many domains can be matched by either knowledge-based or sub-symbolic systems, but even some AI researchers harbor the hope that when it comes to feats of sheer brilliance, mind over machine is an unalterable fact. In this book, the authors push AI toward a time when machines can autonomously write not just humdrum stories of the sort seen for years in AI, but first-rate fiction thought to be the province of human genius. It reports on five years of effort devoted to building a story generator--t

  1. A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

    Science.gov (United States)

    Becker, Lee A.

    1987-01-01

    Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

  2. Abdominal respiration expression of side-view single pig based on machine vision%基于机器视觉的单侧视猪腹式呼吸表达

    Institute of Scientific and Technical Information of China (English)

    马丽; 纪滨

    2012-01-01

    为了监测猪的呼吸急促,引入机器视觉技术构建单侧视猪的腹式呼吸表达。根据猪腹式呼吸时脊腹部分呈起伏的特点,从视频帧的猪轮廓图像中提取形心,确定感兴趣的脊腹线段,然后在垂直方向提取脊线与腹线的截距,接着,构建脊腹线截距描述子(RACID)作为度量脊腹轮廓波动的指标,最后,根据帧序列中随时间变化的RACID,得到猪腹式呼吸表达。逐段检测猪视频腹式呼吸频次,实验结果显示机器法和人工法相关系数为98.23%。%To monitor the tachypnea of pigs, the machine-vision is introduced to construct a model on the pig's abdominal respiration. Firstly, according to the marked dilating and shrinking at ridge-abdomen of pigs, tworidge-abdomen profile segments are ensured based on the centroid of pig's contour. Secondly, the intercepts between both segments are obtained in vertical direction. Thirdly, Ridge-Abdomen Contour Intercept Descriptor (RACID) is created as an index of the fluctuating ones. Finally, the pig abdominal breathing expression is created according to the varying RACID over time. The frequency of the pig abdominal respiration was respectively obtained by the machine-vision method and the artificial method. Experiments showed that the correlation coefficient between the two methods is 98.23%.

  3. Multilevel Cognitive Machine-Learning-Based Concept for Artificial Awareness: Application to Humanoid Robot Awareness Using Visual Saliency

    Directory of Open Access Journals (Sweden)

    Kurosh Madani

    2012-01-01

    Full Text Available As part of “intelligence,” the “awareness” is the state or ability to perceive, feel, or be mindful of events, objects, or sensory patterns: in other words, to be conscious of the surrounding environment and its interactions. Inspired by early-ages human skills developments and especially by early-ages awareness maturation, the present paper accosts the robots intelligence from a different slant directing the attention to combining both “cognitive” and “perceptual” abilities. Within such a slant, the machine (robot shrewdness is constructed on the basis of a multilevel cognitive concept attempting to handle complex artificial behaviors. The intended complex behavior is the autonomous discovering of objects by robot exploring an unknown environment: in other words, proffering the robot autonomy and awareness in and about unknown backdrop.

  4. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    Directory of Open Access Journals (Sweden)

    Mustafa Serter Uzer

    2013-01-01

    Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

  5. A novel kernel extreme learning machine algorithm based on self-adaptive artificial bee colony optimisation strategy

    Science.gov (United States)

    Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Ji, Jin-Chao

    2016-04-01

    In this paper, we propose a novel learning algorithm, named SABC-MKELM, based on a kernel extreme learning machine (KELM) method for single-hidden-layer feedforward networks. In SABC-MKELM, the combination of Gaussian kernels is used as the activate function of KELM instead of simple fixed kernel learning, where the related parameters of kernels and the weights of kernels can be optimised by a novel self-adaptive artificial bee colony (SABC) approach simultaneously. SABC-MKELM outperforms six other state-of-the-art approaches in general, as it could effectively determine solution updating strategies and suitable parameters to produce a flexible kernel function involved in SABC. Simulations have demonstrated that the proposed algorithm not only self-adaptively determines suitable parameters and solution updating strategies learning from the previous experiences, but also achieves better generalisation performances than several related methods, and the results show good stability of the proposed algorithm.

  6. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  7. An Artificial Neural Network Modeling for Force Control System of a Robotic Pruning Machine

    Directory of Open Access Journals (Sweden)

    Ali Hashemi

    2014-06-01

    Full Text Available Nowadays, there has been an increasing application of pruning robots for planted forests due to the growing concern on the efficiency and safety issues. Power consumption and working time of agricultural machines have become important issues due to the high value of energy in modern world. In this study, different multi-layer back-propagation networks were utilized for mapping the complex and highly interactive of pruning process parameters and to predict power consumption and cutting time of a force control equipped robotic pruning machine by knowing input parameters such as: rotation speed, stalk diameter, and sensitivity coefficient. Results showed significant effects of all input parameters on output parameters except rotational speed on cutting time. Therefore, for reducing the wear of cutting system, a less rotational speed in every sensitivity coefficient should be selected.

  8. Carbon Nanotube Growth Rate Regression using Support Vector Machines and Artificial Neural Networks

    Science.gov (United States)

    2014-03-27

    rates are realized by this faster search. 1.3 Assumptions The machine learning approach used for extracting optimal growth parameters assumes the catalyst...and high strength polymers. [25] All carbon to carbon bonds are filled in a CNT so they are chemically inert and stable in acids, bases and solvents ...research in maximizing CNT length. SWNTs of 18.5 cm in length were obtained by using an ethanol precursor and an iron molybdenum catalyst [10]. Also, by

  9. Optimal space-time precoding of artificial sensory feedback through mutichannel microstimulation in bi-directional brain-machine interfaces

    Science.gov (United States)

    Daly, John; Liu, Jianbo; Aghagolzadeh, Mehdi; Oweiss, Karim

    2012-12-01

    Brain-machine interfaces (BMIs) aim to restore lost sensorimotor and cognitive function in subjects with severe neurological deficits. In particular, lost somatosensory function may be restored by artificially evoking patterns of neural activity through microstimulation to induce perception of tactile and proprioceptive feedback to the brain about the state of the limb. Despite an early proof of concept that subjects could learn to discriminate a limited vocabulary of intracortical microstimulation (ICMS) patterns that instruct the subject about the state of the limb, the dynamics of a moving limb are unlikely to be perceived by an arbitrarily-selected, discrete set of static microstimulation patterns, raising questions about the generalization and the scalability of this approach. In this work, we propose a microstimulation protocol intended to activate optimally the ascending somatosensory pathway. The optimization is achieved through a space-time precoder that maximizes the mutual information between the sensory feedback indicating the limb state and the cortical neural response evoked by thalamic microstimulation. Using a simplified multi-input multi-output model of the thalamocortical pathway, we show that this optimal precoder can deliver information more efficiently in the presence of noise compared to suboptimal precoders that do not account for the afferent pathway structure and/or cortical states. These results are expected to enhance the way microstimulation is used to induce somatosensory perception during sensorimotor control of artificial devices or paralyzed limbs.

  10. Non-metallic coating thickness prediction using artificial neural network and support vector machine with time resolved thermography

    Science.gov (United States)

    Wang, Hongjin; Hsieh, Sheng-Jen; Peng, Bo; Zhou, Xunfei

    2016-07-01

    A method without requirements on knowledge about thermal properties of coatings or those of substrates will be interested in the industrial application. Supervised machine learning regressions may provide possible solution to the problem. This paper compares the performances of two regression models (artificial neural networks (ANN) and support vector machines for regression (SVM)) with respect to coating thickness estimations made based on surface temperature increments collected via time resolved thermography. We describe SVM roles in coating thickness prediction. Non-dimensional analyses are conducted to illustrate the effects of coating thicknesses and various factors on surface temperature increments. It's theoretically possible to correlate coating thickness with surface increment. Based on the analyses, the laser power is selected in such a way: during the heating, the temperature increment is high enough to determine the coating thickness variance but low enough to avoid surface melting. Sixty-one pain-coated samples with coating thicknesses varying from 63.5 μm to 571 μm are used to train models. Hyper-parameters of the models are optimized by 10-folder cross validation. Another 28 sets of data are then collected to test the performance of the three methods. The study shows that SVM can provide reliable predictions of unknown data, due to its deterministic characteristics, and it works well when used for a small input data group. The SVM model generates more accurate coating thickness estimates than the ANN model.

  11. Artificial Intelligence and the High School Computer Curriculum.

    Science.gov (United States)

    Dillon, Richard W.

    1993-01-01

    Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

  12. 机器视觉在农业生产中的应用研究%Summary of Research on Machine Vision Application in Agricultural Production

    Institute of Scientific and Technical Information of China (English)

    刁智华; 王会丹; 魏伟

    2014-01-01

    Because of the non-destructive , high accuracy , speed and other advantages , Machine vision technology was widely used in modern agricultural production .Based on the previous research results and analysis of literature , the pro-gress in agricultural product quality grading and testing ,controlling injurious insects and weeds in farmland , agricultural automatic picking system and crop growth process detection and agricultural machine navigation based on machine vision technology were reviewed in this paper .And then they were analyzed and summarized .In the end ,open problems and fur-ther research of machine vision technology in agricultural production application were discussed .%机器视觉技术因其非破坏性、精度高、速度快等特点,在现代农业生产中得到广泛应用。基于前人研究成果和文献分析,综述了近年来机器视觉技术在农产品质量分级与检测、农田病虫草害控制、农业自动采摘系统、农作物生长过程检测以及农业机械导航等方面的国内外研究进展,并对机器视觉技术在各领域的研究情况进行分析和总结,提出了机器视觉技术在农业生产应用中存在的问题和未来的研究方向。

  13. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  14. The Research of Multi Target Tracking Based on Machine Vision%基于机器视觉的多目标跟踪技术的研究

    Institute of Scientific and Technical Information of China (English)

    徐仲勋; 黄科程

    2015-01-01

    Machine vision can help the robot object recognition and operations on objects. In this paper,based on the industrial robot, a machine vision system is added. The system is composed of the robot,camera,image acquisition card,computer and system software. With the robot vision system,features and objects recognition can capture the target object,then the object position,the control of industri⁃al robots to perform tasks.%机器视觉可以帮助机器识别物体并对物体进行作业。本文在工业机器人的设计基础上,增加一个机器视觉系统。系统由机器人、摄像机、图像采集卡、计算机及系统软件所构成。机器人凭着这个视觉系统,可以捕获目标物体的特征并且识别目标物体,然后对物体进行定位,最后控制工业机器人完成作业任务。

  15. Computer vision-based breast self-examination stroke position and palpation pressure level classification using artificial neural networks and wavelet transforms.

    Science.gov (United States)

    Cabatuan, Melvin K; Dadios, Elmer P; Naguib, Raouf N G; Oikonomou, Andreas

    2012-01-01

    This paper focuses on breast self-examination (BSE) stroke position and palpation level classification for the development of a computer vision-based BSE training and guidance system. In this study, image frames are extracted from a BSE video and processed considering the color information, shape, and texture by wavelet transform and first order color moment. The new approach using artificial neural network and wavelet transform can identify BSE stroke positions and palpation levels, i.e. light, medium, and deep, at 97.8 % and 87.5 % accuracy respectively.

  16. Machines versus medication for biventricular heart failure: focus on the total artificial heart.

    Science.gov (United States)

    Arabia, Francisco A; Moriguchi, Jaime D

    2014-09-01

    The medical/surgical management of advanced heart failure has evolved rapidly over the last few decades. With better understanding of heart failure pathophysiology, new pharmacological agents have been introduced that have resulted in improvements in survival. For those patients that fail to improve, mechanical circulatory support with left ventricular assist devices and total artificial hearts (TAHs) have served as a beneficial bridge to transplantation. The TAH has continued to play a significant role as a bridge to transplantation in patients with biventricular failure and more selected indications that could not be completely helped with left ventricular assist devices. Improved survival with the TAH has resulted in more patients benefiting from this technology. Improvements will eventually lead to a totally implantable device that will permanently replace the failing human heart.

  17. A simple numerical model for membrane oxygenation of an artificial lung machine

    Science.gov (United States)

    Subraveti, Sai Nikhil; Sai, P. S. T.; Viswanathan Pillai, Vinod Kumar; Patnaik, B. S. V.

    2015-11-01

    Optimal design of membrane oxygenators will have far reaching ramification in the development of artificial heart-lung systems. In the present CFD study, we simulate the gas exchange between the venous blood and air that passes through the hollow fiber membranes on a benchmark device. The gas exchange between the tube side fluid and the shell side venous liquid is modeled by solving mass, momentum conservation equations. The fiber bundle was modelled as a porous block with a bundle porosity of 0.6. The resistance offered by the fiber bundle was estimated by the standard Ergun correlation. The present numerical simulations are validated against available benchmark data. The effect of bundle porosity, bundle size, Reynolds number, non-Newtonian constitutive relation, upstream velocity distribution etc. on the pressure drop, oxygen saturation levels etc. are investigated. To emulate the features of gas transfer past the alveoli, the effect of pulsatility on the membrane oxygenation is also investigated.

  18. Artificial senses for characterization of food quality

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan-bo; LAN Yu-bin; R.E. Lacey

    2004-01-01

    Food quality is of primary concern in the food industry and to the consumer. Systems that mimic human senses have been developed and applied to the characterization of food quality. The five primary senses are: vision, hearing, smell, taste and touch.In the characterization of food quality, people assess the samples sensorially and differentiate "good" from "bad" on a continuum.However, the human sensory system is subjective, with mental and physical inconsistencies, and needs time to work. Artificial senses such as machine vision, the electronic ear, electronic nose, electronic tongue, artificial mouth and even artificial the head have been developed that mimic the human senses. These artificial senses are coordinated individually or collectively by a pattern recognition technique, typically artificial neural networks, which have been developed based on studies of the mechanism of the human brain. Such a structure has been used to formulate methods for rapid characterization of food quality. This research presents and discusses individual artificial sensing systems. With the concept of multi-sensor data fusion these sensor systems can work collectively in some way. Two such fused systems, artificial mouth and artificial head, are described and discussed. It indicates that each of the individual systems has their own artificially sensing ability to differentiate food samples. It further indicates that with a more complete mimic of human intelligence the fused systems are more powerful than the individual systems in differentiation of food samples.

  19. From geospatial observations of ocean currents to causal predictors of spatio-economic activity using computer vision and machine learning

    Science.gov (United States)

    Popescu, Florin; Ayache, Stephane; Escalera, Sergio; Baró Solé, Xavier; Capponi, Cecile; Panciatici, Patrick; Guyon, Isabelle

    2016-04-01

    The big data transformation currently revolutionizing science and industry forges novel possibilities in multi-modal analysis scarcely imaginable only a decade ago. One of the important economic and industrial problems that stand to benefit from the recent expansion of data availability and computational prowess is the prediction of electricity demand and renewable energy generation. Both are correlates of human activity: spatiotemporal energy consumption patterns in society are a factor of both demand (weather dependent) and supply, which determine cost - a relation expected to strengthen along with increasing renewable energy dependence. One of the main drivers of European weather patterns is the activity of the Atlantic Ocean and in particular its dominant Northern Hemisphere current: the Gulf Stream. We choose this particular current as a test case in part due to larger amount of relevant data and scientific literature available for refinement of analysis techniques. This data richness is due not only to its economic importance but also to its size being clearly visible in radar and infrared satellite imagery, which makes it easier to detect using Computer Vision (CV). The power of CV techniques makes basic analysis thus developed scalable to other smaller and less known, but still influential, currents, which are not just curves on a map, but complex, evolving, moving branching trees in 3D projected onto a 2D image. We investigate means of extracting, from several image modalities (including recently available Copernicus radar and earlier Infrared satellites), a parameterized representation of the state of the Gulf Stream and its environment that is useful as feature space representation in a machine learning context, in this case with the EC's H2020-sponsored 'See.4C' project, in the context of which data scientists may find novel predictors of spatiotemporal energy flow. Although automated extractors of Gulf Stream position exist, they differ in methodology

  20. Parallel Algorithm for GPU Processing; for use in High Speed Machine Vision Sensing of Cotton Lint Trash

    Directory of Open Access Journals (Sweden)

    Mathew G. Pelletier

    2008-02-01

    Full Text Available One of the main hurdles standing in the way of optimal cleaning of cotton lint isthe lack of sensing systems that can react fast enough to provide the control system withreal-time information as to the level of trash contamination of the cotton lint. This researchexamines the use of programmable graphic processing units (GPU as an alternative to thePC’s traditional use of the central processing unit (CPU. The use of the GPU, as analternative computation platform, allowed for the machine vision system to gain asignificant improvement in processing time. By improving the processing time, thisresearch seeks to address the lack of availability of rapid trash sensing systems and thusalleviate a situation in which the current systems view the cotton lint either well before, orafter, the cotton is cleaned. This extended lag/lead time that is currently imposed on thecotton trash cleaning control systems, is what is responsible for system operators utilizing avery large dead-band safety buffer in order to ensure that the cotton lint is not undercleaned.Unfortunately, the utilization of a large dead-band buffer results in the majority ofthe cotton lint being over-cleaned which in turn causes lint fiber-damage as well assignificant losses of the valuable lint due to the excessive use of cleaning machinery. Thisresearch estimates that upwards of a 30% reduction in lint loss could be gained through theuse of a tightly coupled trash sensor to the cleaning machinery control systems. Thisresearch seeks to improve processing times through the development of a new algorithm forcotton trash sensing that allows for implementation on a highly parallel architecture.Additionally, by moving the new parallel algorithm onto an alternative computing platform,the graphic processing unit “GPU”, for processing of the cotton trash images, a speed up ofover 6.5 times, over optimized code running on the PC’s central processing

  1. Machine vision approach to auto-generation of high resolution, continental-scale geomorphometric map from DEM

    Science.gov (United States)

    Jasiewicz, J.; Stepinski, T. F.

    2012-04-01

    Geomorphometric map (GM) is a map of landforms delineated exclusively on the basis of their morphology; it depicts a classification of landscape into its constituent elements. GM is a valuable tool for visual terrain analysis, but more importantly, it's a perfect terrain representation for its further algorithmic analysis. GMs themselves are auto-generated from DEM. We have developed a new technique for auto-generation of GMs that is based on the principle of machine vision. Such approach approximates more closely the mapping process of human analyst and results in an efficient generation of GMs having quality and utility superior to maps generated by a standard technique based on differential geometry. The core of the new technique is a notion of geomorphon. A geomorphon is a relief-invariant, orientation-invariant, and size-flexible abstracted elementary unit of terrain. It is calculated from DEM using simple ternary patterns defined on a neighborhood which size adapts to the character of local terrain. Geomorphons are both terrain attributes and landform types at the same time; they allow for a direct and highly efficient, single-step classification and mapping of landforms. There are 498 unique geomorphons but only a small fraction of them are found in typical natural terrain. The geomorphon-based mapping technique is implemented as a GRASS GIS extension written in ANSI C and will be available in the public domain. In order to showcase the capabilities of geomorphons we have calculated the GM for the entire conterminous United States from the 30m/pixel NED DEM. The map shows ten most abundant landforms: flat, peak, ridge, shoulder, spur, slope, hollow, footslope, valley, and pit; a lookup table was used to assign each of the remaining 488 infrequent forms to a morphologically closest mapped form. The result is a unique, never before seen, type of map that clearly shows multiple geomorphic features and indicates the underlying geologic processes. The auto

  2. 基于机器视觉技术的无精蛋鉴别研究%Identification of Wind Egg Based on Machine Vision Technology

    Institute of Scientific and Technical Information of China (English)

    李天华; 李海亮

    2011-01-01

    [Objectives] To identify the wind egg by machine vision technology so as to improve the accuracy and rapidness of removing the wind eggs during the incubation process. [ Method] The images of hatching eggs were firstly acquired by CCD camera, and then imported into the computer to analyze it gray scale and detect the hatching eggs, the computer transmitted the signals to the core controller, which controlled the sense station to screen out the wind eggs. [ Result ] The wind eggs could be rapidly and accurately removed after 6-day hatching by using the machine vision technology. [Conclusion] The identification of wind egg by machine vision technology had high theoretical and practical significance.%[目的]采用机器视觉技术鉴别无精蛋,提高孵化生产过程中剔除无精蛋的准确率和速度.[方法]首先用CCD照相机获取入孵蛋图像,再将入孵蛋图像传输到计算机主机,主机测控软件对图像进行灰度特征分析、比较等,对入孵蛋进行检测,主机输出信号给核心控制器,由核心控制器控制检测台对无精蛋进行分选.[结果]采用机器视觉技术可以在入孵后第6天快速准确地剔除无精蛋.[结论]利用机器视觉检测技术鉴别无精蛋,具有较高的理论价值和实际生产意义.

  3. Socket Quality Detection Based on Machine Vision%基于机器视觉的插座品质检测方法

    Institute of Scientific and Technical Information of China (English)

    徐德明; 汪成龙

    2016-01-01

    针对目前人工成本上升,人眼易出现视觉疲劳导致检测效率低下等问题,本文提出了一种基于机器视觉的插座品质检测方法.主要研究内容如下:1)研究了基于模板匹配的插座机器视觉定位方法.2)研究了基于灰度均值的螺丝缺陷机器视觉检测方法.3)研究了基于灰度标准偏差的插孔缺陷机器视觉检测方法.根据以上检测方法,编写了检测软件,在生产线上进行测试,对插座螺丝和插孔缺陷的识别率达到100%,平均每帧图像处理仅耗时100ms,表明该方法具有准确率高、速度快的优点.%For the current rising labor costs and low detection efficiency of eye fatigue, this paper presents a method for detecting socket quality based on machine vision. The main research contents are as follows: 1) Socket positioning method based on template matching with machine vision. 2) The machine vision detection method for screws defects based on the mean of gray value. 3) The detection method of jack defect based on grayscale standard deviation. In the production line testing, screws and jack defect recognition rate have reached 100%. And the average per-frame image processing only takes 100ms, which shows that this method has high accuracy, fast speed advantages.

  4. 新型人造花岗石中走丝电火花线切割机%New artificial granite machine for WEDM

    Institute of Scientific and Technical Information of China (English)

    蒋文英; 汪珉; 杨超翔

    2015-01-01

    为了满足精度机械发展需要,进一步提高线切割机的精密度,用人造花岗石来取代铸铁,用智能控制高频电源取代传统高频电源,开发了一种新型人造花岗石中走丝电火花线切割机。所研制的人造花岗石线切割机的性能特点和实际效果说明,该电火花线切割机不仅有助于提高线切割机质量、满足精度加工需要,而且还会有很高的经济效益和社会效益。%In order to develop the high precision machinery and improve the cutting preci‐sion ,the author used the artificial granite to replace the cast iron and used intelligent‐controlled high frequency power supply to replace the traditional high frequency power sup‐ply ,and developed a new type of artificial granite machine for WEDM .The actual performance shows that the new artificial granite machine can improve the quality of the WEDM machine ,sat‐isfy the machining precision and provide high economic and social benefit .

  5. Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR Spectrophotometer

    Science.gov (United States)

    Gutiérrez, Salvador; Tardaguila, Javier; Fernández-Novales, Juan; Diago, María P.

    2015-01-01

    The identification of different grapevine varieties, currently attended using visual ampelometry, DNA analysis and very recently, by hyperspectral analysis under laboratory conditions, is an issue of great importance in the wine industry. This work presents support vector machine and artificial neural network’s modelling for grapevine varietal classification from in-field leaf spectroscopy. Modelling was attempted at two scales: site-specific and a global scale. Spectral measurements were obtained on the near-infrared (NIR) spectral range between 1600 to 2400 nm under field conditions in a non-destructive way using a portable spectrophotometer. For the site specific approach, spectra were collected from the adaxial side of 400 individual leaves of 20 grapevine (Vitis vinifera L.) varieties one week after veraison. For the global model, two additional sets of spectra were collected one week before harvest from two different vineyards in another vintage, each one consisting on 48 measurement from individual leaves of six varieties. Several combinations of spectra scatter correction and smoothing filtering were studied. For the training of the models, support vector machines and artificial neural networks were employed using the pre-processed spectra as input and the varieties as the classes of the models. The results from the pre-processing study showed that there was no influence whether using scatter correction or not. Also, a second-degree derivative with a window size of 5 Savitzky-Golay filtering yielded the highest outcomes. For the site-specific model, with 20 classes, the best results from the classifiers thrown an overall score of 87.25% of correctly classified samples. These results were compared under the same conditions with a model trained using partial least squares discriminant analysis, which showed a worse performance in every case. For the global model, a 6-class dataset involving samples from three different vineyards, two years and leaves

  6. Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR Spectrophotometer.

    Directory of Open Access Journals (Sweden)

    Salvador Gutiérrez

    Full Text Available The identification of different grapevine varieties, currently attended using visual ampelometry, DNA analysis and very recently, by hyperspectral analysis under laboratory conditions, is an issue of great importance in the wine industry. This work presents support vector machine and artificial neural network's modelling for grapevine varietal classification from in-field leaf spectroscopy. Modelling was attempted at two scales: site-specific and a global scale. Spectral measurements were obtained on the near-infrared (NIR spectral range between 1600 to 2400 nm under field conditions in a non-destructive way using a portable spectrophotometer. For the site specific approach, spectra were collected from the adaxial side of 400 individual leaves of 20 grapevine (Vitis vinifera L. varieties one week after veraison. For the global model, two additional sets of spectra were collected one week before harvest from two different vineyards in another vintage, each one consisting on 48 measurement from individual leaves of six varieties. Several combinations of spectra scatter correction and smoothing filtering were studied. For the training of the models, support vector machines and artificial neural networks were employed using the pre-processed spectra as input and the varieties as the classes of the models. The results from the pre-processing study showed that there was no influence whether using scatter correction or not. Also, a second-degree derivative with a window size of 5 Savitzky-Golay filtering yielded the highest outcomes. For the site-specific model, with 20 classes, the best results from the classifiers thrown an overall score of 87.25% of correctly classified samples. These results were compared under the same conditions with a model trained using partial least squares discriminant analysis, which showed a worse performance in every case. For the global model, a 6-class dataset involving samples from three different vineyards, two years

  7. A computational proof of concept of a machine-intelligent artificial pancreas using Lyapunov stability and differential game theory.

