Computer vision camera with embedded FPGA processing

NASA Astrophysics Data System (ADS)

Lecerf, Antoine; Ouellet, Denis; Arias-Estrada, Miguel

2000-03-01

Traditional computer vision is based on a camera-computer system in which the image understanding algorithms are embedded in the computer. To circumvent the computational load of vision algorithms, low-level processing and imaging hardware can be integrated in a single compact module where a dedicated architecture is implemented. This paper presents a Computer Vision Camera based on an open architecture implemented in an FPGA. The system is targeted to real-time computer vision tasks where low level processing and feature extraction tasks can be implemented in the FPGA device. The camera integrates a CMOS image sensor, an FPGA device, two memory banks, and an embedded PC for communication and control tasks. The FPGA device is a medium size one equivalent to 25,000 logic gates. The device is connected to two high speed memory banks, an IS interface, and an imager interface. The camera can be accessed for architecture programming, data transfer, and control through an Ethernet link from a remote computer. A hardware architecture can be defined in a Hardware Description Language (like VHDL), simulated and synthesized into digital structures that can be programmed into the FPGA and tested on the camera. The architecture of a classical multi-scale edge detection algorithm based on a Laplacian of Gaussian convolution has been developed to show the capabilities of the system.

Low computation vision-based navigation for a Martian rover

NASA Technical Reports Server (NTRS)

Gavin, Andrew S.; Brooks, Rodney A.

1994-01-01

Construction and design details of the Mobot Vision System, a small, self-contained, mobile vision system, are presented. This system uses the view from the top of a small, roving, robotic vehicle to supply data that is processed in real-time to safely navigate the surface of Mars. A simple, low-computation algorithm for constructing a 3-D navigational map of the Martian environment to be used by the rover is discussed.

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

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.

Machine vision for real time orbital operations

NASA Technical Reports Server (NTRS)

Vinz, Frank L.

1988-01-01

Machine vision for automation and robotic operation of Space Station era systems has the potential for increasing the efficiency of orbital servicing, repair, assembly and docking tasks. A machine vision research project is described in which a TV camera is used for inputing visual data to a computer so that image processing may be achieved for real time control of these orbital operations. A technique has resulted from this research which reduces computer memory requirements and greatly increases typical computational speed such that it has the potential for development into a real time orbital machine vision system. This technique is called AI BOSS (Analysis of Images by Box Scan and Syntax).

Marking parts to aid robot vision

NASA Technical Reports Server (NTRS)

Bales, J. W.; Barker, L. K.

1981-01-01

The premarking of parts for subsequent identification by a robot vision system appears to be beneficial as an aid in the automation of certain tasks such as construction in space. A simple, color coded marking system is presented which allows a computer vision system to locate an object, calculate its orientation, and determine its identity. Such a system has the potential to operate accurately, and because the computer shape analysis problem has been simplified, it has the ability to operate in real time.

The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas.

PubMed

Friedman, Robert J; Gutkowicz-Krusin, Dina; Farber, Michele J; Warycha, Melanie; Schneider-Kels, Lori; Papastathis, Nicole; Mihm, Martin C; Googe, Paul; King, Roy; Prieto, Victor G; Kopf, Alfred W; Polsky, David; Rabinovitz, Harold; Oliviero, Margaret; Cognetta, Armand; Rigel, Darrell S; Marghoob, Ashfaq; Rivers, Jason; Johr, Robert; Grant-Kels, Jane M; Tsao, Hensin

2008-04-01

To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter

Vision-Based UAV Flight Control and Obstacle Avoidance

DTIC Science & Technology

2006-01-01