    Science.gov (United States)

    Greenwood, Nigel J C; Gunton, Jenny E

    2014-07-01

    This study demonstrated the novel application of a "machine-intelligent" mathematical structure, combining differential game theory and Lyapunov-based control theory, to the artificial pancreas to handle dynamic uncertainties. Realistic type 1 diabetes (T1D) models from the literature were combined into a composite system. Using a mixture of "black box" simulations and actual data from diabetic medical histories, realistic sets of diabetic time series were constructed for blood glucose (BG), interstitial fluid glucose, infused insulin, meal estimates, and sometimes plasma insulin assays. The problem of underdetermined parameters was side stepped by applying a variant of a genetic algorithm to partial information, whereby multiple candidate-personalized models were constructed and then rigorously tested using further data. These formed a "dynamic envelope" of trajectories in state space, where each trajectory was generated by a hypothesis on the hidden T1D system dynamics. This dynamic envelope was then culled to a reduced form to cover observed dynamic behavior. A machine-intelligent autonomous algorithm then implemented game theory to construct real-time insulin infusion strategies, based on the flow of these trajectories through state space and their interactions with hypoglycemic or near-hyperglycemic states. This technique was tested on 2 simulated participants over a total of fifty-five 24-hour days, with no hypoglycemic or hyperglycemic events, despite significant uncertainties from using actual diabetic meal histories with 10-minute warnings. In the main case studies, BG was steered within the desired target set for 99.8% of a 16-hour daily assessment period. Tests confirmed algorithm robustness for ±25% carbohydrate error. For over 99% of the overall 55-day simulation period, either formal controller stability was achieved to the desired target or else the trajectory was within the desired target. These results suggest that this is a stable, high

  8. Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

    Science.gov (United States)

    Ahmadi, Hamed; Rodehutscord, Markus

    2017-01-01

    In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [R(2) = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM (R(2) = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR (R(2) = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel(®) calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

  9. Research on Three-dimensional Motion History Image Model and Extreme Learning Machine for Human Body Movement Trajectory Recognition

    OpenAIRE

    Zheng Chang; Xiaojuan Ban; Qing Shen; Jing Guo

    2015-01-01

    Based on the traditional machine vision recognition technology and traditional artificial neural networks about body movement trajectory, this paper finds out the shortcomings of the traditional recognition technology. By combining the invariant moments of the three-dimensional motion history image (computed as the eigenvector of body movements) and the extreme learning machine (constructed as the classification artificial neural network of body movements), the paper applies the method to the...

  10. Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence.

    Science.gov (United States)

    Aoun, Bachir

    2016-05-01

    A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group.

  11. CYCLOPS: A mobile robotic platform for testing and validating image processing and autonomous navigation algorithms in support of artificial vision prostheses.

    Science.gov (United States)

    Fink, Wolfgang; Tarbell, Mark A

    2009-12-01

    While artificial vision prostheses are quickly becoming a reality, actual testing time with visual prosthesis carriers is at a premium. Moreover, it is helpful to have a more realistic functional approximation of a blind subject. Instead of a normal subject with a healthy retina looking at a low-resolution (pixelated) image on a computer monitor or head-mounted display, a more realistic approximation is achieved by employing a subject-independent mobile robotic platform that uses a pixelated view as its sole visual input for navigation purposes. We introduce CYCLOPS: an AWD, remote controllable, mobile robotic platform that serves as a testbed for real-time image processing and autonomous navigation systems for the purpose of enhancing the visual experience afforded by visual prosthesis carriers. Complete with wireless Internet connectivity and a fully articulated digital camera with wireless video link, CYCLOPS supports both interactive tele-commanding via joystick, and autonomous self-commanding. Due to its onboard computing capabilities and extended battery life, CYCLOPS can perform complex and numerically intensive calculations, such as image processing and autonomous navigation algorithms, in addition to interfacing to additional sensors. Its Internet connectivity renders CYCLOPS a worldwide accessible testbed for researchers in the field of artificial vision systems. CYCLOPS enables subject-independent evaluation and validation of image processing and autonomous navigation systems with respect to the utility and efficiency of supporting and enhancing visual prostheses, while potentially reducing to a necessary minimum the need for valuable testing time with actual visual prosthesis carriers.

  12. The potential of computer vision, optical backscattering parameters and artificial neural network modelling in monitoring the shrinkage of sweet potato (Ipomoea batatas L.) during drying.

    Science.gov (United States)

    Onwude, Daniel I; Hashim, Norhashila; Abdan, Khalina; Janius, Rimfiel; Chen, Guangnan

    2017-07-30

    Drying is a method used to preserve agricultural crops. During the drying of products with high moisture content, structural changes in shape, volume, area, density and porosity occur. These changes could affect the final quality of dried product and also the effective design of drying equipment. Therefore, this study investigated a novel approach in monitoring and predicting the shrinkage of sweet potato during drying. Drying experiments were conducted at temperatures of 50-70 °C and samples thicknesses of 2-6 mm. The volume and surface area obtained from camera vision, and the perimeter and illuminated area from backscattered optical images were analysed and used to evaluate the shrinkage of sweet potato during drying. The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95. Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  13. An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs.

    Science.gov (United States)

    Ortiz-Catalan, Max; Håkansson, Bo; Brånemark, Rickard

    2014-10-08

    A major challenge since the invention of implantable devices has been a reliable and long-term stable transcutaneous communication. In the case of prosthetic limbs, existing neuromuscular interfaces have been unable to address this challenge and provide direct and intuitive neural control. Although prosthetic hardware and decoding algorithms are readily available, there is still a lack of appropriate and stable physiological signals for controlling the devices. We developed a percutaneous osseointegrated (bone-anchored) interface that allows for permanent and unlimited bidirectional communication with the human body. With this interface, an artificial limb can be chronically driven by implanted electrodes in the peripheral nerves and muscles of an amputee, outside of controlled environments and during activities of daily living, thus reducing disability and improving quality of life. We demonstrate in one subject, for more than 1 year, that implanted electrodes provide a more precise and reliable control than surface electrodes, regardless of limb position and environmental conditions, and with less effort. Furthermore, long-term stable myoelectric pattern recognition and appropriate sensory feedback elicited via neurostimulation was demonstrated. The opportunity to chronically record and stimulate the neuromuscular system allows for the implementation of intuitive control and naturally perceived sensory feedback, as well as opportunities for the prediction of complex limb motions and better understanding of sensory perception. The permanent bidirectional interface presented here is a critical step toward more natural limb replacement, by combining stable attachment with permanent and reliable human-machine communication.

  14. Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Because of the excellent performance on monitoring and controlling an autocorrelated process, the integration of statistical process control (SPC and engineering process control (EPC has drawn considerable attention in recent years. Both theoretical and empirical findings have suggested that the integration of SPC and EPC can be an effective way to improve the quality of a process, especially when the underlying process is autocorrelated. However, because EPC compensates for the effects of underlying disturbances, the disturbance patterns are embedded and hard to be recognized. Effective recognition of disturbance patterns is a very important issue for process improvement since disturbance patterns would be associated with certain assignable causes which affect the process. In practical situations, after compensating by EPC, the underlying disturbance patterns could be of any mixture types which are totally different from the original patterns. This study proposes the integration of support vector machine (SVM and artificial neural network (ANN approaches to recognize the disturbance patterns of the underlying disturbances. Experimental results revealed that the proposed schemes are able to effectively recognize various disturbance patterns of an SPC/EPC system.

  15. 一种基于机器视觉的跑偏角估计算法%An algorithm of machine vision-based yaw-angle estimation

    Institute of Scientific and Technical Information of China (English)

    魏丽; 田克纯

    2011-01-01

    在移动机器人、汽车等自主行进过程中,由于受到道路情况等因素的影响,极易出现方向跑偏,导致其无法按照预定路径前进.为了防止出现跑偏等危险情况,研究了利用机器视觉估计预定运动方向和实际运动方向夹角即跑偏角的方法.介绍了利用机器视觉测量跑偏角的基本原理;研究了基于特征点跟踪的跑偏角估计算法.实验研究表明:该方法可以有效地在行进过程中计算跑偏角.%In the process of robot and automobile autonomous moving, vehicle cannot move along predestinate path due to road status and other factors. An algorithm of machine vision-based yaw angle computation for avoiding vehicle in danger is presented. The system constitutes of machine vision-based yaw angle computation is introduced. Algorithm of yaw angle computation which is built on feature points tracking is studied. Experimental results show that this method can compute yaw-angle in the process of vehicle moving effectively.

  16. Gradual Reduction in Sodium Content in Cooked Ham, with Corresponding Change in Sensorial Properties Measured by Sensory Evaluation and a Multimodal Machine Vision System.

    Science.gov (United States)

    Greiff, Kirsti; Mathiassen, John Reidar; Misimi, Ekrem; Hersleth, Margrethe; Aursand, Ida G

    2015-01-01

    The European diet today generally contains too much sodium (Na(+)). A partial substitution of NaCl by KCl has shown to be a promising method for reducing sodium content. The aim of this work was to investigate the sensorial changes of cooked ham with reduced sodium content. Traditional sensorial evaluation and objective multimodal machine vision were used. The salt content in the hams was decreased from 3.4% to 1.4%, and 25% of the Na(+) was replaced by K(+). The salt reduction had highest influence on the sensory attributes salty taste, after taste, tenderness, hardness and color hue. The multimodal machine vision system showed changes in lightness, as a function of reduced salt content. Compared to the reference ham (3.4% salt), a replacement of Na(+)-ions by K(+)-ions of 25% gave no significant changes in WHC, moisture, pH, expressed moisture, the sensory profile attributes or the surface lightness and shininess. A further reduction of salt down to 1.7-1.4% salt, led to a decrease in WHC and an increase in expressible moisture.

  17. Gradual Reduction in Sodium Content in Cooked Ham, with Corresponding Change in Sensorial Properties Measured by Sensory Evaluation and a Multimodal Machine Vision System

    Science.gov (United States)

    Greiff, Kirsti; Mathiassen, John Reidar; Misimi, Ekrem; Hersleth, Margrethe; Aursand, Ida G.

    2015-01-01

    The European diet today generally contains too much sodium (Na+). A partial substitution of NaCl by KCl has shown to be a promising method for reducing sodium content. The aim of this work was to investigate the sensorial changes of cooked ham with reduced sodium content. Traditional sensorial evaluation and objective multimodal machine vision were used. The salt content in the hams was decreased from 3.4% to 1.4%, and 25% of the Na+ was replaced by K+. The salt reduction had highest influence on the sensory attributes salty taste, after taste, tenderness, hardness and color hue. The multimodal machine vision system showed changes in lightness, as a function of reduced salt content. Compared to the reference ham (3.4% salt), a replacement of Na+-ions by K+-ions of 25% gave no significant changes in WHC, moisture, pH, expressed moisture, the sensory profile attributes or the surface lightness and shininess. A further reduction of salt down to 1.7–1.4% salt, led to a decrease in WHC and an increase in expressible moisture. PMID:26422367

  18. 机械制造自动化的机器视觉技术应用%Machinery Manufacturing Automation Application of Machine Vision Technique

    Institute of Scientific and Technical Information of China (English)

    支月蓉

    2015-01-01

    In machinery manufacturing industry,video technology and infrared imaging technology have been widely applied. The machine vision technology is a technology which uses computer technology to simulate visual system of human beings and to interpret images instead of supervisor.Depending on its advantages such as quick processing speed,large information processing, full functions and so on,machine vision technology gets developed along with the process of facilitating automation level.%在机械制造行业,视频技术和红外成像技术得到了广泛的应用.机器视觉技术是由计算机技术来模拟人的视觉系统,代替原有的监控人员进行图像理解.凭借其运行速度较快,信息处理量大,以及功能齐全等诸多优点,机器视觉技术在推动自动化水平前进的同时自身也得到了良好的发展.

  19. Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Cédric Beaulac

    2017-01-01

    Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.

  20. Comparing artificial neural networks, general linear models and support vector machines in building predictive models for small interfering RNAs.

    Directory of Open Access Journals (Sweden)

    Kyle A McQuisten

    Full Text Available BACKGROUND: Exogenous short interfering RNAs (siRNAs induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models. PRINCIPAL FINDINGS: Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs, General Linear Models (GLMs and Support Vector Machines (SVMs. Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation. CONCLUSIONS: The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features

  1. Development of an artificial vision system for the automatic evaluation of the cutting angles of worn tools

    Directory of Open Access Journals (Sweden)

    Gianni Campatelli

    2016-03-01

    Full Text Available This article presents a new method to evaluate the geometry of dull cutting tools in order to verify the necessity of tool re-sharpening and to decrease the tool grinding machine setup time, based on a laser scanning approach. The developed method consists of the definition of a system architecture and the programming of all the algorithms needed to analyze the data and provide, as output, the cutting angles of the worn tool. These angles are usually difficult to be measured and are needed to set up the grinding machine. The main challenges that have been dealt with in this application are related to the treatment of data acquired by the system’s cameras, which must be specific for the milling tools, usually characterized by the presence of undercuts and sharp edges. Starting from the architecture of the system, an industrial product has been designed, with the support of a grinding machine manufacturer. The basic idea has been to develop a low-cost system that could be integrated on a tool sharpening machine and interfaced with its numeric control. The article reports the developed algorithms and an example of application.

  2. Artificial intelligence: Principles and applications

    Energy Technology Data Exchange (ETDEWEB)

    Yazdani, M.

    1986-01-01

    Following the Japanese announcement that they intend to devise, make, and market, in the 1990s, computers incorporating a level of intelligence, a vast amount of energy and expense has been diverted at the field of Artificial Intelligence. Workers for the past 25 years in this discipline have tried to reproduce human behavior on computers and this book presents their achievements and the problems. Subjects include: computer vision, speech processing, robotics, natural language processing expert systems and machine learning. The book also attempts to show the general principles behind the various applications and finally attempts to show their implications for other human endeavors such as philosophy, psychology, and the development of modern society.

  3. Analysis on Application and Research Progress of Machine Vision in Agriculture in China%机器视觉在我国农业中的应用研究进展分析

    Institute of Scientific and Technical Information of China (English)

    王风云; 郑纪业; 唐研; 刘延忠; 李乔宇; 穆元杰; 王磊

    2016-01-01

    随着图像处理、模式识别、人工智能等技术的不断发展,机器视觉技术在我国农业上的研究逐步深入,并取得了许多重要成果。本文基于中国知网全文数据库检索系统,对我国基于机器视觉的农业研究进行了博、硕士学位论文与期刊论文的统计、分析。结果显示,我国农业机器视觉研究主要涉及检测、图像处理、轨迹跟踪与车辆导航、模式识别及其应用等主题,主要集中在图像信息获取方法、图像处理与识别算法、智能导航算法以及系统集成应用等方面,以《农机化研究》、《农业工程学报》和《农业机械学报》为主要发表刊物,主要受国家自然科学基金、国家高技术研究发展计划(“863”计划)、国家科技支撑计划、省科技攻关计划、省自然科学基金等项目支持,国内研究机构以中国农业大学、南京农业大学、浙江大学、华南农业大学、山西农业大学和江苏大学为主。但目前我国基于机器视觉的农业研究在作物生长信息检测、杂草识别、变量控制、机械智能导航、采摘与分选等方面离实用化、商品化仍有一定的距离,集成符合我国农业发展实际的机器视觉技术系统将是今后重要的研究方向。本研究为机器视觉在我国农业上的进一步应用研究提供了参考。%The research on machine vision technology in agriculture in China is gradually deepened with the development of image processing,pattern recognition and artificial intelligence technologies.Many a-chievements have been obtained.Based on the full -text database retrieval system of CNKI (China National Knowledge Infrastructure),the statistical analysis is carried out on dissertations and journal articles to study the research progress of machine version in agriculture.It was summarized that the main research topics in-cluded vision measuring,image processing,trajectory tracking

  4. 基于机器视觉维氏硬度检测技术研究%Research on Technigues of Vickers Hardness Test Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    韦喆; 张绍荣

    2015-01-01

    Vickers hardness test has advantages of high precision and wide application. But it has great manual operation error and limitation. The Vickers hardness test platform is set up base on machine vision method in this paper. Through acquiring and processing the images in dentation, hardness value is obtained by calculating. Its feasibility is verified through experiment.%维氏硬度测试是一种精度高、应用范围广的硬度测量方法,但人工操作测量误差高、局限性大。本研究基于机器视觉的方法,搭建维氏硬度测试平台,通过采集压痕图像并对其进行处理、运算得出被测物硬度值。实验验证了其可行性。

  5. Real-time drogue recognition and 3D locating for UAV autonomous aerial refueling based on monocular machine vision

    Institute of Scientific and Technical Information of China (English)

    Wang Xufeng; Kong Xingwei; Zhi Jianhui; Chen Yong; Dong Xinmin

    2015-01-01

    Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling (AAR). To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi-tions, without using a set of infrared light emitting diodes (LEDs) on the parachute part of the dro-gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective-ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.

  6. Vision Alignment System of Solar Cell Screen Printing Machine%太阳能硅片丝印机视觉定位系统

    Institute of Scientific and Technical Information of China (English)

    魏海滨; 朱跃红; 郎鹏; 郑海红; 张素枝

    2012-01-01

    Solar Cell Screen Printing Machine is the key equipment in solar cell production industry. How to improve the precision, quality and efficiency of screen printing is very important, the alignment is one of the key technologies. Introduce the typical application of precision alighnment based on computer vision in the solar cell screen printing, and illustrate the basic components, design principle and hardware selection of vision precision alignment system, give out the motional relationship between CCD optical system and UVWworktable and the alionment orocess.%太阳能硅片丝印机是太阳能电池生产行业中的关键设备,如何提高丝印精度、印刷质量和印刷效率成为研究重点,而对位技术则是其中的关键技术之一。介绍了基于机器视觉的精密对位技术在太阳能硅片丝印机中的典型应用,阐述了视觉精密定位系统的基本组成、设计原理及硬件选型,给出了CCD光学系统与UVW工作平台坐标系之间的各运动关系和对位过程。

  7. High-speed Robot Auto-sorting System Based on Machine Vision%高速机器人分拣系统机器视觉技术的研究

    Institute of Scientific and Technical Information of China (English)

    晏祖根; 李明; 徐克非; 孙小华; 闫志鹏; 孙智慧

    2014-01-01

    针对我国食品生产行业的实际需求,基于并联机器人、机器视觉等先进技术,构建了面向食品生产包装的高速机器人分拣系统,研究了输送带上运动食品的机器视觉定位算法,设计了运动食品分级与定位的机器视觉硬件系统,基于专业图像处理软件Sherlock,研发了自动分拣机器视觉软件系统,以提高我国食品生产效率、保证食品卫生、降低劳动强度。%In view of the actual demand of the food industry in China,the high-speed parallel robot auto-sorting system is constructed.The machine vision positioning algorithm of the moving food on the conveyor belt is studied.The machine vision hardware system for food sorting and positioning is designed.Based on second-ary development for Sherlock in VC programming environment,the machine vision software system is devel-oped.By applied the machine vision system,it can improve the production efficiency and reduce the labor’s intensity in our food and packaging industry.

  8. When Machines Design Machines!

    DEFF Research Database (Denmark)

    2011-01-01

    Until recently we were the sole designers, alone in the driving seat making all the decisions. But, we have created a world of complexity way beyond human ability to understand, control, and govern. Machines now do more trades than humans on stock markets, they control our power, water, gas...... and food supplies, manage our elevators, microclimates, automobiles and transport systems, and manufacture almost everything. It should come as no surprise that machines are now designing machines. The chips that power our computers and mobile phones, the robots and commercial processing plants on which we...... depend, all are now largely designed by machines. So what of us - will be totally usurped, or are we looking at a new symbiosis with human and artificial intelligences combined to realise the best outcomes possible. In most respects we have no choice! Human abilities alone cannot solve any of the major...

  9. Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

    Science.gov (United States)

    Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

    2013-10-01

    Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the

  10. Evolving detectors of 2D patterns on a simulated CAM-Brain machine: an evolvable hardware tool for building a 75-million-neuron artificial brain

    Science.gov (United States)

    de Garis, Hugo; Korkin, Michael; Guttikonda, Padma; Cooley, Donald

    2000-11-01

    This paper presents some simulation results of the evolution of 2D visual pattern recognizers to be implemented very shortly on real hardware, namely the 'CAM-Brain Machine' (CBM), an FPGA based piece of evolvable hardware which implements a genetic algorithm (GA) to evolve a 3D cellular automata (CA) based neural network circuit module, of approximately 1,000 neurons, in about a second, i.e. a complete run of a GA, with 10,000s of circuit growths and performance evaluations. Up to 65,000 of these modules, each of which is evolved with a humanly specified function, can be downloaded into a large RAM space, and interconnected according to humanly specified gvdvips -o SPIE-2000.ps SPIE-2000 artificial brain architectures. This RAM, containing an artificial brain with up to 75 million neurons, is then updated by the CBM at a rate of 130 billion CA cells per second. Such speeds will enable real time control of robots and hopefully the birth of a new research field that we call 'brain building.' The first such artificial brain, to be built at STARLAB in 2000 and beyond, will be used to control the behaviors of a life sized kitten robot called 'Robokitty.' This kitten robot will need 2D pattern recognizers in the visual section of its artificial brain. This paper presents simulation results on the evolvability and generalization properties of such recognizers.

  11. Development of a Committee of Artificial Neural Networks for the Performance Testing of Compressors for Thermal Machines in Very Reduced Times

    Directory of Open Access Journals (Sweden)

    Coral Rodrigo

    2015-03-01

    Full Text Available This paper presents a new test method able to infer - in periods of less than 7 seconds - the refrigeration capacity of a compressor used in thermal machines, which represents a time reduction of approximately 99.95% related to the standardized traditional methods. The method was developed aiming at its application on compressor manufacture lines and on 100% of the units produced. Artificial neural networks (ANNs were used to establish a model able to infer the refrigeration capacity based on the data collected directly on the production line. The proposed method does not make use of refrigeration systems and also does not require using the compressor oil.

  12. Simulation of the «COSMONAUT-ROBOT» System Interaction on the Lunar Surface Based on Methods of Machine Vision and Computer Graphics

    Science.gov (United States)

    Kryuchkov, B. I.; Usov, V. M.; Chertopolokhov, V. A.; Ronzhin, A. L.; Karpov, A. A.

    2017-05-01

    Extravehicular activity (EVA) on the lunar surface, necessary for the future exploration of the Moon, involves extensive use of robots. One of the factors of safe EVA is a proper interaction between cosmonauts and robots in extreme environments. This requires a simple and natural man-machine interface, e.g. multimodal contactless interface based on recognition of gestures and cosmonaut's poses. When travelling in the "Follow Me" mode (master/slave), a robot uses onboard tools for tracking cosmonaut's position and movements, and on the basis of these data builds its itinerary. The interaction in the system "cosmonaut-robot" on the lunar surface is significantly different from that on the Earth surface. For example, a man, dressed in a space suit, has limited fine motor skills. In addition, EVA is quite tiring for the cosmonauts, and a tired human being less accurately performs movements and often makes mistakes. All this leads to new requirements for the convenient use of the man-machine interface designed for EVA. To improve the reliability and stability of human-robot communication it is necessary to provide options for duplicating commands at the task stages and gesture recognition. New tools and techniques for space missions must be examined at the first stage of works in laboratory conditions, and then in field tests (proof tests at the site of application). The article analyzes the methods of detection and tracking of movements and gesture recognition of the cosmonaut during EVA, which can be used for the design of human-machine interface. A scenario for testing these methods by constructing a virtual environment simulating EVA on the lunar surface is proposed. Simulation involves environment visualization and modeling of the use of the "vision" of the robot to track a moving cosmonaut dressed in a spacesuit.

  13. Vision and Motion Pictures.

    Science.gov (United States)

    Grambo, Gregory

    1998-01-01

    Presents activities on persistence of vision that involve students in a hands-on approach to the study of early methods of creating motion pictures. Students construct flip books, a Zoetrope, and an early movie machine. (DDR)

  14. New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method

    Science.gov (United States)

    Mofavvaz, Shirin; Sohrabi, Mahmoud Reza; Nezamzadeh-Ejhieh, Alireza

    2017-07-01

    In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM) as intelligent methods based on absorption spectra in the range of 230-300 nm have been used for determination of antihistamine decongestant contents. In the first step, one type of network (feed-forward back-propagation) from the artificial neural network with two different training algorithms, Levenberg-Marquardt (LM) and gradient descent with momentum and adaptive learning rate back-propagation (GDX) algorithm, were employed and their performance was evaluated. The performance of the LM algorithm was better than the GDX algorithm. In the second one, the radial basis network was utilized and results compared with the previous network. In the last one, the other intelligent method named least squares support vector machine was proposed to construct the antihistamine decongestant prediction model and the results were compared with two of the aforementioned networks. The values of the statistical parameters mean square error (MSE), Regression coefficient (R2), correlation coefficient (r) and also mean recovery (%), relative standard deviation (RSD) used for selecting the best model between these methods. Moreover, the proposed methods were compared to the high- performance liquid chromatography (HPLC) as a reference method. One way analysis of variance (ANOVA) test at the 95% confidence level applied to the comparison results of suggested and reference methods that there were no significant differences between them.

  15. How do we think machines think? An fMRI study of alleged competition with an artificial intelligence

    Directory of Open Access Journals (Sweden)

    Thierry eChaminade

    2012-05-01

    Full Text Available Humans are particularly skilled in mentalizing, the inference of other agents’ hidden mental states. Here we question whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by investigating brain responses during the interaction with an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing the opponent was a fellow human (Intentional agent, a humanoid robot endowed with an algorithm developed to win the game (Artificial agent, or a laptop playing randomly (Random agent. Subjective reports indicated that participants perceived differences between the three opponents. No brain area responded specifically to interaction with the robot, suggesting the absence of reproducible stance when interacting with an artificial agent. We probed response to the artificial agent in clusters activated during the interaction with the intentional agent. A highly significant increase from robot to human in all clusters, including the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, supports the intrinsically engaging nature of social interactions. Mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting that humans do not adopt an intentional stance when interacting with an artificial agent. In contrast, left premotor cortex and anterior intraparietal sulcus involved in motor resonance were activated when interacting with the intentional and artificial agent, suggesting that participants also simulated the embodied humanoid robot’s actions in the game. Results support the specificity of mentalizing areas for interactions with intentional agents, while motor resonance generalizes to interactions with

  16. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-01-01

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play. PMID:26343664

  17. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques.

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-08-28

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower(®), firstly guides the user to appropriately take an inflorescence photo using the smartphone's camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower(®) has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application's efficiency on four different devices covering a wide range of the market's spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  18. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    Directory of Open Access Journals (Sweden)

    Arturo Aquino

    2015-08-01

    Full Text Available Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  19. Thread Recognition System Based on Machine Vision Technology%基于机器视觉技术的螺纹识别系统

    Institute of Scientific and Technical Information of China (English)

    景敏

    2013-01-01

    Thread angle identification is a common method to distinguish thread types. Traditional detection methods have many disadvantages such as low efficiency and high cost and gauges are easy to be abraded. The needs of high efficient development of modern industry are not met any more. CCD is used to obtain the basic im-age of thread. And the thread contour is analyzed through image smoothness, edge detection, binary image pro-duction and contour hunting. The thread angle parameters are measured and identified. The measurement meth-ods of thread angle parameter using machine vision are discussed. And a thread recognition system mainly based on the machine vision recognition technology and integrated visual sensing with image processing system is de-signed. The feasibility and correctness of the method is proved from theory and practice.%螺纹牙型角识别是区分螺纹种类的常用手段,传统检测手段效率低、量规易磨损、成本高,已不能满足现代工业高效发展的需求。利用CCD获取螺纹基本图像,并通过图像的平滑、边缘检测、二值化处理及轮廓提取,对螺纹轮廓进行分析,从中测量出螺纹的牙型角参数并进行识别。探讨了利用机器视觉对螺纹牙型角参数进行测量的方法,并设计出一套以机器视觉识别技术为核心的视觉传感和图像处理系统为一体的螺纹识别系统。从理论和实践上证实了该方法的可行性和准确性。

  20. Early vision and focal attention

    Science.gov (United States)

    Julesz, Bela

    1991-07-01

    At the thirty-year anniversary of the introduction of the technique of computer-generated random-dot stereograms and random-dot cinematograms into psychology, the impact of the technique on brain research and on the study of artificial intelligence is reviewed. The main finding-that stereoscopic depth perception (stereopsis), motion perception, and preattentive texture discrimination are basically bottom-up processes, which occur without the help of the top-down processes of cognition and semantic memory-greatly simplifies the study of these processes of early vision and permits the linking of human perception with monkey neurophysiology. Particularly interesting are the unexpected findings that stereopsis (assumed to be local) is a global process, while texture discrimination (assumed to be a global process, governed by statistics) is local, based on some conspicuous local features (textons). It is shown that the top-down process of "shape (depth) from shading" does not affect stereopsis, and some of the models of machine vision are evaluated. The asymmetry effect of human texture discrimination is discussed, together with recent nonlinear spatial filter models and a novel extension of the texton theory that can cope with the asymmetry problem. This didactic review attempts to introduce the physicist to the field of psychobiology and its problems-including metascientific problems of brain research, problems of scientific creativity, the state of artificial intelligence research (including connectionist neural networks) aimed at modeling brain activity, and the fundamental role of focal attention in mental events.

  1. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  2. Quantitative structure-property relationships of electroluminescent materials: Artificial neural networks and support vector machines to predict electroluminescence of organic molecules

    Indian Academy of Sciences (India)

    Alana Fernandes Golin; Ricardo Stefani

    2013-12-01

    Electroluminescent compounds are extensively used as materials for application in OLED. In order to understand the chemical features related to electroluminescence of such compounds, QSPR study based on neural network model and support vector machine was developed on a series of organic compounds commonly used in OLED development. Radial-basis function-SVM model was able to predict the electroluminescence with good accuracy ( = 0.90). Moreover, RMSE of support vector machine model is approximately half of RMSE observed for artificial neural networks model, which is significant from the point of view of model precision, as the dataset is very small. Thus, support vector machine is a good method to build QSPR models to predict the electroluminescence of materials when applied to small datasets. It was observed that descriptors related to chemical bonding and electronic structure are highly correlated with electroluminescence properties. The obtained results can help in understating the structural features related to the electroluminescence, and supporting the development of new electroluminescent materials.

  3. How do we think machines think? An fMRI study of alleged competition with an artificial intelligence

    Science.gov (United States)

    Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

    2012-01-01

    Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents. PMID:22586381

  4. How do we think machines think? An fMRI study of alleged competition with an artificial intelligence.

    Science.gov (United States)

    Chaminade, Thierry; Rosset, Delphine; Da Fonseca, David; Nazarian, Bruno; Lutcher, Ewald; Cheng, Gordon; Deruelle, Christine

    2012-01-01

    Mentalizing is defined as the inference of mental states of fellow humans, and is a particularly important skill for social interactions. Here we assessed whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by comparing brain responses during the interaction with an intentional and an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing their opponent was a fellow human (Intentional agent, Int), a humanoid robot endowed with an artificial intelligence (Artificial agent, Art), or a computer playing randomly (Random agent, Rnd). Participants' subjective reports indicated that they adopted different stances against the three agents. The contrast of brain activity during interaction with the artificial and the random agents didn't yield any cluster at the threshold used, suggesting the absence of a reproducible stance when interacting with an artificial intelligence. We probed response to the artificial agent in regions of interest corresponding to clusters found in the contrast between the intentional and the random agents. In the precuneus involved in working memory, the posterior intraparietal suclus, in the control of attention and the dorsolateral prefrontal cortex, in executive functions, brain activity for Art was larger than for Rnd but lower than for Int, supporting the intrinsically engaging nature of social interactions. A similar pattern in the left premotor cortex and anterior intraparietal sulcus involved in motor resonance suggested that participants simulated human, and to a lesser extend humanoid robot actions, when playing the game. Finally, mentalizing regions, the medial prefrontal cortex and right temporoparietal junction, responded to the human only, supporting the specificity of mentalizing areas for interactions with intentional agents.

  5. Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques

    Science.gov (United States)

    Sun, Ke; Wang, Zhengjie; Tu, Kang; Wang, Shaojin; Pan, Leiqing

    2016-11-01

    To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network (BPNN), convolutional neural network (CNN), and deep belief network (DBN) models. An accuracy rate of 100% was achieved by using the DBN model to identify the mould species in the sample images based on selected colour-histogram parameters, followed by the SVM and BPNN models. A pitch segmentation recognition method combined with different classification models was developed to recognize the mould colony areas in the image. The accuracy rates of the SVM and CNN models for pitch classification were approximately 90% and were higher than those of the BPNN and DBN models. The CNN and DBN models showed quicker calculation speeds for recognizing all of the pitches segmented from a single sample image. Finally, an efficient uniform CNN pitch classification model for all five types of sample images was built. This work compares multiple classification models and provides feasible recognition methods for mouldy unhulled paddy recognition.

  6. Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

    Science.gov (United States)

    McMullen, David P; Hotson, Guy; Katyal, Kapil D; Wester, Brock A; Fifer, Matthew S; McGee, Timothy G; Harris, Andrew; Johannes, Matthew S; Vogelstein, R Jacob; Ravitz, Alan D; Anderson, William S; Thakor, Nitish V; Crone, Nathan E

    2014-07-01

    To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

  7. DEVELOPMENT OF A MACHINE VISION SYSTEM FOR WEED DETECTION DURING BOTH OF OFF-SEASON AND IN-SEASON IN BROADACRE NO-TILLAGE CROPPING LANDS

    Directory of Open Access Journals (Sweden)

    Huajian Liu

    2014-01-01

    Full Text Available More than half of the Australian cropping land is no-tillage and weed control within continuous no-tillage agricultural cropping area is becoming more and more difficult. A major problem is that the heavy herbicide usage causes some of more prolific weeds becoming more resistant to the regular herbicides and therefore more powerful and more expensive options are being pursued. To overcome such problems with aiming at the reduction of herbicide usage, this proposed research focuses on developing a machine vision system which can detect and mapping weeds or do spot spray. The weed detection methods described in this study include three aspects which are image acquisition, a new green plant detection algorithm using hybrid spectral indices and a new inter-row weed detection method taking the advantage of the location of the crop rows. The developed method could detect the weeds both during the non-growing summer period and also within the growing season until the canopy of the crop has closed. The design of the methods focuses on overcoming the challenges of the complex no-tillage background, the faster image acquisition speed and quicker processing time for real-time spot spray. The experiment results show that the proposed method are more suitable for the weed detection in the no-tillage background than the existing methods and could be used as a powerful tool for the weed control.

  8. Designing of cigarette detection system based on machine vision%基于机器视觉的烟支检测系统的设计

    Institute of Scientific and Technical Information of China (English)

    章磊; 李耀; 刘光徽

    2012-01-01

    According to the loose-ends and tobacco shortage problems in cigarette packaging line. This paper proposes a software and hardware design of cigarette detection system based on machine vision, gives the critical circuit and software processes of system, and analyzes problems in practical test. The system realizes the real-time images acquisition by OV7620 and FIFO cache, uses the image processing technology in cigarette image analysis,and chieves the automatic detection of the loose-ends and tobacco shortage.%针对卷烟包装线上出现的空头和缺支问题,提出了一种基于机器视觉技术的烟支在线检测系统软硬件设计,给出了关键的电路原理图及软件流程,并对实际测试中的一些问题进行了分析.系统利用OV7620及FIFO缓存技术实现了图像的实时采集,并采用数字图像处理的方法对烟支图像进行分析,实现了空头及缺支的自动检测.

  9. SURFACE QUALITY INSPECTION OF CERAMIC TILES BY MACHINE VISION%陶瓷砖表面质量视觉检测系统研究

    Institute of Scientific and Technical Information of China (English)

    李庆利; 郭彩玲; 张向红

    2011-01-01

    重点介绍了机器视觉技术在陶瓷砖表面质量检测中的应用.系统采用面阵摄象机作为测量工具,应用方向算子进行对目标边缘的定位和跟踪,以便获得完整、精确、封闭的目标边缘.实现了对陶瓷砖的边直度、直角度、缺边和缺角等项目的非接触检测.%In this paper, an on-line machine vision system for surface quality inspection of ceramic tiles is introduced, which grabs the images scanned by area-array cameras. The image processing algorithm which uses direction masks is used to locate the edge points exactly. The surface quality of ceramic tiles is measured by the real-time, high precision and non-contact method, which can detect straightness of sides, deviation from rectangularity, rough edge, chip and so on.

  10. STUDY ON SURFACE QUALITY OF CERAMIC TILES BY MACHINE VISION%陶瓷砖表面质量视觉检测系统研究

    Institute of Scientific and Technical Information of China (English)

    李庆利; 郭彩玲; 张向红

    2011-01-01

    In this paper an on-line machine vision system for surface quality of ceramic tiles is introduced, which grabs the images scanned by area-array camera.The image processing algorithm which uses direction masks is used to locate the edge points exactly.The surface quality of ceramic tiles is measured with the real-time, high precision and non-contact method, which includes straightness of sides,deviation from rectangularity, rough edge,chip and so on.%重点介绍了机器视觉技术在陶瓷砖表面质量检测中的应用.系统采用面阵摄像机作为测量工具,应用方向算子进行对目标边缘的定位和跟踪,以便获得完整、精确、封闭的目标边缘.实现了对陶瓷砖的边直度、直角度、缺边和缺角等项目的非接触检测.

  11. TWO-DIMENSION CODE RECOGNITION BASED ON MACHINE VISION%基于机器视觉的2D码识别

    Institute of Scientific and Technical Information of China (English)

    常晓玮

    2014-01-01

    According to components detection of the auto parts supply chain,put forward a kind code recognition method for DataMatrix code,PDF41 7 code,and QR code based on machine vision.The method of obtaining image firstly,and then using the image denoising technique to the image acquired with a 2D code processing,and then select different processing methods according to the 2D code can effectively identify these three 2D codes.The experimental result shows that the proposed approach is feasible and effective and can recognize DataMatrix code,PDF41 7 code,QR code real -timely.%针对汽车生产中零部件供应环节的部件检测应用,提出一种基于机器视觉的DataMatrix码、PDF417码、QR码识别方法。本方法利用图像获取、图像去噪等技术对获取的具有2D码的图像进行处理,然后根据2D码选取不同的处理方法,能有效识别以上三种2D码。实验结果表明该方法是可行的,能实时识别DataMatrix码、PDF417码、QR码。

  12. Automated analysis of retinal imaging using machine learning techniques for computer vision [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jeffrey De Fauw

    2017-06-01

    Full Text Available There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases. Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular (“wet” age-related macular degeneration (wet AMD and diabetic retinopathy. Two methods of imaging are commonly used: digital photographs of the fundus (the ‘back’ of the eye and Optical Coherence Tomography (OCT, a modality that uses light waves in a similar way to how ultrasound uses sound waves. Changes in population demographics and expectations and the changing pattern of chronic diseases creates a rising demand for such imaging. Meanwhile, interrogation of such images is time consuming, costly, and prone to human error. The application of novel analysis methods may provide a solution to these challenges. This research will focus on applying novel machine learning algorithms to automatic analysis of both digital fundus photographs and OCT in Moorfields Eye Hospital NHS Foundation Trust patients. Through analysis of the images used in ophthalmology, along with relevant clinical and demographic information, DeepMind Health will investigate the feasibility of automated grading of digital fundus photographs and OCT and provide novel quantitative measures for specific disease features and for monitoring the therapeutic success.

  13. Automated analysis of retinal imaging using machine learning techniques for computer vision [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jeffrey De Fauw

    2016-07-01

    Full Text Available There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases.   Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular (“wet” age-related macular degeneration (wet AMD and diabetic retinopathy. Two methods of imaging are commonly used: digital photographs of the fundus (the ‘back’ of the eye and Optical Coherence Tomography (OCT, a modality that uses light waves in a similar way to how ultrasound uses sound waves. Changes in population demographics and expectations and the changing pattern of chronic diseases creates a rising demand for such imaging. Meanwhile, interrogation of such images is time consuming, costly, and prone to human error. The application of novel analysis methods may provide a solution to these challenges.   This research will focus on applying novel machine learning algorithms to automatic analysis of both digital fundus photographs and OCT in Moorfields Eye Hospital NHS Foundation Trust patients.   Through analysis of the images used in ophthalmology, along with relevant clinical and demographic information, Google DeepMind Health will investigate the feasibility of automated grading of digital fundus photographs and OCT and provide novel quantitative measures for specific disease features and for monitoring the therapeutic success.

  14. Artificial intelligence expert systems with neural network machine learning may assist decision-making for extractions in orthodontic treatment planning.

    Science.gov (United States)

    Takada, Kenji

    2016-09-01

    New approach for the diagnosis of extractions with neural network machine learning. Seok-Ki Jung and Tae-Woo Kim. Am J Orthod Dentofacial Orthop 2016;149:127-33. Not reported. Mathematical modeling. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Low Vision

    Science.gov (United States)

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

  16. The PLC Control of Vision Detection Machine for Ceramic Sleeve Surface Defects%陶瓷套圈表面质量机器视觉检测系统

    Institute of Scientific and Technical Information of China (English)

    张磊; 陈红; 范维浩

    2011-01-01

    本文在分析陶瓷套圈表面质量机器视觉检测机的系统组成和自动检测工作流程基础上,设计出检测机的气动驱动系统和PLC集成电气控制系统,给出PLC控制程序流程.通过PLC集成机器视觉、气动驱动和步进电机驱动控制系统,实现陶瓷套圈外圆表面缺陷机器视觉检测自动化,自动检测节拍达到2秒/件.%This paper firstly analyzes the mechanical system principle and technological process of the vision detection machine for ceramic sleeve surface quality inspection, and then designs a pneumatic drive system and PLC control system for the machine finally programs a PLC control program to implement the integrating control of machine vision, pneumatic drive system and stepping motor. The automatic cycle time of vision detection implements is 2 sec / piece.

  17. SENSITIVITY ANALYSIS BY ARTIFICIAL NEURAL NETWORK (ANN) OF VARIABLES THAT INFLUENCE THE DIAGONAL TWIST IN A PAPERBOARD INDUSTRIAL MACHINE

    OpenAIRE

    Guinter Neutzling Schneid; Rubens Chaves de Oliveira; Osvaldo Vieira

    2016-01-01

    The dimensional stability of the paper may change due to middle exchange moisture, releasing the latent stress acquired into the manufacturing process. One result of this tension release is the diagonal curl. This study aims to conduct a sensitivity analysis of the different input’s variables of an industrial paper machine, along with some laboratory measurements, in order to identify the importance in production of paperboard quality control and relate to the property of the paper called...

  18. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  19. Artificial fish swarm algorithm for virtual machine placement%人工鱼群算法在虚拟机分配中的应用

    Institute of Scientific and Technical Information of China (English)

    李迎; 张璟; 虎群; 李军怀

    2015-01-01

    Virtual machine management is a crucial mission of the cloud datacenters.It identifies the mapping between virtual machines and physical machines,which has important implications for clustering performance,response time and service quality,etc.It is necessary to adopt effective strategies to make sure it can be completed automatically and goals such as load balancing,virtual machine migration and power consumption are achieved at the same time.This paper proposes an improved artificial fish swarm algorithm which employs a new behaviors selection and applies it to solve the virtual machine management problem.The simulation calculation results,compared with other common algorithms,show that it can obtain high quality solution with much less time consumption without accuracy losing.%虚拟机分配是云数据中心的一个重要任务,它实现物理机和虚拟机的映射,这对整个云数据中心中计算集群的性能,响应时间和服务质量有重要影响。需要采用一定的虚拟机分配策略来保障在同一集群中自动地完成虚拟机分配,以便达到物理机集群的负载均衡,虚拟机迁移次数最小并且节能环保等目的。提出了一种添加新型行为策略的人工鱼群算法,并将该算法成功应用于虚拟机分配问题的求解。与多种虚拟机分配算法的对比结果表明,算法能更快获得符合云数据中心多个需求的分配方案,对于其他实时性要求较高的组合优化问题同样具有应用价值。

  20. 基于机器视觉瓷砖尺寸在线检测系统设计%System design of ceramic tile dimension online detection based on machine vision

    Institute of Scientific and Technical Information of China (English)

    郭峰林; 管庶安; 胡尧俊; 田魁

    2013-01-01

    Proposed a novelty ceramic tile dimension detection method based on machine vision using overhead light source with inclined installation,uses this method to carry on the ceramic tile image acquisition,then,according to the image characteristics designs ceramic tile vertex recognition algorithm and extracts the ceramic tile vertex position,then,adjusts the vertex position using the camera calibration parameter,finally,according to standard ceramic tile vertex position and relative deviation of testing ceramic tile vertex position indirectly computes ceramic tile size.Experiments show that the error of device online detection value and artificial measuring value of ceramic tile size is small and the repeated test precision of system is accuracy,which show that the online detection result is reliable.Meanwhile,the overall system can conveniently integrate with other detection facility,which is able to save the equipment cost,the manpower cost as well as the equipment occupying space for the equipment user.%提出一种上光源侧射式的机器视觉瓷砖尺寸检测新方法,利用该方法进行瓷砖图像获取,然后,根据图像特征设计瓷砖角点识别算法,提取瓷砖角点位置,接着,利用相机标定参数对角点位置进行校正,最后,根据标准瓷砖角点位置与待测瓷砖角点位置的相对偏差间接计算瓷砖尺寸.实验表明,瓷砖尺寸的在线检测值与人工测量值误差小,系统的.重复检测精度高,检测结果可信.同时,整个系统能够方便地与其他检测设备整合,能为设备使用者节省设备成本、人力成本以及设备占地空间.

  1. Automatic Defect Inspection of PCB Bare Board Based on Machine Vision%基于机器视觉PCB裸板缺陷自动检测研究

    Institute of Scientific and Technical Information of China (English)

    刘百芬; 李海文; 张姝颖; 林德欣

    2014-01-01

    AppIying to the method of reference comparison to automatic defect inspection of PCB bare board based on machine vision.Camera captures muItipIe standard PCB image and caIcuIate its average gray get standard circuit board image tn the same position,image registration compIeted by standard PCB image under test PCB image's corner detection and cor-ner registration,adopting to standard PCB image under test PCB image adopt gray-scaIe transformation,fiItering,binarization, XOR and other image processing respectiveIy to detect the position of the defect area.%运用参考比较法对机器视觉PCB裸板缺陷检测进行了研究。在相机摄像头下同一位置采集多幅标准PCB图像累加求平均值得到标准电路板图像,运用Harris角点算法进行标准电路板图像和待测电路板图像的配准,分别对标准电路板图像和待测电路板图像进行灰度变换、中值滤波、二值化、异或等图像处理检测出缺陷区域,然后通过形态学消除伪缺陷,实验证明,该检测方法有较高的准确率。

  2. Application of machine vision in smartphone based on OpenCV%基于OpenCV的机器视觉在智能手机中的应用

    Institute of Scientific and Technical Information of China (English)

    何鹏; 王连鹏; 楚艳红

    2011-01-01

    For the features of competing mainly in software in the smart phone market, the machine vision technology is introduced to the smart phone based on embedded Linux. The hand signal recognition control application procedure based on OpenCV is studied and realized. Part of the decision started music player with the hand signal to regularly to carry on the discussion, and the program expansion interfaces can implement more different gestures to control the different actions. The experiment indicated that this system meets the realtime processing need, and the movement is stable. This feature of contactless controlling smart phone are both practical and avant-garde, and it makes the smart phones based on Linux more attractive, more broad prospects for development.%针对智能手机市场竞争中主要力拼软件的特点,将机器视觉技术引入以Linux为操作系统的智能手机中,基于OpenCV研究并实现了手势识别控制应用程序.系统决策实现的部分是以手势来启动音乐播放程序进行讨论,而且程序留有扩展接口可以实现更多不同的手势来控制不同的操作.实验结果表明,该系统满足实时处理需求,运行稳定,这种非接触式控制智能手机操作的功能既实用又前卫,使Linux操作系统的智能手机更具吸引力,发展前景更广阔.

  3. 基于机器视觉的点餐自动提示器设计%Design for automatic ordering prompter based on machine vision

    Institute of Scientific and Technical Information of China (English)

    陈善为; 余建安; 邵梦甜; 李萍; 王小梅

    2015-01-01

    According to blinding consumption and unhealthy diet, this thesis puts forward the automatic ordering prompter system based on machine vision;Starting with the key software and hardware technology from the composition of this system, based on the Design of light source, the selection of lens and image acquisition card and image processing control system integrated, this thesis analyzes the working principle of the system, designs the principle structure of the system and prototype designs;Finally, through the analysis of the data from the practice application, showing that the design is helpful to realize the expected goal of the scientific meal and civilized dining and showing that the design has a certain application prospect on the premise of cost control.%针对在外就餐中的盲目消费,不健康饮食等问题,提出基于机器视觉的点餐自动提示器系统;从组成系统的关键软硬件技术入手,基于光源设计、镜头及图像采集卡的选择、图像处理控制系统的设计集成,分析了系统的工作原理,设计了系统的原理结构,并在此基础上进行了原型设计;最后通过对原型系统实践应用得到的数据分析,表明该设计有助于实现科学点餐,文明就餐的预期目标,在成本得到进一步控制的前提下具有一定的应用前景。

  4. Research on color difference detection algorithm based on machine vision%基于机器视觉的色差检测算法

    Institute of Scientific and Technical Information of China (English)

    范鹏飞; 孙俊

    2016-01-01

    Algorithm for color difference detection based on machine vision is studied to solve the problem of color difference detection in metal printing. By printing color mark in metal blank area,capture color mark areas on metal printing products using industrial CCD cameras,digital image processing technique is applied to extract color. Use color difference detection algorithm based on HSV color space and color difference detection algorithm based on CIELAB color space,analyze color difference detection results in two kinds of color space,using the method combining the two kinds of color space detection algorithms,implement rapid and effective detection,and at the same time,it can ensure accuracy of detection results.%针对金属印刷质量中的色差检测问题,采用机器视觉的技术对色差检测算法进行了研究。通过在金属印刷品的留白区域印刷色标,使用工业CCD相机采集金属印刷产品上的色标区域,使用数字图像处理技术提取色标。使用了基于HSV颜色空间的色差检测算法和基于CIELAB颜色空间的色差检测算法,分析了两种颜色空间下色差检测的实验结果,采用两种颜色空间检测算法相结合的方法,实现对色差合理有效的快速检测,同时能保证检测结果的准确性。

  5. Automatic Detecting a Bunch of Cash Based on Machine Vision Systems%基于机器视觉的智能卡把系统

    Institute of Scientific and Technical Information of China (English)

    张海宁; 许飞; 冯晓岗

    2012-01-01

    卡把是指对捆钱的把数进行数目的核定.目前的卡把操作是人工的,不仅费时,而且可能出现误判.基于机器视觉的卡把系统通过摄像机取像,将被摄取的目标信号转换成图像信号,并将此图像信号传送给专用的图像处理系统,抽取图像的特征,进而根据判别的结果来控制智能设备的执行相应的操作.本系统能够自动进行智能卡把操作,并对不符合规范的钱捆进行报警和处理.不仅提高了卡把速度,而且极大降低了卡把的误判率.%Detecting a bunch of cash is refers to approve the number of money. Recently, this operation is manual, which not only takes time, but also appears a miscalculation. Automatic detecting a bunch of cash based on machine vision system gets the picture through the camera, makes the target signal convert into image signal, and takes the image signals lo the dedicated image processing system, extracts the image characteristics, and then controls the equipment to do the corresponding operation according to the result of discrimination. Tliis system can be automatically detected a bunch of cash, and alarms and handles money which is not up to standard, which not only improves the speed, and greatly reduces the false rate.

  6. 采棉机视觉导航路线图像检测方法%Detection for navigation route for cotton harvester based on machine vision

    Institute of Scientific and Technical Information of China (English)

    李景彬; 陈兵旗; 刘阳; 查涛

    2013-01-01

    Auto-navigation has a great significance in increasing the operating quality and production efficiency of agriculture machinery, such as improving the working environment and security situation for workers, reducing the labor intensity, etc. The vision navigation has many technical advantages that it can adapt to the complicated field of the operating environment, has wide detection range and has rich and complete information. It is the research focus in the field of agriculture machinery auto-navigation. How to extract routes fast, accurately, and effectively in the natural environment is the key in vision navigation. The vision navigation routes’ detect of a Cotton-picker is the main premise to achieve its auto-navigation. There are many difficulties in detecting the operation routes of a cotton-picker in the field. For example, during harvest, there are many kinds of target features like stalks, cotton, bolls, leaves, weeds in the cotton field and its outside region. In addition, a little cotton may be left on the stalks in the harvested region when we use machine to pick. This paper puts forward the detection algorithms of the operation routes of a cotton-picker, the edge and the end of the cotton field by analyzing the different color features of the harvested region, the un-harvested region, the outside region, and the end of the field. First, we used the difference of color components, such as 3B-R-G, |R-G|, |R-B| and |G-B| to extract the target features of the inner and outside of the cotton field respectively, and smooth the image using the moving average method by the set length. Then by finding the rose critical point of the crest that is based on the lowest trough point to the un-harvested region, and connecting with the line detect result of the previous frame, we determine the alternate point group of a straight line transform. At last, we extracted the navigation routes based on Passing a Known Point Hough Transform (PKPHT). The test proves that

  7. Design on special robot used for colliery based on machine vision and independent suspension system%基于机器视觉和独立悬挂系统的煤矿特种机器人设计

    Institute of Scientific and Technical Information of China (English)

    赵建伟; 班钰; 王俊懿

    2016-01-01

    由于煤矿井下煤尘存在爆炸性、煤层中溢出的瓦斯也具有威胁性,所以采煤工作环境十分恶劣和危险。为此利用 LabVIEW 和 IMAQ Vision 构建了基于彩色图像二值化的机器视觉图像处理算法,提出了一种基于机器视觉和独立悬挂系统的煤矿特种机器人。该机器人四轮能够独立运动,同时兼备灵活的探测抓取和越障能力,应用于煤矿勘探以及利用视觉进行物体识别方面,并通过抓球和爬楼梯试验验证了该机构的可行性。%In view of severe and dangerous surroundings of coal mining operation, the paper applied LabVIEW and IMAQ Vision to construct the machine vision image processing algorithm based on color image binarization, and proposed a special robot used for colliery based on machine vision and independent suspension system. The four wheels of the robot moved independently, and the robot possessed flexible grasping ability and obstacle climbing ability. It could be applied to colliery exploration and object recognition via vision. Finally, the robot proved feasible via ball grasping and stair climbing test.

  8. 基于机器视觉的猪体质量估测模型比较与优化%Comparison and optimization of pig mass estimation models based on machine vision

    Institute of Scientific and Technical Information of China (English)

    李卓; 毛涛涛; 刘同海; 滕光辉

    2015-01-01

    Pig’s weight is an important index for farmers to monitor pig’s growth performance and health. Traditional weighting brings lots of stress to animals and stockmen due to manual operation. Pig weighting based on machine vision is a non-intrusive, fast and precise approach, for it can free the farmer from heavy operational labor. The weighting system precision is assured by the estimation model. A lot of estimation models are addressed in pig weighting based on machine vision by researchers and engineers. Both independent variables and modeling approaches would influence the accuracy of estimated weight. In present work, comparison and optimization of the models were conducted, and the best model was validated in the real farm. In the first experiment, four growing pigs were raised from 30 to 124 kg. The feed was suppliedad libitum, and the lighting was in a 12/12 h light/dark cycle. A machine vision system was assembled and installed with two parallel cameras, an RFID (radio frequency identification devices) reader and a PC for capturing live images of pigs automatically. Using the assembled system, the pigs’ back areas were measured. The head and tail of pig in each picture was cut off for pig’s back area calculation. Five indexes of pig body (body length, width, height, hip width, and hip height) were measured manually every day. Linear regression, power regression, quadratic regression, principal component regression and RBF (radial basis function) artificial neural network were used to establish estimation models using the 79 sets of data. Those models were compared using the remaining 97 sets of data. The second experiment was carried out in the real farm to validate the favorable model. Five body indexes of 24 adult pigs were measured three times manually. The results of experiment station showed that all the reestablished models were suitable for pig weight estimation with varied accuracies. Linear regression model based on body sizes was the best one

  9. SENSITIVITY ANALYSIS BY ARTIFICIAL NEURAL NETWORK (ANN OF VARIABLES THAT INFLUENCE THE DIAGONAL TWIST IN A PAPERBOARD INDUSTRIAL MACHINE

    Directory of Open Access Journals (Sweden)

    Guinter Neutzling Schneid

    2016-01-01

    Full Text Available The dimensional stability of the paper may change due to middle exchange moisture, releasing the latent stress acquired into the manufacturing process. One result of this tension release is the diagonal curl. This study aims to conduct a sensitivity analysis of the different input’s variables of an industrial paper machine, along with some laboratory measurements, in order to identify the importance in production of paperboard quality control and relate to the property of the paper called twist. A survey was made of the production history, relating to 2012, to observe the products with the highest quality losses. From this, they were correlated with the critical points of measurement profile in the machine cross direction and consequently with the paper. It was found some changes once the variables correlated with twist, referring to the three analyzes of the profile (tender side, middle and drive side. It was revealed, from the sensitivity analysis, that the most important and sensitive variables, respectively for the tender side, middle and drive side, were total flow from the top layer, vapor pressure in the 6th group of drying cylinders and mass flow side of the bottom layer of the formation of paperboard.

  10. 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

  11. Machine Learning

    CERN Document Server

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  12. Automotic Recognition of Sleep Spindles Based on Two-Stage Classifier with Artificial Neural Networks and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    MohammadHoseyn Khaksar

    2008-03-01

    Full Text Available Sleep spindles are one of the most important transient waveforms found in the sleep EEG signal. Here, we introduce a two-stage procedure based on artificial neural networks for the automatic recognition of sleep spindles (SS in a 19-channel electroencephalographic signal. In the first stage, a pre-processing perception is used for enhancing overall detection and also reducing computation time. In the second stage, the selected Sleep spindles (SS, classified with neural network post-classifier. Classifying tools in post-processing procedure were MLP and RBSVM that their operations are compared in the last section of the report. Visual inspection of 19-channel EEG from six subjects by one expert in this theme, showed that RBSVM operation is better than MLP with BP (Back propagation training, that SVM provided 91.4% average sensitivity and 3.85% average false detection rate.

  13. Novel pose measurement for agricultural vehicle guided by machine vision%视觉导航农用车辆相对位姿测量新方法

    Institute of Scientific and Technical Information of China (English)

    周俊; 姬长英; 刘成良

    2006-01-01

    农田环境中农作物大多呈近似直线的行垄分布特点,农用车辆自主视觉导航时通常利用这些景物特征作为跟踪目标.提出了一种计算车辆相对于跟踪目标位姿的新型方法,首先分析了传统算法中存在的计算量大、忽视图像平面中各像素权重不同等缺陷,而后依据跟踪路径局部线性模型假设,详细地推导了算法过程.基于视觉导航原型车辆的试验结果表明,与人工测量值相比,横向距离和航向角的误差均值都等于零,标准差分别为3cm 和0.62deg.%Some agricultural tasks consist of applying chemical fertilizer to crops, but the products are often applied throughout the field in most cases, which cause pollution of water and possible chemical residues. In order to apply the products selectively and reduce the quantity of application, an autonomous vehicle can be used. Generally, this kind of vehicle follows the crop rows autonomously in the field where plants are arranged in rows, so its pose relative to crop row is important for tracking algorithm to work. With the machine vision, a novel method to calculate this pose was demonstrated, which could adapt to the complex characteristics of field environment excellently. First, some shortcomings involved in the conventional measuring method were analyzed carefully, such as processing time being long, pixel weight in the digital image being ignored and so on. With the local linear model of the tracked crop row then the algorithm was deduced at full length. Finally, based on the prototype of autonomous agricultural vehicle, the experiment was carried out, and it was shown that compared with the manual measurement the standard deviation of offset was 3 cm and of heading angle 0.62 deg while without any fixed displacement.

  14. Application of OpenCV in machine vision detection system of cigarette case%OpenCV在条烟视觉检测系统中的应用

    Institute of Scientific and Technical Information of China (English)

    周传宏; 陈郭宝; 王怀虎; 康少博

    2011-01-01

    The cigarette case detection system is a special device, which is installed on the production line in front of packing machine to detect the appearance defect.The system can detect cigarette case in real-time and remove the defective products in time with characteristics of high-speed, efficient and accurate, which is an auto-detection system covering mechanic, optical, electric, computer and communications as well as other technologies.The application of the system greatly improves the automation of the tobacco company;In addition, it also can reduce the labor intensity,improve the working environment and ensure the product quality.The algorithm for common detection items of cigarette case was designed and the open source computer vision library OpenCV of Intel Company was used to improve the detection speed and accuracy in it.%条烟视觉检测系统是安装在条包生产线上,在条包装箱之前,对其外观缺陷进行检测的一种专用设备.系统可以对生产线上的条包进行实时检测,并及时剔除外观有缺陷的产品,具有高速、高效、准确的优点.该检测系统是集机械、光电、计算机、通信等技术为一体自动化检测系统,系统具有高速、高效、准确的优点,它的使用不仅可以提高烟草生产企业的自动化程度,还可以降低工人的劳动程度,改善工作环境,保证产品的质量.对常见条烟检测项进行了算法设计,并利用某公司的开源计算机视觉库OpenCV进行算法实现,提高了检测速度和精度.

  15. Research on workpiece Sorting Technology of Industrial Robot Based on Machine Vision%基于机器视觉的工业机器人工件分拣技术研究

    Institute of Scientific and Technical Information of China (English)

    甘伟

    2014-01-01

    工业机器人广泛应用于自动化生产线上完成工件搬运、上下料等操作,机器视觉的引入增加机器人了的灵活性和智能化。本文对基于视觉的工业机器人工件分拣的技术进行研究,机器视觉系统对传送带上进入工作区的工件进行图像采集,根据图像信息提取工件特征参数,识别出工件类型,并判断出工件所处的位置姿态,最后控制机器人执行抓取。经过实验表明本系统工作可靠,提高了自动化生产线效率和柔性。%Industrial robots have been widely used on industrial production line to complete a variety of operations such as workpiece handling,loading and unloading,etc.The machine vision can improve robotic lfexibilities and Intel igence.This paper introduces researching machine vision for the workpiece Sorting technology of industrial robot. When workpiece enter the sorting operation area,machine vision system capture image information to extract the feature parameters of workpiece, recognize the workpiece types,colour,size,and to judge the position and posture of workpiece,and ifnal y control the robot to implement the sorting action.Experiments prove the system work reliability,improve the efifciency and lfexibility of the automatic production line.

  16. 机器视觉辅助的插头锥套式无人机自主空中加油仿真%Machine Vision Aided Simulation of Probe and Drogue Unmanned Aerial Vehicle Autonomous Aerial Refueling

    Institute of Scientific and Technical Information of China (English)

    王旭峰; 董新民; 孔星炜

    2013-01-01

    In order to precisely obtain the relative pose between probe and drogue during unmanned aerial vehicle (UAV) autonomous aerial refueling docking,a machine vision aided simulation scheme of probe-drogue UAV autonomous aerial refueling is proposed.Based on the machine vision,the recognition and tracking algorithm of refueling drogue is investigated.The relative pose between UAV and refueling drogue is estimated by using of Kalman filter algorithm.Experiment results show that the machine vision aided image processing algorithm can recognize and track refueling drogue precisely and the convergence of relative pose errors estimated by the filter algorithm is proved,fulfilling the demand of probe-drogue UAV autonomous aerial refueling.%为准确获取无人机自主空中加油对接阶段受油插头与加油锥套的相对位姿信息,提出一种机器视觉辅助的插头锥套式无人机自主空中加油方案.研究了机器视觉识别跟踪加油锥套的算法,利用卡尔曼滤波算法估计无人机与加油锥套的相对位姿.实验结果表明:机器视觉图像处理算法可精确识别跟踪加油锥套,滤波器估计的相对位姿误差收敛速度较快,满足插头锥套式无人机自主空中加油的需要.

  17. Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

    Science.gov (United States)

    Rienow, A.; Menz, G.

    2015-12-01

    Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future

  18. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    Science.gov (United States)

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  19. Using machine learning to classify image features from canine pelvic radiographs: evaluation of partial least squares discriminant analysis and artificial neural network models.

    Science.gov (United States)

    McEvoy, Fintan J; Amigo, José M

    2013-01-01

    As the number of images per study increases in the field of veterinary radiology, there is a growing need for computer-assisted diagnosis techniques. The purpose of this study was to evaluate two machine learning statistical models for automatically identifying image regions that contain the canine hip joint on ventrodorsal pelvis radiographs. A training set of images (120 of the hip and 80 from other regions) was used to train a linear partial least squares discriminant analysis (PLS-DA) model and a nonlinear artificial neural network (ANN) model to classify hip images. Performance of the models was assessed using a separate test image set (36 containing hips and 20 from other areas). Partial least squares discriminant analysis model achieved a classification error, sensitivity, and specificity of 6.7%, 100%, and 89%, respectively. The corresponding values for the ANN model were 8.9%, 86%, and 100%. Findings indicated that statistical classification of veterinary images is feasible and has the potential for grouping and classifying images or image features, especially when a large number of well-classified images are available for model training. © 2012 Veterinary Radiology & Ultrasound.

  20. Machine learning on-a-chip: a high-performance low-power reusable neuron architecture for artificial neural networks in ECG classifications.

    Science.gov (United States)

    Sun, Yuwen; Cheng, Allen C

    2012-07-01

    Artificial neural networks (ANNs) are a promising machine learning technique in classifying non-linear electrocardiogram (ECG) signals and recognizing abnormal patterns suggesting risks of cardiovascular diseases (CVDs). In this paper, we propose a new reusable neuron architecture (RNA) enabling a performance-efficient and cost-effective silicon implementation for ANN. The RNA architecture consists of a single layer of physical RNA neurons, each of which is designed to use minimal hardware resource (e.g., a single 2-input multiplier-accumulator is used to compute the dot product of two vectors). By carefully applying the principal of time sharing, RNA can multiplexs this single layer of physical neurons to efficiently execute both feed-forward and back-propagation computations of an ANN while conserving the area and reducing the power dissipation of the silicon. A three-layer 51-30-12 ANN is implemented in RNA to perform the ECG classification for CVD detection. This RNA hardware also allows on-chip automatic training update. A quantitative design space exploration in area, power dissipation, and execution speed between RNA and three other implementations representative of different reusable hardware strategies is presented and discussed. Compared with an equivalent software implementation in C executed on an embedded microprocessor, the RNA ASIC achieves three orders of magnitude improvements in both the execution speed and the energy efficiency.

  1. Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM and Artificial Neural Network (ANN

    Directory of Open Access Journals (Sweden)

    Maria Grazia De Giorgi

    2014-08-01

    Full Text Available A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP. A comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain. The performances of Least-Squares Support Vector Machine (LS-SVM with Wavelet Decomposition (WD were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN-based methods. It is acknowledged that hybrid methods based on LS-SVM with WD mostly outperform other methods. A decomposition of the commonly known root mean square error was beneficial for a better understanding of the origin of the differences between prediction and measurement and to compare the accuracy of the different models. A sensitivity analysis was also carried out in order to underline the impact that each input had in the network training process for ANN. In the case of ANN with the WD technique, the sensitivity analysis was repeated on each component obtained by the decomposition.

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

    OpenAIRE

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

    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 D...

  3. Implications of VISIDEPtm For Artificial Intelligence Applications

    Science.gov (United States)

    McLaurin, A. P.; Jones, Edwin R.; Cathey, LeConte

    1987-04-01

    VISIDF is a system for generating true three-dimensional displays on flat-screened devices. Hodges and McAllister, in their article, state clearly that this system is the autostereoscopic alternative to PLZT shutter systems for computer-generated graphic appli-cations. This opens the door to consideration of the system as a component of vision for artificial intelligence applications. In order to understand the potentials of VISIDEP one must, in fact, accept several fundamental assumptions. These are: 1. Perception is an intelligent activity rather than purely stimulus/response. 2. Binocular depth cues are of greater importance to accurate depth interpretation than monocular cues. 3. Depth perception does not require object identification. Each of these assumptions is essential to the application of VISIDEP research in practical operations requiring depth interpretation. The relationships between human vision and perception and the parallax induction generated by VISIDEP technology offer depth in real time to artificial intelligence. Through machine operations on incoming data, the perception of depth is generated in much the same way as the stereoptic data enter the human being, thus providing rapidly quantifiable depth interpretation which is very accurate, perhaps more accurate that human perception of depth. The analysis of a mechanical system in relationship to human approaches to depth perceptions offers the potential of many applications of visually competent artificial intelligence. An additional factor is that the system under discussion is user friendly for human operators as well as requiring minimal reconfiguration of existing equipment and relatively simple software.

  4. 基于机器视觉的电子器件在线检测分选系统%Design of Online Detecting and Sorting System for Electronic Devices Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    李啸宇

    2011-01-01

    针对一种声表面波滤波电子器件,设计了基于机器视觉的电子器件在线检测分选系统,详细论述了机器视觉系统的硬件组成和工作原理.在搭建系统硬件平台后,采用Qt应用程序框架,结合OpenCV开发了一套电子器件在线检测分选系统软件.经过大量实验和长时间实际生产运行表明,该系统检测速度快、识别准确率高、成本预算低,完全满足现代工业在线检测的需要.%In order to design a kind of electronic devices of surface acoustic wave filter, it describes a online detecting and sorting system based on machine vision, shows the detail about the hardware components and operating principle of the machine vision system. Based on hardware platform of the system, it develops the system software with Qt application framework and OpenCV library. Lots of experiments and a long period of running show that the system costs low and sorts devices with high detection speed and identification rate, the whole system is able to fully meet the needs of modern industrial online detection.

  5. Conveyor Belt Surface Image Correction and Fault Detection Algorithm Research Based on Machine Vision%基于机器视觉的输送带图像校正和故障检测算法研究

    Institute of Scientific and Technical Information of China (English)

    2016-01-01

    为了消除基于机器视觉的输送带故障在线监测系统中采集图像的不均匀光照影响,提高图像质量,检测出图像中的故障区域,提出了一种基于机器视觉的输送带图像校正和故障检测算法.该算法首先采用Butterworth低通滤波器对图像滤波,结合Retinex理论计算估计真实图像的背景,对图像进行灰度校正,得到校正后的图像;然后将机器视觉与生物视觉相结合,利用PCNN算法,对采集的图像进行检测,检测出故障区域.实验结果表明,算法能有效校正输送带表面图像,清晰检测出故障区域,具有很高的应用价值.%For the purposes of eliminating the influence of the non-uniform illumination which was used in on-line fault moni-toring system of conveyor belt based on machine vision and improved the quality of detected image and detecting the fault area of the image, a new kind of detection algorithm based on machine vision was proposed which can be used to realize the image correc-tion and fault detection of conveyor belt. The proposed algorithm firstly implemented the low-pass filtering of the acquired images by using Butterworth low-pass filter, then established estimated background model of the non-uniform illumination based on Retinex theory. Gray scale of the image can be amended evenly. Lastly, by using the combination the machine vision with biological vision and PNCC theory, the defected area of collected surface image of the conveyor belt was detected. Experimental results show that the proposed algorithm can be effectively used to correct the uneven gray scale of the surface images and detect the defected area of the surface image. It proves that this proposed algorithm has very high application value in mine belt conveyor supervision system.

  6. 基于机器视觉的水稻秧苗图像分割%Machine vision based segmentation algorithm for rice seedling

    Institute of Scientific and Technical Information of China (English)

    袁加红; 朱德泉; 孙丙宇; 孙磊; 武立权; 宋宇; 蒋锐

    2016-01-01

    水稻秧苗的识别是水稻插秧机自主导航系统的关键内容之一.针对插秧机机器视觉导航中稻田图像秧苗与背景分割问题,建立了基于RGB(红绿蓝)颜色空间的秧苗表面颜色模型.通过颜色特征对秧苗图像进行处理,使用Photoshop软件获取秧苗部分和背景R,G,B分量值;通过对G-R值与G-B值的分析统计,发现两者之间存在分界关系:各自的权重与各分量的乘积之和为某个定值;为方便分析,选取权值a,b为0.5,即ExG因子,采用Otsu法获取定值最佳值,最大程度分割出目标和背景.与适合于大多数绿色作物的传统RGB法进行比较,并采用分割质量因子和算法运算时间作为评判标准,分析各算法的综合性能.试验发现,ExG因子结合Otsu分割法分割效果相对理想、稳定性更高,而且耗时更短.%The recognition of rice seedling is one of the significant parts of autonomous guidance for rice transplan-ting. Considering the segmentation of seedlings and remainder based on machine vision system, a simple dichromatic reflection model was established in RGB color space, which represented that the seedling could be recognized by u-sing its color feature. The values of R, G, B components of seedlings and remainder were obtained in Photoshop soft-ware respectively and analyzed statistically in order to get the relation between them. In order to simplify the compu-ting process, the weight values of a and b were set as 0. 5, ExG index and Otsu method (ExG+Otsu method) which could obtain the optimal threshold were combined to distinguish the seedlings and remainder well. The RGB method and previous ExG+Otsu method were carried out to compare their performance intuitively. Their comprehensive per-formance was evaluated with segmentation quality factor and time consuming. The results have proved that the latter for segmenting was more efficient, highly stable and timesaving.

  7. 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.

  8. Bio-inspired vision

    Science.gov (United States)

    Posch, C.

    2012-01-01

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

  9. 基于机器视觉的随机纹理瓷砖的分选系统%Classification System of Random Texture Ceramic Tiles Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    焦亮; 胡国清; Jahangir Alam SM

    2016-01-01

    针对日益加快的瓷砖生产速度与缓慢的人工分选速度之间不协调导致的瓷砖出产效率低下的问题,提出了以机器视觉软件HALCON 11.0为软件开发平台的结合瓷砖颜色、纹理特征提取的算法,以及针对多分类问题的改进多层感知器神经网络算法(MLPNN).首先对拍摄到的瓷砖图像进行去噪预处理,在HSI颜色空间中提取瓷砖的色调(Hue)特征并计算反映瓷砖的纹理特征的灰度共生矩阵(GLCM)和灰度幅值分布特征,再将得到的特征作为多层感知器的神经网络输入层神经元,然后设计以softmax为激活函数的多层感知器神经网络来进行模式匹配,并与BP神经网络模式匹配方法进行对比,最终搭建出具有简单人机交互界面的随机纹理瓷砖的分选实验样机.实验结果表明:本系统对实验的各类随机纹理瓷砖的分选准确率都在90%以上,具有较高的分选准确率,能应用于瓷砖生产实践.%Aiming at the problem of poor efficiency of ceramic tile production caused by the mismatch between higher and higher speed of production and slow speed of artificial classification, the paper presented an algorithm about extracting the features of color and texture of ceramic tiles and an algorithm about improved multilayer perceptron neural network (MLPNN) aiming at the problem of multi-classification based on machine vision software, HALCON 11.0, as the development platform. Firstly, the images of ceramic tiles were denoised as pretreatment. Then the system extracted the hue features of ceramic tiles in HSI color space, calculated the gray level co-occurrence matrix (GLCM) and gray level characteristics of amplitude distribution to reflect the texture feature of ceramic tiles, and put the features as input layer neurons of multilayer perceptron neural network. Next, the paper designed the multilayer perceptron neural network with putting softmax function as the activation for pattern matching, and

  10. Support vector machine regression (LS-SVM)--an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?

    Science.gov (United States)

    Balabin, Roman M; Lomakina, Ekaterina I

    2011-06-28

    A multilayer feed-forward artificial neural network (MLP-ANN) with a single, hidden layer that contains a finite number of neurons can be regarded as a universal non-linear approximator. Today, the ANN method and linear regression (MLR) model are widely used for quantum chemistry (QC) data analysis (e.g., thermochemistry) to improve their accuracy (e.g., Gaussian G2-G4, B3LYP/B3-LYP, X1, or W1 theoretical methods). In this study, an alternative approach based on support vector machines (SVMs) is used, the least squares support vector machine (LS-SVM) regression. It has been applied to ab initio (first principle) and density functional theory (DFT) quantum chemistry data. So, QC + SVM methodology is an alternative to QC + ANN one. The task of the study was to estimate the Møller-Plesset (MPn) or DFT (B3LYP, BLYP, BMK) energies calculated with large basis sets (e.g., 6-311G(3df,3pd)) using smaller ones (6-311G, 6-311G*, 6-311G**) plus molecular descriptors. A molecular set (BRM-208) containing a total of 208 organic molecules was constructed and used for the LS-SVM training, cross-validation, and testing. MP2, MP3, MP4(DQ), MP4(SDQ), and MP4/MP4(SDTQ) ab initio methods were tested. Hartree-Fock (HF/SCF) results were also reported for comparison. Furthermore, constitutional (CD: total number of atoms and mole fractions of different atoms) and quantum-chemical (QD: HOMO-LUMO gap, dipole moment, average polarizability, and quadrupole moment) molecular descriptors were used for the building of the LS-SVM calibration model. Prediction accuracies (MADs) of 1.62 ± 0.51 and 0.85 ± 0.24 kcal mol(-1) (1 kcal mol(-1) = 4.184 kJ mol(-1)) were reached for SVM-based approximations of ab initio and DFT energies, respectively. The LS-SVM model was more accurate than the MLR model. A comparison with the artificial neural network approach shows that the accuracy of the LS-SVM method is similar to the accuracy of ANN. The extrapolation and interpolation results show that LS-SVM is

  11. 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...

  12. Vision Screening

    Science.gov (United States)

    ... of Prematurity Strabismus Stye (defined) Vision Screening Vision Screening Recommendations Loading... Most Common Searches Adult Strabismus Amblyopia Cataract Conjunctivitis Corneal Abrasions Dilating Eye ...

  13. The Recognition of Face-Gear' s Tooth Surface based on the Theory of Machine Vision%基于计算机视觉的面齿轮齿面重构技术

    Institute of Scientific and Technical Information of China (English)

    冯美君; 佟勇

    2012-01-01

    As face-gear is used on aeronautical drives system, the advantages of the face-gear drives has been known by people and the research of the face-gear is deep going. Machine vision has the characteristics of high precision, fast speed, no-contact, the thesis has research the application of the machine vision measurement technique on the tooth surface reconstruction, the mathematic model of camera imaging is analyzed, 2D digital image of tooth surface is acquired by two cameras, computer is used to process image and reconstruct 3D coordinates of the key point on the surface of the face-gear and finally realize the reconstruction, this paper provides support for further machining of the face-gear.%随着面齿轮在航空传动系统上的应用,面齿轮传动的优点逐渐被人们认识,对面齿轮的研究也不断深入.计算机视觉检测技术具有检测精度高、实现速度快、非接触检测的特点,论文研究了计算机视觉测量技术在面齿轮齿面重构中的应用,建立了摄像机成像的数学模型,由摄像机获取齿轮齿面的二维图像,通过计算机对数字图像进行图像处理,计算出关键齿面点的三维坐标,实现面齿轮齿面的重构,为基于面齿轮实体的数字化加工奠定了基础.

  14. Recognition of artificial ripening tomato and nature mature tomato based on computer vision%基于计算机视觉的番茄催熟与正常熟识别

    Institute of Scientific and Technical Information of China (English)

    赵海波; 周向红

    2011-01-01

    国内常有菜农采摘远离成熟期的番茄,采用乙烯利处理进行催熟,为了阻止催熟番茄进入瓜果市场危害食用者的身体健康,给出了催熟番茄识别系统的硬件组成,通过计算机视觉装置获取番茄透射光颜色参数(R、G、B),并将RGB值转换成HIS值,采用遗传算法训练的多层前馈神经网络实现催熟番茄的自动识别.试验结果表明,系统正确识别率为91.7%,为进一步进行番茄催熟与正常熟识别的研究提供参考.%Nowadays some vegetable farmers pick unripe tomatoes and treat them with ethylene to quicken ripeness in China. In order to keep artificial ripening tomato which harming consumer's health from entering into melon and fruit market, the hardware structure of artificial ripening tomato recognition system was given. The colour parameters RGB (red, green, blue) of transmitted light of tomatoes were obtained through computer vision device, and the RGB values were converted into HIS (hue, intensity, saturation) values. The multilayer feedforward neural networks with genetic algorithm training realized the automated recognition of artificial ripening tomato. The results of test showed that accurate recognition rate of the system was 91.7%, and the method can provide references for further research on recognition of artificial ripening tomato and nature mature tomato.

  15. 机器视觉在钢化玻璃缺陷检测中的应用研究%Application and Research of Machine Vision in Tempered Glass Defect Inspection

    Institute of Scientific and Technical Information of China (English)

    杨杰; 卢盛林; 赵晓芳

    2013-01-01

      在总结引发钢化玻璃产生自爆的原因的基础上,针对有缺陷玻璃和无缺陷玻璃的光学特性差异性和人工检测缺陷玻璃的局限性等问题,提出采用机器视觉技术对钢化玻璃的缺陷进行检测。首先分析了钢化玻璃缺陷检测的光学基本原理,然后给出了缺陷检测系统的基本结构设计,最后探讨了针对钢化玻璃自爆的机器视觉检测系统的技术要点。试验结果表明,利用机器视觉技术能够快速、可靠、准确地检测出含有缺陷的钢化玻璃,从而避免其在使用中出现自爆。%Based on the study of several facts that may cause self-broken of tempered glass,a machine vision inspection technology is a-dopted to detect the defects of the tempered glass for the limitations of manual inspection of defects in glass and the optical characteristic differences of defect glass and defect-free glass. First analyze the basic optical principles of the tempered glass defect detection,and then give the basic structure design of the defect detection system,finally the technical points of the machine vision inspection system in view of the self-broken of tempered glass are also mentioned. The test results show that the use of machine vision technology can detect the de-fects rapidly,reliably and accurately,avoiding the self-broken in using.

  16. The Analysis of Artificial Retina Organization for Signal Processing

    Institute of Scientific and Technical Information of China (English)

    WEIHui

    2004-01-01

    Machine vision is an active branch of artificial intelligence. An important problem in this area is the trade-off among efficiency, accuracy and computation complexity. The human visual system can keep watchfulness to the perimeter of a viewing field while at the same time focus on the center of the field for fine information processing. This mechanism of appropriate assignment of computing resources can reduce the demand for huge and complex hardware structure. Therefore, the design of a computer model based on the biological visual mechanism is an effective approach to resolve problems in machine vision. In this paper, a multi-layer neural model is developed based on the features of receptive field of ganglion in retina to simulate multi-scale perceptive fields of ganglion cell. The neural model can maintain alert on the outer area of the image while capturing and processing more important information in the central part. It may provide valuable inspiration for the implementation of real-time processing and avoidance of huge computation in machine vision.

  17. Identification and counting method of orchard pests based on fusion method of infrared sensor and machine vision%红外传感器与机器视觉融合的果树害虫识别及计数方法

    Institute of Scientific and Technical Information of China (English)

    田冉; 陈梅香; 董大明; 李文勇; 矫雷子; 王以忠; 李明; 孙传恒; 杨信廷

    2016-01-01

    by comparing with the manual count. Taking Grapholitha molesta, Dichocrocis punctiferalis, Adoxophyes orana and disruptors as research objects, recognition results of infrared sensors and machine vision are obtained using the laboratory artificially randomly scattered test samples. Test samples were collected in Xiaotangshan National Precision Agriculture Research and Demonstration Base from July to September in 2015. For the infrared method, infrared circuit is mainly composed of infrared detector, photoelectric detector, filter, amplifier, communication module, and so on. Due to the different size of insect pests, the infrared output is different. The bigger the pest, the bigger the value of the infrared output. Therefore, the influence of ambient light on the detection results is significant. For example, Adoxophyes orana is larger than Grapholitha molesta and smaller than Dichocrocis punctiferalis. To go along with this, the thresholds of Grapholitha molesta, Adoxophyes orana, Dichocrocis punctiferalis and disruptors are 5.655, 13.47 and 23.13, respectively. The system is mainly composed of infrared sensor unit and machine vision unit. The infrared sensor unit introduces the phase lock amplifier technology to extract the weak useful signal from the noise environment, and to solve the problem of the influence of the natural light environment. The core of the lock-in amplification technology is correlation detection, and using the characteristic of useful signals and noise signals being not related to each other to extract the useful signal from the noise by the correlation operation. Using Matlab environment feature extraction algorithm, normalized entropy and normalized energy are chosen as texture feature indices for the HSV three-channel texture feature based on the 'DB4' wavelet decomposition. Infrared image fusion and pest identification are mainly based on the time stamp of infrared and image recognition. Fusion count results are obtained by a formula

  18. Machine vision based evaluation of impact of light emitting diodes (LEDs) on shoot regeneration and the effect of spectral quality on phenolic content and antioxidant capacity in Swertia chirata.

    Science.gov (United States)

    Dutta Gupta, S; Karmakar, A

    2017-09-01

    The present study demonstrates the influence of LED irradiance of various wavelengths on shoot regeneration, biomass accumulation, photosynthetic pigment contents, and antioxidant potentials of Swertia chirata - a critically endangered medicinal plant. Mixed treatment of blue (BL) and red LEDs (RL) in equal proportion (1:1) significantly improved the shoot regeneration response. A machine vision system was developed to assess the shoot regeneration potential under different lighting treatments. Regenerated shoots exposed under BL:RL (1:1) exhibited higher biomass accumulation and canopy development compared to other lighting treatments. Improved canopy growth was evident from the increase in the area, major axis, minor axis, convex area, equivalent diameter and perimeter of regenerated shoot clusters. A higher correlation of dry weight (DW) was noted with the image feature, weighted density (WD) than the fresh weight (FW) in all the LED treated cultures. The significant correlation between DW and WD implies that the image feature WD can be adopted as a non-invasive approach for measuring biomass accumulation as well as detecting hyperhydricity. The developed machine vision approach provides a new direction in the evaluation of shoot organogenesis that displayed features including both shoot multiplication and canopy development. Chlorophyll and carotenoid contents of the regenerated shoots were found to be higher under BL:RL (1:1) than the other treatments. Supplementation of RL led to a reduction in the pigment contents. Spectral quality of lights also significantly influenced the accumulation of total phenolics, flavonoids and flavonols. Cultures exposed under BL exhibited the maximum accumulation of polyphenols. A similar effect of spectral quality was observed with the antioxidant capacity and reducing power potential of leaf extract. The findings demonstrate the ability of LEDs in inducing shoot regeneration as well as accumulation of phenolic antioxidants and

  19. 基于机器视觉的半球面微小孔位置的精密测量系统%A Machine Vision System for Position Measurement of Small Holes on Spherical Surface

    Institute of Scientific and Technical Information of China (English)

    黄劼; 许斌

    2016-01-01

    针对精密零件的半球表面上微小功能孔的位置测量需求,研制了一套基于二维扫描机构、图像获取单元和精密隔振工作台的机器视觉测量系统.本文提出了基于二维正交旋转扫描测量微小孔孔间位置的理论方法和数学模型,探讨了在图像处理过程中小孔边缘的提取算法以及小孔空心位置的计算方法.为了验证测量系统对半球面微小孔位置的测量能力,实验中选用了半球面半径为60 mm、小孔半径为2 mm的工件作为测量对象;利用光学准直仪验证了小孔位置的测量重复性和测量精度等性能指标,实验结果显示测量重复性误差为1.0″和1.4″,在微孔位置测量偏差的极大值为2.13″和4.13″.%This paper presents a machine vision system for the position measurement of small holes fabri-cated on a spherical surface.The machine vision system consists of two rotation stages to rotate the meas-urement sample, an imaging sensor to scan the surface profile of the small hole under detection and a vi-bration-isolation table to reduce the disturbance of the measurement environment.In this paper, the ap-proach to measuring the spatial position of small holes was firstly introduced based on the method of or-thogonal rotary scanning.Due to that the image quality around the hole edge was influenced by the ma-chining defects and machining marks, the image processing algorithm to search the hole edge and to de-termine the hole centre was described in detail.Then, to verify the feasibility of the machine vision sys-tem, the position measurement of a hemispherical artifact, of which the radius was 60 mm and on which the surface was fabricated with small holes with radius of 2 mm, was carried out.Furthermore, the meas-urement repeatability of the spatial position of small holes was experimentally investigated, and the meas-urement accuracy of that was also studied by an optical autocollimator.Experimental result indicates that the

  20. AI And Early Vision - Part II

    Science.gov (United States)

    Julesz, Bela

    1989-08-01

    A quarter of a century ago I introduced two paradigms into psychology which in the intervening years have had a direct impact on the psychobiology of early vision and an indirect one on artificial intelligence (AI or machine vision). The first, the computer-generated random-dot stereogram (RDS) paradigm (Julesz, 1960) at its very inception posed a strategic question both for AI and neurophysiology. The finding that stereoscopic depth perception (stereopsis) is possible without the many enigmatic cues of monocular form recognition - as assumed previously - demonstrated that stereopsis with its basic problem of finding matches between corresponding random aggregates of dots in the left and right visual fields became ripe for modeling. Indeed, the binocular matching problem of stereopsis opened up an entire field of study, eventually leading to the computational models of David Marr (1982) and his coworkers. The fusion of RDS had an even greater impact on neurophysiologists - including Hubel and Wiesel (1962) - who realized that stereopsis must occur at an early stage, and can be studied easier than form perception. This insight recently culminated in the studies by Gian Poggio (1984) who found binocular-disparity - tuned neurons in the input stage to the visual cortex (layer IVB in V1) in the monkey that were selectively triggered by dynamic RDS. Thus the first paradigm led to a strategic insight: that with stereoscopic vision there is no camouflage, and as such was advantageous for our primate ancestors to evolve the cortical machinery of stereoscopic vision to capture camouflaged prey (insects) at a standstill. Amazingly, although stereopsis evolved relatively late in primates, it captured the very input stages of the visual cortex. (For a detailed review, see Julesz, 1986a)

  1. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  2. Design and Implementation of Gesture Recognition System Based on Machine Vision%基于机器视觉的手势识别系统设计与实现

    Institute of Scientific and Technical Information of China (English)

    刘德强

    2015-01-01

    机器视觉的手势识别系统,采用FPGA驱动摄像头OV7650采集视频图像,通过控制FT245RL实现与PC机之间的高速数据传输,在PC机上有运用OpenCV视觉库简单快速的识别手势,避免了高难度算法编程.通过大量实验验证,该系统开发周期短,识别率高.%This article describes the gesture recognition system based on machine vision.The system uses FPGA driven OV7650 camera to capture video images,through controlling FT245RL to achieve high-speed data transfer between PC and FT245RL.Using the simple and rapid identification gestures of OpenCV vision library on PC can avoid the difficult algorithmic programming.A large number of experiments show that the system development cycle is short and recognition rate is high.

  3. 机器视觉技术在卷烟纸剩余量控制中的运用%Applioation of Machine Vision Technology in Control of Cigarette Paper Remnant

    Institute of Scientific and Technical Information of China (English)

    邓春宁

    2015-01-01

    为解决卷烟机自动搭接过程中卷烟纸剩余量过大的问题,利用机器视觉检测技术对生产过程中的卷烟纸剩余量进行精确测量,在最小剩余量的情况下启动卷接纸的自动搭接程序,有效降低了卷烟纸的消耗,可推广到卷烟生产过程中所有卷筒类的辅料自动搭接控制过程中。%To solve the problem of excessive cigarette paper during the process of cigarette machine automatic splice,the machine vision technology is used to accurately measure the cigarette paper remnant during the production. The automatic splice program is started in the case of the minimum remaining amount to effectively reduce the consumption of cigarette paper. It can be applied to al rol class materials automatic splice systems of cigarette manufacturing.

  4. 机器视觉技术在烟箱缺条检测中的应用%Application of Machine Vision Technology in Detection of Lacking Carton of Cigarettes during Case-packing

    Institute of Scientific and Technical Information of China (English)

    董鸿江; 赵日峰

    2011-01-01

    The auto case-packing plays an important role in the production of cigarettes. The lacking carton of cigarettes in the case-packing process may result in line or row vacancy, which will cause reputation lapse and serious quality problems. At present, the mature methods, including eddy current, weighing and radiographic detection, all have their own shortcomings. The machine vision detection technique is widely used in the modern cigarette production due to its superiorities, such as low cost, mature technique and strong applicability. The machine vision technique was used in detecting the lacking carton in the case-packing process of cigarettes, which have positive and important significance in removing the hided quality problems, maintaining and increasing the the enterprise reputation. Based on the existing machines and techniques, the system for detecting the lacking carton in the case-packing process of cigarettes was successfully developed and its reliability was also tested in practice.%在卷烟生产过程中,自动装箱是一道重要的工序,在装箱过程中可能产生漏装导致缺条、缺排现象,造成严重的质量问题.目前比较成熟的检测方法有涡流、称重和射线检测等,但都存在不同程度的缺陷.机器视觉检测技术在现代卷烟生产过程中具有日益广泛的应用,其具有费用低、检测技术成熟、适用性强等优点.在此将机器视觉技术应用到装箱机缺条检测中,对于消除产品质量隐患、提高生产可靠性和维护企业信誉具有十分重要的意义.依据现有的生产机械设备和技术手段,成功开发了卷烟生产过程中的烟箱缺条检测系统,并在生产实践中检验了其可靠性.

  5. 基于机器视觉的种薯自动切块机设计%Design of Automatic Cutter for Potato Used as Seeds Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    邢作常; 田素博; 刘思瑶; 白雪卫; 张祖立

    2016-01-01

    现阶段中国市场没有成熟的种薯切块机,薯农主要依靠手工切块。其主要原因是种薯切削需要控制切削位置以保留薯芽的顶端优势,普通机器不能识别薯芽,并控制切刀切削方位。为此,使用数字图像处理技术,实现了薯芽及其位姿的实时识别,开发了相应的控制系统,设计了基于机器视觉的薯种自动切块机。试验表明:薯芽识别正确率达100%,位姿识别正确率达98.5%,耗时107.431ms,满足使用要求。%There is not mature cutter for potato used as seeds in Chinese market at the present .Potato farmers rely mainly on manual cutting .The main reason is that potato cutting used as a seed need to control the cutting position to keep pota-to bud advantage , ordinary machine cannot identify potato bud , and controls the cutter cutting position .Using image pro-cessing technology , the potato bud and its posture real-time identification is realized , the corresponding control system is developed , and the automatic cutting machine is designed based on machine vision .Tests show that potato bud recogni-tion accuracy reaches 100%, posture recognition accuracy reaches 98 .5%, takes 107 .431 ms .it meets the require-ment.

  6. 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.

  7. The reported incidence of man-machine interface issues in Army aviators using the Aviator's Night Vision System (ANVIS) in a combat theatre

    Science.gov (United States)

    Hiatt, Keith L.; Rash, Clarence E.

    2011-06-01

    Background: Army Aviators rely on the ANVIS for night operations. Human factors literature notes that the ANVIS man-machine interface results in reports of visual and spinal complaints. This is the first study that has looked at these issues in the much harsher combat environment. Last year, the authors reported on the statistically significant (p89,000 flight hours of which >22,000 were with ANVIS) participated. Analysis demonstrated high complaints of almost all levels of back and neck pain. Additionally, the use of body armor and other Aviation Life Support Equipment (ALSE) caused significant ergonomic complaints when used with ANVIS. Conclusions: ANVIS use in a combat environment resulted in higher and different types of reports of spinal symptoms and other man-machine interface issues over what was previously reported. Data from this study may be more operationally relevant than that of the peacetime literature as it is derived from actual combat and not from training flights, and it may have important implications about making combat predictions based on performance in training scenarios. Notably, Aircrew remarked that they could not execute the mission without ANVIS and ALSE and accepted the degraded ergonomic environment.

  8. Applications of artificial neural networks (ANNs) in food science.

    Science.gov (United States)

    Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

    2007-01-01

    Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

  9. Qualitative classification of milled rice grains using computer vision and metaheuristic techniques.

    Science.gov (United States)

    Zareiforoush, Hemad; Minaei, Saeid; Alizadeh, Mohammad Reza; Banakar, Ahmad

    2016-01-01

    Qualitative grading of milled rice grains was carried out in this study using a machine vision system combined with some metaheuristic classification approaches. Images of four different classes of milled rice including Low-processed sound grains (LPS), Low-processed broken grains (LPB), High-processed sound grains (HPS), and High-processed broken grains (HPB), representing quality grades of the product, were acquired using a computer vision system. Four different metaheuristic classification techniques including artificial neural networks, support vector machines, decision trees and Bayesian Networks were utilized to classify milled rice samples. Results of validation process indicated that artificial neural network with 12-5*4 topology had the highest classification accuracy (98.72 %). Next, support vector machine with Universal Pearson VII kernel function (98.48 %), decision tree with REP algorithm (97.50 %), and Bayesian Network with Hill Climber search algorithm (96.89 %) had the higher accuracy, respectively. Results presented in this paper can be utilized for developing an efficient system for fully automated classification and sorting of milled rice grains.

  10. Methods and experiments of obtaining corn population based on machine vision%基于机器视觉的玉米植株数量获取方法与试验

    Institute of Scientific and Technical Information of China (English)

    贾洪雷; 王刚; 郭明卓; Dylan Shah; 姜鑫铭; 赵佳乐

    2015-01-01

    获得田间的玉米植株数量对于优化不同玉米品种的种植密度有重要意义,玉米植株数量也是计算新玉米品种平均每株产量的重要参数。为了减轻人工获得玉米植株数量的劳动强度,提高数据的准确率,该文利用基于机器视觉的图像处理技术来获得玉米植株数量。被留高茬玉米收获机作业之后的地块,有一定高度的玉米秸秆站立在地表,摄录这样的图像信息可以大大简化图像处理的难度,提高结果的精确度,所以将图像采集装置安装在留高茬玉米收获机之后来获得视频流。后处理过程中,将视频文件分解为图片文件,然后将真彩色的RGB图片文件转化成灰度图像进行图片的配准,再将灰度图像转化为二值图像进行图像分割与边界提取,最后找到玉米秸秆断面的几何中心并进行标记,统计标记结果即获得玉米植株数量。试验结果显示,人工播种与机械播种在图像识别的误差上没有显著差异(P>0.05);机器视觉识别出来的玉米植株数量与实际数量也没有显著差异(P>0.05),其平均误差为6.7%;并且该误差不会随着图像中玉米植株数量的增加而产生积累。该文的设计可以降低机器视觉在识别玉米植株数量过程中的难度,提高图像识别的准确度,更好地服务生产实际问题。%It is very important to count corn population for optimizing plant density of each corn variety, and corn population is also a very important parameter for calculating average yield of each corn plant. Generally speaking, there are three methods to count corn population, which are based on mechanism, photoelectric technology and machine vision separately. In order to decrease the labor intensity and improve the accuracy, image identifying technology is used in this paper to obtain corn population. As corn seedling and weeds have some similarities, and not every corn

  11. Living with vision loss

    Science.gov (United States)

    Diabetes - vision loss; Retinopathy - vision loss; Low vision; Blindness - vision loss ... Low vision is a visual disability. Wearing regular glasses or contacts does not help. People with low vision have ...

  12. Moving Obstacle Detection Based on Machine Vision for Agricultural Mobile Robot%基于机器视觉的农业机器人运动障碍目标检测

    Institute of Scientific and Technical Information of China (English)

    周俊; 程嘉煜

    2011-01-01

    The robotic ego-motion and the motion of moving obstacle were overlapped when an agricultural mobile robot need to detect the moving obstacle based on machine vision. So two images were taken from the mobile robot and the Harris feature points were extracted and matched. Then a bilinear model was applied to model the movement between the two images, and a least square optimization method was used to calculate the model parameters. A transformation matrix was obtained with this model to compensate the first image to eliminate the effect of the ego-motion of the mobile robot. Finally, a frame difference between the compensated image and the second image was carried out to detect the moving obstacle in the environment. Experimental results showed that this algorithm could eliminate the image movement caused by the ego-motion of the mobile robot, and the moving obstacles were able to be detected effectively with machine vision for the agricultural mobile robot.%在农业移动机器人平台上运用机器视觉技术检测作业环境中是否存在运动障碍目标时,机器人自身运动会与障碍目标运动叠加在一起.为此,首先在移动机器人平台上连续采集两帧图像,提取其特征点并加以匹配;然后应用双线性模型描述对应特征点在图像之间的运动特性,并用最小二乘法对模型参数进行最优估计,得到两帧图像之间的变换矩阵;最后利用此变换矩阵补偿前帧图像来消除机器人自身运动的影响,再与后帧图像作帧差,在线检测出运动障碍目标.实验结果表明,该方法仅依据图像信息即可有效地检测出农业机器人导航环境中存在的运动障碍目标.

  13. Potato grading method of weight and shape based on imaging characteristics parameters in machine vision system%基于机器视觉图像特征参数的马铃薯质量和形状分级方法

    Institute of Scientific and Technical Information of China (English)

    王红军; 熊俊涛; 黎邹邹; 邓建猛; 邹湘军

    2016-01-01

    马铃薯自动分级过程中,存在既要保证分级精度又对分级速度有一定要求的难点问题。该文探讨了利用机器视觉技术快速获取马铃薯图像特征参数,结合多元线性回归方法,建立马铃薯质量和形状分级预测模型,实现基于无损检测的马铃薯自动分级。搭建了同时获取马铃薯三面投影图像的机器视觉系统,通过图像数据处理获得马铃薯俯视图像轮廓面积、两侧面图像轮廓面积、俯视及侧面图像外接矩形长度及宽度数据等图像特征参数,通过多元数据回归分析,建立了马铃薯质量和形状分级预测模型。选择100个试验样本运用该方法进行质量和形状分级模型构建和预测,采用电子称获取样本实际质量,采用目测法对马铃薯进行形状分选。对比试验结果表明,质量分级相关度系数R为0.991,形状分级分辨率为86.7%。表明该方法对马铃薯质量和形状分级进行预测具有可行性,可运用于马铃薯自动分选系统中。%Potato is cultivated as a major food resource in China. Manual grading is labor intensive. Machine vision system is one of the modern grading techniques and is becoming research focus. Weight and shape of potato are important indexes to divide potato grade. Generally, weight and shape of potato have significant positive correlation with outside dimension parameters of potatoes. It is the key to increase potato grading accuracy and speed in order to quickly obtain the imaging feature data possessing high correlation with potato weight and shape and to establish a strong correlation predictions estimation model for potato weight and shape. The focus of this research was to develop a potato grading method of weight and shape by means of image processing in the machine vision system. Firstly, the machine vision system was established, which can capture a potato’s three projection images simultaneously using a V

  14. Automated science target selection for future Mars rovers: A machine vision approach for the future ESA ExoMars 2018 rover mission

    Science.gov (United States)

    Tao, Yu; Muller, Jan-Peter

    2013-04-01

    The ESA ExoMars 2018 rover is planned to perform autonomous science target selection (ASTS) using the approaches described in [1]. However, the approaches shown to date have focused on coarse features rather than the identification of specific geomorphological units. These higher-level "geoobjects" can later be employed to perform intelligent reasoning or machine learning. In this work, we show the next stage in the ASTS through examples displaying the identification of bedding planes (not just linear features in rock-face images) and the identification and discrimination of rocks in a rock-strewn landscape (not just rocks). We initially detect the layers and rocks in 2D processing via morphological gradient detection [1] and graph cuts based segmentation [2] respectively. To take this further requires the retrieval of 3D point clouds and the combined processing of point clouds and images for reasoning about the scene. An example is the differentiation of rocks in rover images. This will depend on knowledge of range and range-order of features. We show demonstrations of these "geo-objects" using MER and MSL (released through the PDS) as well as data collected within the EU-PRoViScout project (http://proviscout.eu). An initial assessment will be performed of the automated "geo-objects" using the OpenSource StereoViewer developed within the EU-PRoViSG project (http://provisg.eu) which is released in sourceforge. In future, additional 3D measurement tools will be developed within the EU-FP7 PRoViDE2 project, which started on 1.1.13. References: [1] M. Woods, A. Shaw, D. Barnes, D. Price, D. Long, D. Pullan, (2009) "Autonomous Science for an ExoMars Rover-Like Mission", Journal of Field Robotics Special Issue: Special Issue on Space Robotics, Part II, Volume 26, Issue 4, pages 358-390. [2] J. Shi, J. Malik, (2000) "Normalized Cuts and Image Segmentation", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 22. [3] D. Shin, and J.-P. Muller (2009

  15. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  16. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  17. Tests of Machine Intelligence

    CERN Document Server

    Legg, Shane

    2007-01-01

    Although the definition and measurement of intelligence is clearly of fundamental importance to the field of artificial intelligence, no general survey of definitions and tests of machine intelligence exists. Indeed few researchers are even aware of alternatives to the Turing test and its many derivatives. In this paper we fill this gap by providing a short survey of the many tests of machine intelligence that have been proposed.

  18. 基于机器视觉技术的智能停车管理系统的研究%Research on intelligent parking management system based on machine vision

    Institute of Scientific and Technical Information of China (English)

    王冰洋; 张崎

    2012-01-01

    In order to solve the surge of the parking space and capacity expansion, the application of machine vision technology has great significance to improve development of intelligent transportation. This paper provides an implement method, including vehicle detection module, license plate recognition module, parking detection module and vehicle tracing module of intelligent parking system. The vehicle detection module, license plate recognition module, and parking detection module in the system go through system testing, and get a reasonable result.%基于机器视觉技术的智能停车管理系统的研究是为了解决城市停车场激增、停车管理效率低下而涉及的一种智能交通系统的应用发展领域.现提出了一种由车辆检测模块、车牌识别模块、车位查询模块及车辆跟踪模块所构成的智能停车场管理系统,并对其中的车牌定位检测及识别以及车位查询模块进行了相应测试,结果较为合理.

  19. Automatic Defect lnspection of PCB Based on Machine Vision Technology%基于机器视觉技术的印制电路板自动检测研究

    Institute of Scientific and Technical Information of China (English)

    汤宏亮

    2015-01-01

    ln this paper,applying to image acquisition,image processing,image recognition to design a printed circuit board defects automatic detection system based on machine vision technology,in which the image processing software as part of the core of this issue,focusing on the key functional modules include Grayhound image filtering,image sharpening,im-age recognition several parts design and programming,and complete visual C ++ based visual programming dialog.%通过图像采集、图像处理、图像识别设计一套基于机器视觉技术的印刷电路板缺陷的自动检测系统,其中图像处理软件部分作为该课题的核心,着重研究了其关键功能模块包括图像灰度化、图像滤波、图像锐化、图像识别几个部分设计与编程,并完成Visual C++基于对话框的可视化编程。

  20. Measurement System of Quartz Mound's Vertical Status Based on Machine Vision Technique%基于机器视觉技术的石英砣垂直状态测量系统

    Institute of Scientific and Technical Information of China (English)

    邓彬; 于洪明; 王明昱; 李硕

    2014-01-01

    This paper introduces an auto inspection system of quartz mound's vertical status based on machine vision technique. The system of image acquisition, processing and controlling is composed of image sensors of array CCD (type:MINTRON 220X) and image acquisition card ( type: OKMC10A) . The system overcomes disadvantages of inefficiency by personal inspection and the low-level of precision. The accuracy of measurement, production efficiency and automaticity are improved greatly by this system.%介绍了基于机器视觉技术的石英砣垂直状态自动检测系统。以面阵CCD 型号为MINTRON 220 X 及OKMC10 A采集卡为核心器件构成的图像采集、处理及控制系统,克服了人工视觉测量效率低、精度不高等缺点,大大提高了企业的生产效率和自动化程度。

  1. 基于机器视觉的井下猴车钢丝绳检测系统%Detection System of Steel wire of Monkey Car in Mine based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    涂帅

    2013-01-01

    The steel wire is widely used in monkey car in mine.At long-term operation,danger of the steel wire wears and fracture existing in monkey car.To solve this problem, a detection method of steel wire crack based on Machine Vision is proposed.The image is acquired by CCD camera,and the crack is detected by edge detection.The alarm is occurred when crack is detected and the alarm is handed down to the upper computer.Experimental result shows that precision of the detection system is high,and solve the safe transportation problem of monkey car greatly.%  井下猴车广泛采用无极钢丝绳,长期运作存在钢丝绳磨损、断裂等安全隐患,针对这一问题,提出了一种基于机器视觉的检测方法,采用边缘检测算法对CCD采集的图像进行缺陷检测,并产生报警信号传送到上位机。实验结果表明该套检测系统检测精度高,极大地解决了猴车的安全运输问题。

  2. Design and Application of Gun Type Micro Resistance Welding System Based on Machine Vision%基于机器视觉的枪式微型电阻焊接系统设计与应用

    Institute of Scientific and Technical Information of China (English)

    乔凤斌; 张松; 郭立杰

    2013-01-01

    Machine vision has a broad and important applications in industry, using CCD visual sensor collection the spot information in welding, thereby determining the solder joint pixel coordinates, and converted to the actual spatial coordinates, and then control the welding torch is moved to the top spot, achieving the purpose of automatic welding. The welding system for solar array efficient automated assembly and welding, which improved the solar array solder joint bearing capacity, extreme temperature mechanics performance, reliability, conductive and has the important significance.%基于机器视觉在工业上的广泛应用,通过采用CCD视觉传感器在焊前采集焊点的图像信息来确定焊点的像素坐标,并将其转换为实际的空间位置坐标,然后控制焊枪移动到焊点的正上方,达到自动焊接的目的.该焊接系统的研制对实现太阳电池阵的高效自动化组装和焊接,提高太阳电池阵焊点的承载能力、极端温度下的力学性能、可靠性、导电性等具有重要意义.

  3. Micro Vision

    OpenAIRE

    Ohba, Kohtaro; OHARA, Kenichi

    2007-01-01

    In the field of the micro vision, there are few researches compared with macro environment. However, applying to the study result for macro computer vision technique, you can measure and observe the micro environment. Moreover, based on the effects of micro environment, it is possible to discovery the new theories and new techniques.

  4. 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

  5. Sorting System Algorithms Based on Machine Vision for Delta Robot%基于机器视觉的Delta机器人分拣系统算法

    Institute of Scientific and Technical Information of China (English)

    倪鹤鹏; 刘亚男; 张承瑞; 王云飞; 夏飞虎; 邱正师

    2016-01-01

    To overcome the repeat shooting to workpieces by vision system in sorting process, an image deduplication algorithm based on time and workpieces’ positions is proposed. The running time of the real-time sorting system is used as basis of each sorting module, and the predicted time that workpieces arrive at a fixed reference position is combined with its current location into a set of coordinates to uniquely identify a part. So the duplicate image information can be found and removed by comparing those coordinates periodically. At the same time, in order to improve sorting efficiency, a dynamic picking algorithm based on Newton-Raphson method is proposed. The non-linear mathematical model is established for workpiece tracking, which is solved by Newton-Raphson iteration. Finally, the proposed dynamic picking algorithm is verified by MATLAB. In prototype test the maximum sorting speed can reach 110 times per minute, mistaken-grab rate is lower than 2‰, missing-grab rate is 0, which proves that the algorithms can meet the real-time, the accuracy and the stability requirements.%针对分拣过程中视觉系统对工件的重复拍摄问题,提出一种基于时间与工件位置的图像去重复算法,以实时分拣系统的系统运行时刻作为各单元的时间基准,将预测的工件到达某一固定参考位置的时刻与工件当前位置组合成一组能唯一识别工件的坐标,经周期性比较,判断并去掉重复图像信息。同时为提高分拣效率,提出一种基于牛顿-拉夫森迭代的动态抓取算法,建立了机器人跟踪工件的数学模型,并通过牛顿-拉夫森方法求解该非线性数学模型。最后用MATLAB对动态抓取算法进行了验证。样机实验中最快分拣速度达110次/min,误抓率小于2‰,漏抓率为0,证明了算法能够满足实时性要求,同时具有较高的准确性和稳定性。

  6. Novel Method for Measuring the Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters Based on Artificial Neural Networks and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhijian Liu

    2015-08-01

    Full Text Available The determinations of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, which also wastes too much time and manpower. To address this problem, we propose machine learning models including artificial neural networks (ANNs and support vector machines (SVM to predict the heat collection rate and heat loss coefficient without a direct determination. Parameters that can be easily obtained by “portable test instruments” were set as independent variables, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, final temperature and angle between tubes and ground, while the heat collection rate and heat loss coefficient determined by the detection device were set as dependent variables respectively. Nine hundred fifteen samples from in-service water-in-glass evacuated tube solar water heaters were used for training and testing the models. Results show that the multilayer feed-forward neural network (MLFN with 3 nodes is the best model for the prediction of heat collection rate and the general regression neural network (GRNN is the best model for the prediction of heat loss coefficient due to their low root mean square (RMS errors, short training times, and high prediction accuracies (under the tolerances of 30%, 20%, and 10%, respectively.

  7. Learning Spatial Object Localization from Vision on a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Jürgen Leitner

    2012-12-01

    Full Text Available We present a combined machine learning and computer vision approach for robots to localize objects. It allows our iCub humanoid to quickly learn to provide accurate 3D position estimates (in the centimetre range of objects seen. Biologically inspired approaches, such as Artificial Neural Networks (ANN and Genetic Programming (GP, are trained to provide these position estimates using the two cameras and the joint encoder readings. No camera calibration or explicit knowledge of the robot's kinematic model is needed. We find that ANN and GP are not just faster and have lower complexity than traditional techniques, but also learn without the need for extensive calibration procedures. In addition, the approach is localizing objects robustly, when placed in the robot's workspace at arbitrary positions, even while the robot is moving its torso, head and eyes.

  8. 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.

  9. Determinación por Visión Artificial del Factor de Degradación en Aleaciones Biocompatibles Computer Vision for Determination of Degradation Factor in Biocompatible Alloys

    Directory of Open Access Journals (Sweden)

    Willian Aperador-Chaparro

    2013-01-01

    Full Text Available Se determinó por visión artificial el factor de degradación de una aleación biocompatible, AISI 316LVM. Para ello, se utilizó una solución fisiológica simulada (solución de Hanks, electrolito que simula la composición presente en el organismo, es decir, el ambiente donde el implante se utilizará. El comportamiento electroquímico fue evaluado mediante curvas potencio-dinámicas. La caracterización superficial se desarrolló mediante un estereoscopio y los productos de corrosión se evaluaron mediante difracción de rayos X. El sistema usó una imagen microscópica de la superficie del material en su estado natural (brillo espejo como parámetro base para la comparación, para definir en qué estado se encuentran las muestras una vez han pasado por las pruebas realizadas. Se encontró, que es posible estimar el factor de degradación o de deterioro en un material mediante un análisis topográfico del mismo.The degradation factor of a biocompatible alloy, AISI 316LVM, was determined by computer vision. For this, a simulated physiological solution (Hanks' solution which simulates the electrolyte composition in the body, that is the environment in which the implant is used. The electrochemical behavior was evaluated by potentio-dynamic curves. The surface characterization was performed using a stereoscope and corrosion products were evaluated by X-ray diffraction. The system used a microscopic image of the surface of the material in its natural state (mirror finish as a basis for comparison parameter to define what state are once samples have undergone testing. It was found that it is possible to estimate the factor of degradation or deterioration of a material through a topographic analysis.

  10. Online grading method for tissue culture seedlings ofSpathiphyllum floribundum based on machine vision%基于机器视觉的白掌组培苗在线分级方法

    Institute of Scientific and Technical Information of China (English)

    杨意; 初麒; 杨艳丽; 张祥接; 徐祥朋; 辜松

    2016-01-01

    白掌在观叶类花卉中占有很大比例,其育苗多采用组织栽培法,且组培苗生产具有规模化。为提高成苗出苗品质,需要在组培苗炼苗前对其分级,而目前常用分级法不能有效解决自然状态下水平放置的白掌组培苗存在的叶片扭曲和重叠问题,因此该文提出一种基于机器视觉实现白掌组培苗在线分级的方法,通过对自然状态下水平放置的白掌组培苗的叶片面积、苗高、地径以及投影面积的分析,得到其投影面积与叶片面积呈线性关系,相关度为0.9344;投影面积与地径呈多项式函数关系,相关性为0.9067,故确定组培苗投影面积和苗高为实际生产中的分级指标。该文采用基于颜色模板匹配算法测量组培苗投影面积,得到的叶片面积和地径与实际叶片面积和地径的变异系数相对误差分别为0.35%和7.95%;利用最小外接矩形法(MBR,minimum bounding rectangle)测量苗高,得到的苗高和实际苗高变异系数相对误差为1.44%。通过整机分级试验发现在输送间距为0.25 m,输送速度为0.5 m/s,分级级别为3级的条件下,该分级装置的分级成功率可达96%,对应生产率为7200株/h。%At present, most of young plants ofSpathiphyllum floribundum are breeding by the technique of tissue culture. Due to absence of grading machine specially designed for primary-growth plants that is small, irregular and young, the grading of tissue culture seedlings are normally handled manually. In this paper, we proposed an automated online grading method for Spathiphyllum floribundum tissue culture seedlings based on the technique of machine vision. SinceSpathiphyllum floribundum is a foliage flower, the leaf area is one of the most important parameters in grading, along with seedling height and diameter. Direct measurement not only would do damage to young plant because of its tenderness, but also the manpower productivity

  11. What Is Low Vision?

    Science.gov (United States)

    ... Condition Eye Health Low Vision What Is Low Vision? What "Low Vision" Means Signs and Symptoms of ... Services The Low Vision Pilot Project What "Low Vision" Means As we age, our eyes change too. ...

  12. All Vision Impairment

    Science.gov (United States)

    ... Home > Statistics and Data > All Vision Impairment All Vision Impairment Vision Impairment Defined Vision impairment is defined as the ... Ethnicity 2010 U.S. Age-Specific Prevalence Rates for Vision Impairment by Age and Race/Ethnicity Table for ...

  13. Healthy Living, Healthy Vision

    Science.gov (United States)

    ... Financial Assistance Information Vision Screening and Eye Exams Zika Virus and Vision Eye Problems Eye Problems Amblyopia ( ... Eye Health Report Reports and External Resources The Cost of Vision Problems The Future of Vision Vision ...

  14. Pregnancy and Your Vision

    Science.gov (United States)

    ... Financial Assistance Information Vision Screening and Eye Exams Zika Virus and Vision Eye Problems Eye Problems Amblyopia ( ... Eye Health Report Reports and External Resources The Cost of Vision Problems The Future of Vision Vision ...

  15. 基于机器视觉的燃料电池MEA贴片方案设计%Scheme design for fuel cell MEA placement based on machine vision

    Institute of Scientific and Technical Information of China (English)

    张步阳; 梅爽; 陈伟; 王瑜辉

    2014-01-01

    According to the placement processes for gas diffusion layer and the catalyst layer in the fuel cell membrane electrode assembly,gives a placement scheme with automatic deviation-correcting function .At first,a mechanical unit with multi degrees of freedom was given .This unit was a manipulator using vacuum adsorption technology .Then a fusion estimation algorithm based on pseudo-omnidirectional vision for autonomous mobile robot self-motion was proposed .Then the IPC obtained the location informa-tion of the gas diffusion layer and the catalyst layer using machine vision technology .In addition,the reason for affecting the placement precision was analyzed and the solution of this problem was put forward .At last,the IPC controlled the motor moving to paste accurately .Experimental results show that this automatic correction scheme not only has high placement precision but also has the good stability and reproducibility .%针对燃料电池膜电极组件中气体扩散层与催化剂层的贴片工艺,提出了一种具有自动纠偏功能的贴片方案。首先,针对贴片工艺给定机械结构,该结构为具有真空吸附功能的多自由度机械手。然后,采用机器视觉技术获得气体扩散层与催化剂层的位置信息,分析影响贴片精度的原因,并针对该机械结构提出了相应的贴片算法。最后,控制各轴电动机的运动实现精确层合。实验结果表明,该方案的精度符合要求,并具有良好的稳定性和可重复性。

  16. Anti-shake and coordinate interpolation techniques in machine vision electronic whiteboard system application%机器视觉电子白板系统的防抖与坐标插值技术

    Institute of Scientific and Technical Information of China (English)

    周祖微; 刘森; 王忆文; 李辉

    2012-01-01

    在基于机器视觉的电子白板系统应用中,为了消除各种因素导致的触控点抖动,提出了一种改进的均值滤波的防抖方法.为了突破硬件设备的限制提高系统工作的流畅性,采用了一种基于曲线拟合的坐标插值方法来提高系统实时性并平滑处理触控点的运动轨迹.实验结果表明:触控点的抖动情况得到了消除,在摄像头最高工作频率60fps的情况下,系统能以每秒输出180个触控点坐标的速度实时工作,在不增加硬件成本的情况下提高了系统实时性.%In the electronic whiteboard system based on machine vision, an improved mean filter was proposed to eliminate touching-point jitter. In order to enhance the working fluency without hardware restrictions, a coordinate interpolation based on curve-fitting was adopted to improve the real-time performance of the whole system and smooth the trajectory of moving touching-point. The experimental results show that: on one hand, touching-point jitter can be eliminated. On the other hand, the system can output 180 touching-point coordinates per second when the camera works at its highest speed of 60 frame per second. The real-time performance of the whole system gets effectively improved without any new hardware cost.

  17. 基于机器视觉的高密度电路板缺陷检测系统%Defects Inspection System of HID PCB Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    熊光洁; 马树元; 聂学俊; 武思远; 汤晓华

    2011-01-01

    An improved automated optical inspection system (AOI) is researched to decrease defects false alarm rate of HDI PCB. With a new multicolor LED illuminator, the system can capture the tested PCB image by using machine vision, and identify the various defects quickly and accurately through image processing software systems in this paper. The performance system of this AOI has been greatly im-proved by using improved hardware system and algorithms which was programmed on OPENCV platform by using the colorful information of captured images. The 36300 testing points of 30 HDI PCB are detected, and the results of this experiment prove that the PCB defect detection rate of the AOI inspection system is improved to 99. 87% and the false alarm rate of defects down to 0. 32%.%为减少高密度电路板的缺陷误报率,研究一种新型自动光学检测系统(AOI);系统采用自行研制的多色LED照明系统,利用机器视觉获取被测PCB的图像,通过图像处理软件系统快速准确地识别出各种缺陷;系统利用获取的彩色图像信息,根据各种缺陷的特征信息不同,采用OPENCV对各种缺陷的检测算法进行改进,使得系统性能有很大改进;对30块同类HDI型PCB的36300个检测点进行测试,测试结果证明,系统PCB缺陷的检出率高达99.87%,误报率只有0.32%.

  18. Color Detection Method for Gas Generator of Safety Belt Based on Machine Vision%基于机器视觉的安全带气体发生器颜色检测方法

    Institute of Scientific and Technical Information of China (English)

    于保军

    2016-01-01

    The purpose was to measure the color of safety belt’ s gas generator by the method of machine vision. First, color CCD camera was use to get the color images of the components. Then the software ( NI LabVIEW) was used to process those images easily. The color cast adjustment of those images and image filtering were made to get the desired images. Then the color values of different gas generators were saved as standard templates. The values of the template were matched with the detecting members to determine the com⁃ponent’ s color.%对基于机器视觉的汽车安全带气体发生器的颜色检测方法进行研究,研究的目的是检测出该元件的颜色信息。使用的方法是:采用彩色CCD相机获得被检测元件的彩色图像;对获取到的彩色图像使用美国NI公司的LabVIEW软件及其图像处理模块来实现彩色图像的色偏调整、彩色图像的滤波处理等操作后获得可用于检测的理想彩色图像;将获取到的各种不同的气体发生器的颜色图片保存为标准模板,之后检测到的元件与标准模板之间通过颜色距离计算的方法相匹配就可以检测出该元件的颜色。

  19. Development of the railway freight log scaling system based on machine vision%基于机器视觉的铁路货运木材检尺系统开发

    Institute of Scientific and Technical Information of China (English)

    王纪武; 高伟杰; 廖方波; 李建勇

    2012-01-01

    利用三角测量原理,采用图像处理技术,解决了基于机器视觉木材检尺技术的难点问题.实验结果表明:开发的检尺系统可直接确定目标面到相机镜头间的距离,并且能够与机器视觉检尺无缝融合,与其他测距传感器相比,该系统成本低,不仅适合单根等小批量的木材检尺要求,而且适合大批量的铁路货运木材的检尺工作.%The conventional log scaling, which is done with a tape measure by manual operation in order to get higher accuracy, is carried out by more workers working hard for a longer time. It is difficult 10 realize systematic and scientific management. Based on machine vision, a new log scaling system is developed. The distance between the log-end and camera is calculated directly by the image processing with a point laser according to the principle of triangulation. Moreover, the distance calculation can be done with other image processing simultaneously. With this technique, the developed log scaling system can be used not only for scaling a single log one by one, but also for scaling bundles of logs at the same time.

  20. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  1. Research on Maize Leaf Recognition of Characteristics from Transmission Image Based on Machine Vision%基于机器视觉的玉米叶片透射图像特征识别研究

    Institute of Scientific and Technical Information of China (English)

    唐俊; 邓立苗; 陈辉; 栾涛; 马文杰

    2014-01-01

    The purpose of the study was to create database of characteristics from maize leaf transmission images, analyze the rules of characteristics variation with maize varieties and the recognition results of different types of characteristics in order to provide a basis for further research of identifying maize varieties from leaf transmission image of different growth periods based on machine vision. [Method] Twenty-one common varieties of maize were selected as the research materials. The maize leaves at jointing stage, small bell stage, large bell stage and tasselling stage were collected. A total of 420 high quality transmission images of maize leaves were taken in lamp box. The software for characteristic extraction and recognition of maize leaves was designed and developed based on Matlab R2009a, which included image preprocessing module, characteristic extraction module, neural network recognition module and threshold selection module. The transmission images of maize leaves at jointing stage, small bell stage, large bell stage and tasselling stage were pre-processed by the software. Then 48 characteristics of color group, shape group and texture group were extracted from transmission images of maize leaf, and a total of 20 160 characteristic data. In order to study the rules of characteinristics variation with maize varieties, the coefficient of variation of 48 characteristics of leaf transmission image among different maize varieties were analyzed. In order to search the important characteristics with strong ability of identifying maize varieties from transmission images of leaves, the Artificial Neural Network was built and the recognition rate of single characteristics from different time were analyzed. In order to study the recognition results, the recognition rates of the three groups of characteristics and the group combinations of characteristics from different time were further analyzed. [Result] The results in 4 stages indicated that there were

  2. Artificial Intelligence in Tele-Vision

    Directory of Open Access Journals (Sweden)

    S.Praveenkumar,

    2010-11-01

    Full Text Available The digital television (DTV semiconductor market is expected to grow to $7.7billion in 2010 and to $10 billion in 2013, an 18% CAGR. Flat screen DTV semiconductor revenue will grow to $6.9 billion in 2010 and to $9 billion in 2013, a 25% CAGR.. The above mentioned numbers provide huge opportunity for TV vendors but in a highly-competitive environment. Introducing value added features is one of the ways to address the intense competition. Increase in the number of television channels and programs have provided a number of choices to the consumer, which has led to confusion. The user interested favorite item can be a song, a comedy scene. This may be transmitted in a particular channel while he is viewing another one and the user might end up missing his favorite program .This write-up proposes a solution by which the manufacturer will be able to provide an advanced feature, which ensures the consumers get a great experience without missing their favorites.

  3. Introduction to Concepts in Artificial Neural Networks

    Science.gov (United States)

    Niebur, Dagmar

    1995-01-01

    This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

  4. Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine

    Science.gov (United States)

    Acharya, Nachiketa; Shrivastava, Nitin Anand; Panigrahi, B. K.; Mohanty, U. C.

    2014-09-01

    The south peninsular part of India gets maximum amount of rainfall during the northeast monsoon (NEM) season [October to November (OND)] which is the primary source of water for the agricultural activities in this region. A nonlinear method viz., Extreme learning machine (ELM) has been employed on general circulation model (GCM) products to make the multi-model ensemble (MME) based estimation of NEM rainfall (NEMR). The ELM is basically is an improved learning algorithm for the single feed-forward neural network (SLFN) architecture. The 27 year (1982-2008) lead-1 (using initial conditions of September for forecasting the mean rainfall of OND) hindcast runs (1982-2008) from seven GCM has been used to make MME. The improvement of the proposed method with respect to other regular MME (simple arithmetic mean of GCMs (EM) and singular value decomposition based multiple linear regressions based MME) has been assessed through several skill metrics like Spread distribution, multiplicative bias, prediction errors, the yield of prediction, Pearson's and Kendal's correlation coefficient and Wilmort's index of agreement. The efficiency of ELM estimated rainfall is established by all the stated skill scores. The performance of ELM in extreme NEMR years, out of which 4 years are characterized by deficit rainfall and 5 years are identified as excess, is also examined. It is found that the ELM could expeditiously capture these extremes reasonably well as compared to the other MME approaches.

  5. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  6. 基于机器视觉的作物多姿态害虫特征提取与分类方法%Feature extraction and classification method of multi-pose pests using machine vision

    Institute of Scientific and Technical Information of China (English)

    李文勇; 李明; 陈梅香; 钱建平; 孙传恒; 杜尚丰

    2014-01-01

    Pest identification and classification is time-consuming work that requires expert knowledge for integrated pest management. Automation, including machine vision combined with pattern recognition, has achieved some applications in areas such as fruit sorting, robotic harvesting, and quality detection, etc. Automatic classification and counting of pests using machine vision is still a challenge because of variable and uncertain poses of trapped pests. Therefore, using Pseudaletia separata, Conogethes punctiferalis, Helicoverpa armigera, Agrotis ypsilon with different poses as research objects, this paper presents a novel classification method for multi-pose pests based on color and texture feature groups and using a multi-class support vector machine. 320 images were taken using field samples with an original resolution of 4 288×2 848. The subimages of pests with 640×640 pixel size were obtained from original images for computational efficiency. Color features in RGB and HSV spaces, statistical texture features, and wavelet-based texture features were extracted. Six feature vector groups were constructed using those features. In order to select effective feature parameters of each group, a genetic algorithm was designed to optimize feature vectors based on 10-fold cross-validation. Finally, the one-against-one DAGMSVM (acronym as yet undefined) algorithm was applied to classify and recognize the four kinds of target pests and to find the best feature group. 80 images (60 for the training set and 20 for the testing set) were adopted for each species. Parameter numbers were calculated and analyzed after optimization, thus the best parameters were selected for each group. The training time of the SVM model and classification accuracy, which contains false negative and false positive details, were compared between pre-optimization and post-optimization. The results showed that the highest parameter optimization ratio is from the sixth feature group with a dimension

  7. Identification of Fungi by Machine Vision

    DEFF Research Database (Denmark)

    Dørge, Thorsten Carlheim; Carstensen, Jens Michael

    1999-01-01

    This paper presents some methods for identification and classification of fungal colonies into species solely by means of digital image analysis without any additinal chemical analysis needed. The methods described are completly automated hence objective once a digital image of the fungus has bee...

  8. Close range photogrammetry and machine vision

    CERN Document Server

    Atkinson, KB

    1996-01-01

    This book presents the methodology, algorithms, techniques and equipment necessary to achieve real time digital photogrammetric solutions, together with contemporary examples of close range photogrammetry.

  9. Backlit Keyboard Inspection Using Machine Vision

    Institute of Scientific and Technical Information of China (English)

    Der-Baau Perng; Hsiao-Wei Liu; Po-An Chen

    2015-01-01

    Abstract⎯A robust system for backlit keyboard inspection is revealed. The backlit keyboard not only has changeable diverse colors but also has the laser marking keys. The keys on the keyboard can be divided into regions of function keys, normal keys, and number keys. However, there might have some types of defects: incorrect illuminating area, non-uniform illumination of specified inspection region (IR), and incorrect luminance and intensity of individual key. Since the illumination features of backlit keyboard are too complex to inspect for human inspector in the production line, an auto-mated inspection system for the backlit keyboard is proposed in this paper. The system was designed into the operation module and inspection module. A set of image processing methods were developed for these defects inspection. Some experimental results demonstrate the robustness and effectiveness of the proposed system.

  10. Shape Parameter of Micro Part Detection Method Based on Machine Vision%基于机器视觉的微小零件形貌检测方法

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    针对当前工业生产中人工对微小异形零件形貌参数测量精度低、速度慢的问题,提出了一种基于机器视觉的检测方法,并开发了一款基于开源计算机视觉库OpenCV的检测软件。该检测方法首先使用CMOS相机采集被测零件的图像,并结合频谱特征对其进行滤波、阈值分割等预处理;然后选取效率高、边缘跨度为单像素的Canny边缘检测算法对预处理之后的图像进行边缘检测;最后采用Ramer算法对零件轮廓进行递归细分,拟合出几何基元,并结合测量焦距下的系统标定系数计算出零件实际的形貌参数。实验结果表明:通过该检测方法对长、宽均为毫米量级的Ω型微小零件进行形貌检测,检测精度达到10μm以下,具有精度高、速度快的优点,可为工业化生产提供可靠依据。%Aiming at the faults of low precision and slow speed in the manual measurement of tiny special-shaped com-ponent’s shape parameters in current industrial production, a detecting method based on machine vision was proposed and a detecting software founded on open-source computer vision library OpenCV was programmed. Firstly, the object was imaged with a CMOS sensor and preprocessed with filtering and threshold by the use of spectrum analysis method. And then Canny edge detecting algorithm which is successful in extracting the edges with pixel precision and high effi-ciency was chosen to detect the edge of preprocessed image. In the end,by adopting the Ramer algorithm which per-forms a recursive subdivision of the contour to fit geometric primitives and using system calibration coefficient, the shape parameters of the measured part were obtained. The experimental result shows that through the proposed detec-tion method, the shape parameters of a micro component in the shape of Ω, the length and width of which were in millimeter level which can be acquired. And the detecting precision can reach to a

  11. Design of Intelligent Mobile Fruit Picking Robot—Based on Machine Vision Technology%智能移动式水果采摘机器人设计—基于机器视觉技术

    Institute of Scientific and Technical Information of China (English)

    孙承庭; 胡平

    2016-01-01

    The deepening of industry automation and computer intelligent control makes the intelligent robot in various fields of application very widespread ,the development of science and technology drives the development of society .China's vast most of the fruit picking work is still done manually .With the rapid development of China's social and economic , the wages of the workers continues to rise , manual picking fruit increased the fruit of economic cost and the demand of robot in the field of agriculture ,so it is becoming more and more urgent .In this paper , based on machine vision technology de-sign and research on the intelligent mobile fruit picking robot , and the mobile carrier , mechanical arm , clip holding de-vice , it designed a horizontal moving mechanism and intelligent control module in a body , by using binocular stereo vi-sion technology , the mobile robot's walking path planning , fruit maturity automatically judge and of mature fruit location recognition function for picking fruit .Experiments show that the design of the picking robot can overcome the impact of climate factors , by using visual technology with simple mechanical structure , operation process of stable performance , high efficiency , high reliability , adapt to ability .%自动化和计算机智能控制行业的不断发展,使得智能机器人在各个领域的应用已经十分普遍. 目前,我国绝大部分水果采摘工作依然靠人工完成,随着工人工资不断攀升,人工采摘水果增加了果农的经济成本,机器人在农业领域方面的需求越来越迫切. 为此,基于机器视觉技术设计了智能移动式水果采摘机器人,集可移动载体、机械手臂、夹持器、横向移动机构及智能控制模块于一身,采用双目立体视觉技术,实现了水果采摘机器人移动行走路径的规划、果实成熟度自动判断及对成熟果实定位识别的功能. 试验表明:所设计的采摘机器人采用视觉技术,机械结构

  12. Research on the Prediction of Soft Soil Foundation Settlement Based on Artificial Bee Colony Support Vector Machines%基于ABC-SVM的软基沉降预测研究

    Institute of Scientific and Technical Information of China (English)

    施俊; 高正夏; 徐嵚嵛

    2016-01-01

    沉降预测一直是地基工程的一个重点研究项目.软土具有天然含水量高、塑性指数大、黏粒含量高等特殊的工程特性,因此,建立在软土上的地基沉降难以预测,对于工程建设有一定的隐患.支持向量机在解决样本数量小、非线性问题上有其特有的优势.利用人工蜂群算法对支持向量机的参数进行优化后建立SVM模型,对木兰溪防洪工程的沉降问题进行预测,将其预测结果与传统的支持向量机模型以及曲线拟合预测方法结果进行对比.最终证明了ABC-SVM模型在软基沉降预测上的可用性.%The prediction of the settlement is always an important research topic in foundation engineering. Soft soil has engineering features of high moisture content,high plastic exponent and high clay content,so it is hard to predict the settlement of soft soil foundation which is dangerous to the engineering construction. The support vector machines are good at dealing with problems that are nonlinear and have little sample size. We use artificial bee colony to optimize the selection of support vector machines'parameters to build SVM model. And the model is used to predict the settlement of flood control project in Mulan stream. The predicting outcomes are used to comparing with the traditional support vector machines and the curve-fitting method's outcomes. It turns out the usability of the ABC-SVM in the prediction of soft soil foundation.

  13. Vision Loss, Sudden

    Science.gov (United States)

    ... of age-related macular degeneration. Spotlight on Aging: Vision Loss in Older People Most commonly, vision loss ... Some Causes and Features of Sudden Loss of Vision Cause Common Features* Tests Sudden loss of vision ...

  14. Healthy Vision Tips

    Science.gov (United States)

    ... NEI for Kids > Healthy Vision Tips All About Vision About the Eye Ask a Scientist Video Series ... Links to More Information Optical Illusions Printables Healthy Vision Tips Healthy vision starts with you! Use these ...

  15. Nondestructive Testing of Tomato Growth Information Based on Machine Vision%基于机器视觉的番茄长势信息无损检测的研究

    Institute of Scientific and Technical Information of China (English)

    杭腾; 毛罕平; 张晓东; 胡静

    2015-01-01

    A rapid determination method was using machine vision in a complex natural environment to test tomato stem diameter , plant height and fruit cross-sectional area .Growth information in different growth periods of tomato were ac-quired by using CCD camera , through preprocessing the image by the median filtering method .By extracting the target re-gion by the use of automatic threshold segmentation based on the color of Otsu R-G factor method , the correlation analy-sis of fitting function for the establishment of crop growth parameters and to target image characteristic value to realize ef -fective tomato growth information .The test results show relative error of detection of tomato stem diameter in the seedling stage, blossom and fruit period , fruiting period to be 1.73%~4.04%,0.64%~4.42%,0.46%~4.78%respective-ly.The relative error of plant height and fruit cross-sectional area detection were also found to be:1.2%~6.5%,0.8%~3 .1% respectively .%提出了利用机器视觉的方法在复杂自然条件环境下对番茄的茎粗、株高和果实横截面积进行快速测定方法。通过利用CCD 获取不同生长周期下番茄的长势信息,采用中值滤波方法对图像进行预处理;采用基于 r-g颜色因子的Otsu自动阈值分割法来提取目标区域。同时,通过相关性分析建立作物长势参数与目标图像特征值的拟合函数,实现了番茄长势信息的有效获取。试验结果表明:对番茄茎粗的检测在幼苗期、开花坐果期、结果期的相对误差分别为1.73%~4.04%,0.64%~4.42%,0.46%~4.78%;株高和果实横截面积检测的相对误差分别为1.2%~6.5%,0.8%~3.1%。

  16. Research on the Extension of Dynamic Range of Textile Samples Image Based on Machine Vision%基于机器视觉的纺织样品图像动态范围扩展方法研究

    Institute of Scientific and Technical Information of China (English)

    钟平; 辛斌杰; 周陵君; 朱小龙; 崔瑛

    2011-01-01

    针对目前机器视觉采集纺织样品的图像动态范围低,严重影响对其质量的分析效果,提出一种通过多帧图像融合来改善图像质量的方法.采用对同一视场多帧不同曝光图像加权平均得到融合图像.并在融合算法中,引入数学多元统计主成份分析方法,估计不同光强条件下获取图像的权重.在处理过程中,对协方差矩阵估计权值的方法进行了改进,克服只能对一个图像子块进行统一加权的方式,实现图像中的每个像素都有恰当的权值参与图像融合,实现最大限度保持原始样品图像的信息.实验表明,该方法能显著增强图像细节特征.%The images of textile samples captured by machine vision often have low dynamic range which made the result of quality analysis inaccurate. This paper proposed a novel method to improve the quality of images by image fusion with multi-frame images. In the method, we can get the fused image by weighted average with multi-frame images which have the different exposure in the same view, and in the fusion algorithm, the weight of image under the different light intensity was estimated by the principal component analysis based on mathematical multivariate statistics. In the processing, we improved the method of estimating the weights of covariance matrix, solved the problem that just unified weighting one block of image, and made each pixel of images have the proper weight to participate in image fusion, finally retained the original information of the sample image as mush as possible. Experiments showed that the approach is effective in enhancing the details characteristics of images.

  17. Design and implementation of the RTPS middleware of distributed machine vision systems%分布式机器视觉的RTPS中间件设计与实现研究

    Institute of Scientific and Technical Information of China (English)

    赵雪峰; 殷国富; 罗小川; 仲晓敏

    2011-01-01

    为了满足网络化制造中分布式机器视觉(DMV)对各种数据流的不同通信性能要求,设计了基于实时发布-订阅(RTPS)协议的中间件.通过定义中间件工作过程中的相关控制参数,对数据传输的可靠性、实时性以及网络带宽和内存等资源的使用进行了定量描述和优化.将设计的RTPS中间件应用到网络化制造中的DMV系统,进行了各种类型数据流的不同通信性能实验,包括视觉图像信息数据流,该数据流可以选择异步通信或者同步通信.对系统进行了建模和模拟实验,结果表明,与基于Client/Server的中间件相比,基于RTPS协议的中间件的延迟低,在数据包大小变化时的稳定性强,而且吞吐量很大.可见,所设计的RTPS中间件能保证DMV的实时性、可靠性、动态适应性,以及多节点对多节点的通信要求.%To meet the communication performance requirements of a network-based manufacturing system' s distributed machine vision (DMV) in data flows, the middleware was designed based on the research on the real-time publish-subscribe (RTPS) protocol. Control parameters were introduced to optimize the reliabihty and the real-time of data transmissions,as well as the use of the memory and the network bandwidth. The designed RTPS middleware was applied to a DMV system in the network-based manufacturing environment, and different communication experiments on various types of data streams were completed. In particular, the visual image information data streams could choose the type of asynchronous communication or synchronous communication. The experimental results demonstrate that the RTPS middleware is suitable for the timelines requirements for DMV systems.

  18. International Conference on Computational Vision and Robotics

    CERN Document Server

    2015-01-01

    Computer Vision and Robotic is one of the most challenging areas of 21st century. Its application ranges from Agriculture to Medicine, Household applications to Humanoid, Deep-sea-application to Space application, and Industry applications to Man-less-plant. Today’s technologies demand to produce intelligent machine, which are enabling applications in various domains and services. Robotics is one such area which encompasses number of technology in it and its application is widespread. Computational vision or Machine vision is one of the most challenging tools for the robot to make it intelligent.   This volume covers chapters from various areas of Computational Vision such as Image and Video Coding and Analysis, Image Watermarking, Noise Reduction and Cancellation, Block Matching and Motion Estimation, Tracking of Deformable Object using Steerable Pyramid Wavelet Transformation, Medical Image Fusion, CT and MRI Image Fusion based on Stationary Wavelet Transform. The book also covers articles from applicati...

  19. Parallel Algorithms for Computer Vision.

    Science.gov (United States)

    1989-01-01

    developed algorithms for sev- stage at which they are used, for example by a eral early vision processes, such as edge detection, stere - navigation...system operates by receiving a stream of instructions from its front end computer. A microcontroller receives the instructions, expands each of them...instructions flow into the Connection Machine hardware from the front end. These I macro-instructions are sent to a microcontroller , which expands them

  20. Blindness and vision loss

    Science.gov (United States)

    ... means you cannot see anything and DO NOT see light. (Most people who use the term "blindness" mean ... the vision loss. For long-term vision loss, see a low-vision specialist, who can help you learn to care for yourself and ... of vision; No light perception (NLP); Low vision; Vision loss and blindness ...

  1. Visions and visioning in foresight activities

    DEFF Research Database (Denmark)

    Jørgensen, Michael Søgaard; Grosu, Dan

    2007-01-01

    The paper discusses the roles of visioning processes and visions in foresight activities and in societal discourses and changes parallel to or following foresight activities. The overall topic can be characterised as the dynamics and mechanisms that make visions and visioning processes work...... or not work. The theoretical part of the paper presents an actor-network theory approach to the analyses of visions and visioning processes, where the shaping of the visions and the visioning and what has made them work or not work is analysed. The empirical part is based on analyses of the roles of visions...... and visioning processes in a number of foresight processes from different societal contexts. The analyses have been carried out as part of the work in the COST A22 network on foresight. A vision is here understood as a description of a desirable or preferable future, compared to a scenario which is understood...

  2. Heidegger and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Diaz, G.

    1987-01-01

    The discipline of Artificial Intelligence, in its quest for machine intelligence, showed great promise as long as its areas of application were limited to problems of a scientific and situation neutral nature. The attempts to move beyond these problems to a full simulation of man's intelligence has faltered and slowed it progress, largely because of the inability of Artificial Intelligence to deal with human characteristic, such as feelings, goals, and desires. This dissertation takes the position that an impasse has resulted because Artificial Intelligence has never been properly defined as a science: its objects and methods have never been identified. The following study undertakes to provide such a definition, i.e., the required ground for Artificial Intelligence. The procedure and methods employed in this study are based on Heidegger's philosophy and techniques of analysis as developed in Being and Time. Results of this study show that both the discipline of Artificial Intelligence and the concerns of Heidegger in Being and Time have the same object; fundamental ontology. The application of Heidegger's conclusions concerning fundamental ontology unites the various aspects of Artificial Intelligence and provides the articulation which shows the parts of this discipline and how they are related.

  3. Research of Vision Detection System on PCB

    Institute of Scientific and Technical Information of China (English)

    CHENG Songlin; ZHOU Zude; HU Wenjuan

    2006-01-01

    Machine vision is applied in defect detection system on PCB. The whole system structure and the principle of vision detection are introduced, while the detection method including image processing, detection and recognition algorithms are detailed. The simulation results demonstrate that through this method, four types of defects including short circuit, open circuit, protuberance and concavity on PCB circuit can be effectively inspected, located and recognized.

  4. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron J

    1981-01-01

    The Handbook of Artificial Intelligence, Volume I focuses on the progress in artificial intelligence (AI) and its increasing applications, including parsing, grammars, and search methods.The book first elaborates on AI, AI handbook and literature, problem representation, search methods, and sample search programs. The text then ponders on representation of knowledge, including survey of representation techniques and representation schemes. The manuscript explores understanding natural languages, as well as machine translation, grammars, parsing, test generation, and natural language processing

  5. Industrial vision

    DEFF Research Database (Denmark)

    Knudsen, Ole

    1998-01-01

    of an implementation in real production environments. The theory for projection of world points into images is concentrated upon the direct linear transformation (DLT), also called the Extended Pinhole model, and the stability of this method. A complete list of formulas for calculating all parameters in the model...... is present ed, and the variability of the parameters is examined and described. The concept of using CAD together with vision information is based on the fact that all items processed at OSS have an associated complete 3D CAD model that is accessible at all production states. This concept gives numerous...... possibilities for using vision in applications which otherwise would be very difficult to automate. The requirement for low tolerances in production is, despite the huge dimensions of the items involved, extreme. This fact makes great demands on the ability to do robust sub pixel estimation. A new method based...

  6. Pleiades Visions

    Science.gov (United States)

    Whitehouse, M.

    2016-01-01

    Pleiades Visions (2012) is my new musical composition for organ that takes inspiration from traditional lore and music associated with the Pleiades (Seven Sisters) star cluster from Australian Aboriginal, Native American, and Native Hawaiian cultures. It is based on my doctoral dissertation research incorporating techniques from the fields of ethnomusicology and cultural astronomy; this research likely represents a new area of inquiry for both fields. This large-scale work employs the organ's vast sonic resources to evoke the majesty of the night sky and the expansive landscapes of the homelands of the above-mentioned peoples. Other important themes in Pleiades Visions are those of place, origins, cosmology, and the creation of the world.

  7. Machine musicianship

    Science.gov (United States)

    Rowe, Robert

    2002-05-01

    The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.

  8. Cartesian visions.

    Science.gov (United States)

    Fara, Patricia

    2008-12-01

    Few original portraits exist of René Descartes, yet his theories of vision were central to Enlightenment thought. French philosophers combined his emphasis on sight with the English approach of insisting that ideas are not innate, but must be built up from experience. In particular, Denis Diderot criticised Descartes's views by describing how Nicholas Saunderson--a blind physics professor at Cambridge--relied on touch. Diderot also made Saunderson the mouthpiece for some heretical arguments against the existence of God.

  9. Lambda Vision

    Science.gov (United States)

    Czajkowski, Michael

    2014-06-01

    There is an explosion in the quantity and quality of IMINT data being captured in Intelligence Surveillance and Reconnaissance (ISR) today. While automated exploitation techniques involving computer vision are arriving, only a few architectures can manage both the storage and bandwidth of large volumes of IMINT data and also present results to analysts quickly. Lockheed Martin Advanced Technology Laboratories (ATL) has been actively researching in the area of applying Big Data cloud computing techniques to computer vision applications. This paper presents the results of this work in adopting a Lambda Architecture to process and disseminate IMINT data using computer vision algorithms. The approach embodies an end-to-end solution by processing IMINT data from sensors to serving information products quickly to analysts, independent of the size of the data. The solution lies in dividing up the architecture into a speed layer for low-latent processing and a batch layer for higher quality answers at the expense of time, but in a robust and fault-tolerant way. This approach was evaluated using a large corpus of IMINT data collected by a C-130 Shadow Harvest sensor over Afghanistan from 2010 through 2012. The evaluation data corpus included full motion video from both narrow and wide area field-of-views. The evaluation was done on a scaled-out cloud infrastructure that is similar in composition to those found in the Intelligence Community. The paper shows experimental results to prove the scalability of the architecture and precision of its results using a computer vision algorithm designed to identify man-made objects in sparse data terrain.

  10. Stereo vision with distance and gradient recognition

    Science.gov (United States)

    Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

    2007-12-01

    Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

  11. Artificial Intelligence.

    Science.gov (United States)

    Waltz, David L.

    1982-01-01

    Describes kinds of results achieved by computer programs in artificial intelligence. Topics discussed include heuristic searches, artificial intelligence/psychology, planning program, backward chaining, learning (focusing on Winograd's blocks to explore learning strategies), concept learning, constraint propagation, language understanding…

  12. Artificial intelligence: Learning to see and act

    Science.gov (United States)

    Schölkopf, Bernhard

    2015-02-01

    An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

  13. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  14. Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

    Science.gov (United States)

    Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

    1989-03-01

    The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

  15. Biological Basis For Computer Vision: Some Perspectives

    Science.gov (United States)

    Gupta, Madan M.

    1990-03-01

    Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

  16. Measurement method for yield component traits of maize based on machine vision%基于机器视觉的玉米果穗产量组分性状测量方法

    Institute of Scientific and Technical Information of China (English)

    周金辉; 马钦; 朱德海; 郭浩; 王越; 张晓东; 李绍明; 刘哲

    2015-01-01

    The maize variety test is an important link in the process of crop genetic breeding. The different maize varieties will produce a large number of varieties phenotype data, which need to be collected, collated, recorded, statistically analyzed and stored. Some phenotype data are related to the maize yield, such as bald rate, ear rows, row grains and so on. These maize characters are often collected by the traditional manual measurement at present. For example, the ear rows can be calculated by the maize section image which destroys the maize to be tested .Another measurement method for the ear rows is to rotate and scan the maize, which is very difficult to meet the needs of high throughput maize variety test. Aiming at the above problems, the calculation model according to the color and biological features of maize has been constructed based on the machine vision technology in this paper. The calculation model can compute the maize character parameters precisely, such as bald rate, ear rows, row grains and so on. The experimental results show that the calculation measurement has the high recognition precision and speed. The ear length ,ear diameter ,ear rows ,row grains and other yield components are taken as example for verifying the above calculation model in this paper. The experimental environment settings for image acquisition model are as follows: non wide-angle CMOS pinhole camera (portable, low cast), acquisition environment of soft light and bright place (no special light source set). The camera is 5 million pixels, and the image resolution is 2942 pixels× 1944 pixels. Shoot height is 55 cm, the shooting format is to A3. The algorithm is tested by the PC machine which is configured as a dual core cpu (1.9 GHz) and 2 GB ram. The method presented in this paper can overcome these disadvantages of traditional manual measurement, such as low efficiency, subjective error, and unable to retain the integrity of the original maize material. The method presented in

  17. Implementation of a classifier didactical machine for learning mechatronic processes

    Directory of Open Access Journals (Sweden)

    Alex De La Cruz

    2017-06-01

    Full Text Available The present article shows the design and construction of a classifier didactical machine through artificial vision. The implementation of the machine is to be used as a learning module of mechatronic processes. In the project, it is described the theoretical aspects that relate concepts of mechanical design, electronic design and software management which constitute popular field in science and technology, which is mechatronics. The design of the machine was developed based on the requirements of the user, through the concurrent design methodology to define and materialize the appropriate hardware and software solutions. LabVIEW 2015 was implemented for high-speed image acquisition and analysis, as well as for the establishment of data communication with a programmable logic controller (PLC via Ethernet and an open communications platform known as Open Platform Communications - OPC. In addition, the Arduino MEGA 2560 platform was used to control the movement of the step motor and the servo motors of the module. Also, is used the Arduino MEGA 2560 to control the movement of the stepper motor and servo motors in the module. Finally, we assessed whether the equipment meets the technical specifications raised by running specific test protocols.

  18. Synthetic organisms and living machines

    OpenAIRE

    Deplazes, Anna; Huppenbauer, Markus

    2009-01-01

    The difference between a non-living machine such as a vacuum cleaner and a living organism as a lion seems to be obvious. The two types of entities differ in their material consistence, their origin, their development and their purpose. This apparently clear-cut borderline has previously been challenged by fictitious ideas of “artificial organism” and “living machines” as well as by progress in technology and breeding. The emergence of novel technologies such as artificial life, nanobiotechno...

  19. Bionic machines and systems

    Energy Technology Data Exchange (ETDEWEB)

    Halme, A.; Paanajaervi, J. (eds.)

    2004-07-01

    actuators and motion control with examples. The motion principle considered in detail is biomimetic flight. Biological shock absorption is a topic related to muscles and their structures. The chapter also introduces two research areas in constructing bio-mimicking actuators, namely artificial muscles and hand prosthetics. Chapter 4 deals with perception and navigation. Topics are vision and remote sensing, spatial cognition for building local maps, and biological signal processing. Chapter 5 give examples of animal communication. Chapter 6 introduces the basic theories on animal learning and a learning model. Finally Chapter 7 shows some ideas on swarming behavior and illustrates through an example how they have been applied in a distributed sensory system.

  20. Macroscopic transport by synthetic molecular machines

    NARCIS (Netherlands)

    Berna, J; Leigh, DA; Lubomska, M; Mendoza, SM; Perez, EM; Rudolf, P; Teobaldi, G; Zerbetto, F

    2005-01-01

    Nature uses molecular motors and machines in virtually every significant biological process, but demonstrating that simpler artificial structures operating through the same gross mechanisms can be interfaced with - and perform physical tasks in - the macroscopic world represents a significant hurdle

  1. Industrial robot's vision systems

    Science.gov (United States)

    Iureva, Radda A.; Raskin, Evgeni O.; Komarov, Igor I.; Maltseva, Nadezhda K.; Fedosovsky, Michael E.

    2016-03-01

    Due to the improved economic situation in the high technology sectors, work on the creation of industrial robots and special mobile robotic systems are resumed. Despite this, the robotic control systems mostly remained unchanged. Hence one can see all advantages and disadvantages of these systems. This is due to lack of funds, which could greatly facilitate the work of the operator, and in some cases, completely replace it. The paper is concerned with the complex machine vision of robotic system for monitoring of underground pipelines, which collects and analyzes up to 90% of the necessary information. Vision Systems are used to identify obstacles to the process of movement on a trajectory to determine their origin, dimensions and character. The object is illuminated in a structured light, TV camera records projected structure. Distortions of the structure uniquely determine the shape of the object in view of the camera. The reference illumination is synchronized with the camera. The main parameters of the system are the basic distance between the generator and the lights and the camera parallax angle (the angle between the optical axes of the projection unit and camera).

  2. A "Living" Machine

    Institute of Scientific and Technical Information of China (English)

    N.R.Bogatyrev

    2004-01-01

    Biomimetics (or bionics) is the engineering discipline that constructs artificial systems using biological principles. The ideal final result in biomimetics is to create a living machine. But what are the desirable and non-desirable properties of biomimetic product? Where can natural prototypes be found? How can technical solutions be transferred from nature to technology? Can we use living nature like LEGO bricks for construction our machines? How can biology help us? What is a living machine? In biomimetic practice only some "part" (organ, part of organ, tissue) of the observed whole organism is utilized. A possible template for future super-organism extension for biomimetic methods might be drawn from experiments in holistic ecological agriculture (ecological design, permaculture, ecological engineering, etc. ). The necessary translation of these rules to practical action can be achieved with the Russian Theory of Inventive Problem Solving (TRIZ), specifically adjusted to biology. Thus, permaculture, reinforced by a TRIZ conceptual framework, might provide the basis for Super-Organismic Bionics, which is hypothesized as necessary for effective ecological engineering. This hypothesis is supported by a case study-the design of a sustainable artificial nature reserve for wild pollinators as a living machine.

  3. Pediatric Low Vision

    Science.gov (United States)

    ... Asked Questions Español Condiciones Chinese Conditions Pediatric Low Vision What is Low Vision? Partial vision loss that cannot be corrected causes ... and play. What are the signs of Low Vision? Some signs of low vision include difficulty recognizing ...

  4. Low Vision FAQs

    Science.gov (United States)

    ... de los Ojos Cómo hablarle a su oculista Low Vision FAQs What is low vision? Low vision is a visual impairment, not ... person’s ability to perform everyday activities. What causes low vision? Low vision can result from a variety ...

  5. Pork backfat thickness on-line detection methods using machine vision%基于机器视觉的猪胴体背膘厚度在线检测技术

    Institute of Scientific and Technical Information of China (English)

    李青; 彭彦昆

    2015-01-01

    为了能在线精准测量猪胴体背膘厚度,解决人工测量过程中效率低、人为因素影响大及结缔组织易被误测量为背膘的问题。该文基于机器视觉及图像处理技术提出一种图像采集并自动测量背膘厚度的算法。在双边滤波、大律法、形态学变换的基础上,通过轮廓面积分割提取出背膘区域及其边缘轮廓,利用拟合线对轮廓边框进行拟合,判断是否包含结缔组织。若包含则针对原始图像目标测量区域像素点特征进行具体分析,去除结缔组织。然后通过直线映射,确定背膘厚度检测线,测量猪胴体背膘厚度。测试结果表明:检测方法能适应在线检测速度需求,检测正确率为93.5%,平均检测时间为0.3 s。研究结果为生猪屠宰生产线上准确、快速测量背膘厚度提供参考。%Detection of pork backfat thickness in most of the slaughtering houses depends on manual labors using measuring tools. The objective of this research was to investigate the method for detecting backfat thickness based on computer vision and image processing technologies. And the paper proposed an algorithm of image acquisition and automatically measuring backfat thickness which could solve the problems that manual measurement process had low efficiency, human factor influenced the test result and connective tissue was readily measured as backfat region. The images of pig carcass between the 6th and the 7th rib were collected by the machine vision image acquisition system on the slaughter line. The system consisted of an image acquisition module containing CCD (charge-coupled device) to capture the images and then save them in computer, a single-chip microcomputer, a detection switch, the calibration rule and the light source in system that could be regulated by the controller to change intensity, and the image processing algorithm was equipped into the self-developed system embedded in the computer. The

  6. Color vision.

    Science.gov (United States)

    Gegenfurtner, Karl R; Kiper, Daniel C

    2003-01-01

    Color vision starts with the absorption of light in the retinal cone photoreceptors, which transduce electromagnetic energy into electrical voltages. These voltages are transformed into action potentials by a complicated network of cells in the retina. The information is sent to the visual cortex via the lateral geniculate nucleus (LGN) in three separate color-opponent channels that have been characterized psychophysically, physiologically, and computationally. The properties of cells in the retina and LGN account for a surprisingly large body of psychophysical literature. This suggests that several fundamental computations involved in color perception occur at early levels of processing. In the cortex, information from the three retino-geniculate channels is combined to enable perception of a large variety of different hues. Furthermore, recent evidence suggests that color analysis and coding cannot be separated from the analysis and coding of other visual attributes such as form and motion. Though there are some brain areas that are more sensitive to color than others, color vision emerges through the combined activity of neurons in many different areas.

  7. Food analysis using artificial senses.

    Science.gov (United States)

    Śliwińska, Magdalena; Wiśniewska, Paulina; Dymerski, Tomasz; Namieśnik, Jacek; Wardencki, Waldemar

    2014-02-19

    Nowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring and determining the quality and authenticity of foods. This paper summarizes achievements in the field of artificial senses. It includes a brief history of these systems, descriptions of most commonly used sensors (conductometric, potentiometric, amperometic/voltammetric, impedimetric, colorimetric, piezoelectric), data analysis methods (for example, artificial neural network (ANN), principal component analysis (PCA), model CIE L*a*b*), and application of artificial senses to food analysis, in particular quality control, authenticity and falsification assessment, and monitoring of production processes.

  8. Impairments to Vision

    Science.gov (United States)

    ... an external Non-Government web site. Impairments to Vision Normal Vision Diabetic Retinopathy Age-related Macular Degeneration In this ... pictures, fixate on the nose to simulate the vision loss. In diabetic retinopathy, the blood vessels in ...

  9. Color vision test

    Science.gov (United States)

    ... present from birth) color vision problems: Achromatopsia -- complete color blindness , seeing only shades of gray Deuteranopia -- difficulty telling ... Vision test - color; Ishihara color vision test Images Color blindness tests References Bowling B. Hereditary fundus dystrophies. In: ...

  10. Machine Translation

    Institute of Scientific and Technical Information of China (English)

    张严心

    2015-01-01

    As a kind of ancillary translation tool, Machine Translation has been paid increasing attention to and received different kinds of study by a great deal of researchers and scholars for a long time. To know the definition of Machine Translation and to analyse its benefits and problems are significant for translators in order to make good use of Machine Translation, and helpful to develop and consummate Machine Translation Systems in the future.

  11. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  12. Machine Translation in Post-Contemporary Era

    Science.gov (United States)

    Lin, Grace Hui Chin

    2010-01-01

    This article focusing on translating techniques via personal computer or laptop reports updated artificial intelligence progresses before 2010. Based on interpretations and information for field of MT [Machine Translation] by Yorick Wilks' book, "Machine Translation, Its scope and limits," this paper displays understandable theoretical frameworks…

  13. 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.

  14. Detection of multi-corn kernel embryos characteristic using machine vision%基于机器视觉的多个玉米籽粒胚部特征检测

    Institute of Scientific and Technical Information of China (English)

    程洪; 史智兴; 尹辉娟; 冯娟; 李亚南

    2013-01-01

    This paper presents a method of multi-corn kernel embryos detection based on threshold segmentation and morphology. Corn kernel varieties identification is of great significance in the fields of agricultural production and crop breeding. In the seed market of China, the identification of corn varieties mainly depends on manual experience and measurement. In order to automatically, quickly, non-destructively identify kernel varieties, the study of automatic identification in a real time using machine vision technology is very active. Determination of the characteristics of the corn kernel is the first and the most important step of automatic identification. The corn kernel embryo is the most important part of the corn kernel. To analyze the characteristics of an embryo, an embryo must be separated from the corn kernel. The embryo detection speed and precision can influence the speed and precision of identification. In the paper, an algorithm based on threshold segmentation and morphology was proposed to segment embryos of multi-corn kernel at the same time, as a result of the deeper study of the identification. This algorithm was used to obtain multi-corn kernel embryos from a 2D digital image obtained by the scanner. It mainly included two parts, i.e. a maximum between-cluster deviation method (Otsu method) excluding pixels with zero value automatically, and improved open-close operation from morphology. Its process was as follow. In RGB color space, the multi-corn kernel embryos in the same image were segmented out at the same time by Otsu excluding pixels with zero value method based on the value of B(blue), in which the zero value pixels were auto-removed form histogram during processing. However, after segmentation, some corn kernel embryos showed a problem of lacking-segmentation or over-segmentation. To solve the problem, the improved open-close operation was used to repair the embryos. To validate the algorithm, four varieties of yellow corn which were

  15. Vision Algorithm for the Solar Aspect System of the HEROES Mission

    Science.gov (United States)

    Cramer, Alexander; Christe, Steven; Shih, Albert

    2014-01-01

    This work covers the design and test of a machine vision algorithm for generating high-accuracy pitch and yaw pointing solutions relative to the sun for the High Energy Replicated Optics to Explore the Sun (HEROES) mission. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small fiducial markers. Images of this plate were processed in real time to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an Average Intersection method, fiducial detection by a matched filter approach, identification with an ad-hoc method based on the spacing between fiducials, and image registration with a simple least squares fit. Performance is verified on a combination of artificially generated images, test data recorded on the ground, and images from the 2013 flight.

  16. Artificial blood

    Directory of Open Access Journals (Sweden)

    Sarkar Suman

    2008-01-01

    Full Text Available Artificial blood is a product made to act as a substitute for red blood cells. While true blood serves many different functions, artificial blood is designed for the sole purpose of transporting oxygen and carbon dioxide throughout the body. Depending on the type of artificial blood, it can be produced in different ways using synthetic production, chemical isolation, or recombinant biochemical technology. Development of the first blood substitutes dates back to the early 1600s, and the search for the ideal blood substitute continues. Various manufacturers have products in clinical trials; however, no truly safe and effective artificial blood product is currently marketed. It is anticipated that when an artificial blood product is available, it will have annual sales of over $7.6 billion in the United States alone.

  17. Artificial blood.

    Science.gov (United States)

    Sarkar, Suman

    2008-07-01

    Artificial blood is a product made to act as a substitute for red blood cells. While true blood serves many different functions, artificial blood is designed for the sole purpose of transporting oxygen and carbon dioxide throughout the body. Depending on the type of artificial blood, it can be produced in different ways using synthetic production, chemical isolation, or recombinant biochemical technology. Development of the first blood substitutes dates back to the early 1600s, and the search for the ideal blood substitute continues. Various manufacturers have products in clinical trials; however, no truly safe and effective artificial blood product is currently marketed. It is anticipated that when an artificial blood product is available, it will have annual sales of over $7.6 billion in the United States alone.

  18. Path Planning Design of Seeding Machine Based on Artificial Force Field and Genetic Algorithm%基于人工势力场和遗传算法的播种机路径规划设计

    Institute of Scientific and Technical Information of China (English)

    马继红

    2016-01-01

    In order to improve the adaptive ability of the planter of complex block, enhance the sowing efficiency of planter seeding accuracy, it put forward suitable for precision seeding machine in sub regional exhumation of full area coverage path planning method based on the seeder row fertilizer.The seed metering device was improved so as to adapt to the need of automatic path planning.In order to optimize the path search method based on sub region, the artificial po-tential field and genetic algorithm are used to optimize the optimization method, which improves the efficiency of the algo-rithm.For the validity and reliability of the test method, path planning system is installed in the planting machinery. Through the seeding test, the method realized complex plots sown with the full area coverage and obstacle avoidance.On the three different algorithms for comparison tests,it was found that optimization effect is the best for its large coverage ar-ea based on genetic algorithm of sub regional model for path planning, turning times less, fewer, the shortest time only 11.25min, only for 1/2 of the other algorithm, path division of higher efficiency and meet the intelligent demand of pre-cision seeding machine, which can be used in path planning system in precision seeder.%为了提高播种机对复杂地块的自适应能力,提升播种机的播种精度和播种效率,提出了适合精播机的基于子区域的折返全区域覆盖路径规划方法,并对播种机的排肥器和排种器进行了改进,以适应自动路径规划的需要. 为了优化基于子区域的路径搜索方法,使用人工势场和遗传算法对寻优方法进行了优化,提高了算法的效率. 为了测试该方法的有效性和可靠性,将路径规划系统安装到了播种机械上,通过对播种的测试发现,该方法实现了复杂地块播种的全区域覆盖,并且可以有效地躲避障碍物. 对3 种不同的算法进行对比测试发现:基于遗传算法的子

  19. Integration of vision and robotic workcell

    Science.gov (United States)

    Bossieux, T. A.

    1994-01-01

    The paper discusses the incorporation of vision into a robotic cell to obtain cell status information and use this information to influence the robot operation. It discusses both mechanical and informational solutions to the operational issues which are present. The cell uses a machine vision system to determine information about part presence in the shipping tray, part location in the tray, and tray orientation. The vision system's edge detector algorithm is used to identify the orientation of the packing trays. In addition, different vision tools are used to determine if parts are present in the trays based on the unique configuration of the individual parts. The mechanical solutions discuss the handling of medium weight (10 - 25 lb.) parts at an average cycle time of 3.1 seconds per part. The robot gripper must handle 33 different models, three identical parts at a time. This is accomplished by using stacks of rotary actuators and slides between the stacks.

  20. Near Vision Test for Adults

    Science.gov (United States)

    ... Financial Assistance Information Vision Screening and Eye Exams Zika Virus and Vision Eye Problems Eye Problems Amblyopia ( ... Eye Health Report Reports and External Resources The Cost of Vision Problems The Future of Vision Vision ...

  1. Artificial intelligence: Human effects

    Energy Technology Data Exchange (ETDEWEB)

    Yazdani, M.; Narayanan, A.

    1984-01-01

    This book presents an up-to-date study of the interaction between the fast-growing discipline of artificial intelligence and other human endeavors. The volume explores the scope and limitations of computing, and presents a history of the debate on the possibility of machines achieving intelligence. The authors offer a state-of-the-art survey of Al, concentrating on the ''mind'' (language understanding) and the ''body'' (robotics) of intelligent computing systems.

  2. Cutting temperature measurement and material machinability

    Directory of Open Access Journals (Sweden)

    Nedić Bogdan P.

    2014-01-01

    Full Text Available Cutting temperature is very important parameter of cutting process. Around 90% of heat generated during cutting process is then away by sawdust, and the rest is transferred to the tool and workpiece. In this research cutting temperature was measured with artificial thermocouples and question of investigation of metal machinability from aspect of cutting temperature was analyzed. For investigation of material machinability during turning artificial thermocouple was placed just below the cutting top of insert, and for drilling thermocouples were placed through screw holes on the face surface. In this way was obtained simple, reliable, economic and accurate method for investigation of cutting machinability.

  3. Deep Extreme Learning Machine and Its Application in EEG Classification

    OpenAIRE

    Shifei Ding; Nan Zhang; Xinzheng Xu; Lili Guo; Jian Zhang

    2015-01-01

    Recently, deep learning has aroused wide interest in machine learning fields. Deep learning is a multilayer perceptron artificial neural network algorithm. Deep learning has the advantage of approximating the complicated function and alleviating the optimization difficulty associated with deep models. Multilayer extreme learning machine (MLELM) is a learning algorithm of an artificial neural network which takes advantages of deep learning and extreme learning machine. Not only does MLELM appr...

  4. Deep Extreme Learning Machine and Its Application in EEG Classification

    OpenAIRE

    2015-01-01

    Recently, deep learning has aroused wide interest in machine learning fields. Deep learning is a multilayer perceptron artificial neural network algorithm. Deep learning has the advantage of approximating the complicated function and alleviating the optimization difficulty associated with deep models. Multilayer extreme learning machine (MLELM) is a learning algorithm of an artificial neural network which takes advantages of deep learning and extreme learning machine. Not only does MLELM appr...

  5. 基于流形学习算法的马铃薯机械损伤机器视觉检测方法%Machine vision detecting potato mechanical damage based on manifold learning algorithm

    Institute of Scientific and Technical Information of China (English)

    汪成龙; 李小昱; 武振中; 周竹; 冯耀泽

    2014-01-01

    Buds and uneven surface of potatoes have caused problems to detect the mechanical damage based on machine vision. The lighting conditions and gray value changes of defect region have great impacts on the pixel level feature extraction. While manifold learning methods have been extensively studied in the face recognition, they have not been used for the external quality inspection of agricultural products. The manifold learning method is mainly divided into linear and nonlinear manifold learning algorithms. The nonlinear manifold learning algorithm includes isometric mapping (Isomap), locally linear embedding (LLE), laplacian eigenmaping (LE). The linear algorithm is extension of the nonlinear methods such as principal component analysis (PCA) and multidimensional scaling (MDS). In order to weaken the influence of the buds and uneven surface on potatoes mechanical damage detection, the image was characterized by using low dimensional manifolds. A mechanical damage detection method for potatoes was provided based on manifold learning. In this study, the Saliency and H images were firstly segmented on the potato regional image. The segmentation accuracies of both images are 100%. However, Saliency-H method can the potato’s location information of the image by unsupervised pattern was automatically obtained. In addition, Saliency-H method was faster (average elapsed time is 477.7ms) than H method with a high data compression rate. After the potato region images were resampled from 1024×768 to 64×64, the features of potato images were extracted from the resample images by using the three manifold learning methods: principal component analysis (PCA), isometric mapping (Isomap) and locally linear embedding (LLE). Thirdly, the three corresponding SVM classification models were developed based on their features. Finally the parameters of the models were optimized to develop corresponding optimal classification models by using the grid search method (grid search

  6. Vision Systems with the Human in the Loop

    Directory of Open Access Journals (Sweden)

    Bauckhage Christian

    2005-01-01

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

  7. "Hypothetical machines": the science fiction dreams of Cold War social science.

    Science.gov (United States)

    Lemov, Rebecca

    2010-06-01

    The introspectometer was a "hypothetical machine" Robert K. Merton introduced in the course of a 1956 how-to manual describing an actual research technique, the focused interview. This technique, in turn, formed the basis of wartime morale research and consumer behavior studies as well as perhaps the most ubiquitous social science tool, the focus group. This essay explores a new perspective on Cold War social science made possible by comparing two kinds of apparatuses: one real, the other imaginary. Even as Merton explored the nightmare potential of such machines, he suggested that the clear aim of social science was to build them or their functional equivalent: recording machines to access a person's experiential stream of reality, with the ability to turn this stream into real-time data. In this way, the introspectometer marks and symbolizes a broader entry during the Cold War of science-fiction-style aspirations into methodological prescriptions and procedural manuals. This essay considers the growth of the genre of methodological visions and revisions, painstakingly argued and absorbed, but punctuated by sci-fi aims to transform "the human" and build newly penetrating machines. It also considers the place of the nearly real-, and the artificial "near-substitute" as part of an experimental urge that animated these sciences.

  8. Artificial urushi.

    Science.gov (United States)

    Kobayashi, S; Uyama, H; Ikeda, R

    2001-11-19

    A new concept for the design and laccase-catalyzed preparation of "artificial urushi" from new urushiol analogues is described. The curing proceeded under mild reaction conditions to produce the very hard cross-linked film (artificial urushi) with a high gloss surface. A new cross-linkable polyphenol was synthesized by oxidative polymerization of cardanol, a phenol derivative from cashew-nut-shell liquid, by enzyme-related catalysts. The polyphenol was readily cured to produce the film (also artificial urushi) showing excellent dynamic viscoelasticity.

  9. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  10. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  11. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  12. Artificial Limbs

    Science.gov (United States)

    ... diabetes. They may cause you to need an amputation. Traumatic injuries, including from traffic accidents and military combat Cancer Birth defects If you are missing an arm or leg, an artificial limb can sometimes replace it. The device, which is ...

  13. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  14. Artificial sweeteners

    DEFF Research Database (Denmark)

    Raben, Anne Birgitte; Richelsen, Bjørn

    2012-01-01

    Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie......-containing sweeteners. The purpose of this review is to summarize the current evidence on the effect of artificial sweeteners on body weight, appetite, and risk markers for diabetes and CVD in humans....

  15. Laser Imaging Systems For Computer Vision

    Science.gov (United States)

    Vlad, Ionel V.; Ionescu-Pallas, Nicholas; Popa, Dragos; Apostol, Ileana; Vlad, Adriana; Capatina, V.

    1989-05-01

    The computer vision is becoming an essential feature of the high level artificial intelligence. Laser imaging systems act as special kind of image preprocessors/converters enlarging the access of the computer "intelligence" to the inspection, analysis and decision in new "world" : nanometric, three-dimensionals(3D), ultrafast, hostile for humans etc. Considering that the heart of the problem is the matching of the optical methods and the compu-ter software , some of the most promising interferometric,projection and diffraction systems are reviewed with discussions of our present results and of their potential in the precise 3D computer vision.

  16. Estimation of storage time of yogurt with artificial neural network modeling.

    Science.gov (United States)

    Sofu, A; Ekinci, F Y

    2007-07-01

    Changes in the physical, chemical, and microbiological structure of yogurt determine the storage and shelf life of the product. In this study, microbial counts and pH values of yogurt during storage were determined at d 1, 7, and 14. Simultaneously, image processing of yogurt was digitized by using a machine vision system (MVS) to determine color changes during storage, and the obtained data were modeled with an artificial neural network (ANN) for prediction of shelf life of set-type whole-fat and low-fat yogurts. The ANN models were developed using back-propagation networks with a single hidden layer and sigmoid activation functions. The input variables of the network were pH; total aerobic, yeast, mold, and coliform counts; and color analysis values measured by the machine vision system. The output variable was the storage time of the yogurt. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 = 0.9996) showing that the developed model was able to analyze nonlinear multivariant data with very good performance, fewer parameters, and shorter calculation time. The model might be an alternative method to control the expiration date of yogurt shown in labeling and provide consumers with a safer food supply.

  17. Identification of bean varieties according to color features using artificial neural network

    Directory of Open Access Journals (Sweden)

    A. Nasirahmadi

    2013-07-01

    Full Text Available A machine vision and a multilayer perceptron artificial neural network (MLP-ANN were applied to identify bean varieties, based on color features. Ten varieties of beans, which were grown in Iran (Khomein1, KS21108, Khomein2, Sarab1, Khomein3, KS21409, Akhtar2, Sarab2, KS21205, and G11870 were collected. Six color features of the bean and six color features of the spots were extracted and used as input for MLP-ANN classifier. In this study, 1000 data sets were used, 70% for training, 15% for validating and 15% for testing. The results showed that the applied machine vision and neural network were able to classify bean varieties with 100% sensibility and specificity, except with Sarab1 with sensibilities of 100%, 73.3%, 60% for the training, validation and testing processes, respectively and KS21108 with specificities of 100%, 79% and 71%, respectively for the aforementioned processes. Considering total sensibilities of 100%, 97.33%, 96% and also specificities of 100%, 97.9% and 97.1% for training, validation and testing of beans, respectively, the ANN could be used as a effective tool for classification of bean varieties.

  18. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  19. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  20. Three-Dimensional Robotic Vision System

    Science.gov (United States)

    Nguyen, Thinh V.

    1989-01-01

    Stereoscopy and motion provide clues to outlines of objects. Digital image-processing system acts as "intelligent" automatic machine-vision system by processing views from stereoscopic television cameras into three-dimensional coordinates of moving object in view. Epipolar-line technique used to find corresponding points in stereoscopic views. Robotic vision system analyzes views from two television cameras to detect rigid three-dimensional objects and reconstruct numerically in terms of coordinates of corner points. Stereoscopy and effects of motion on two images complement each other in providing image-analyzing subsystem with clues to natures and locations of principal features.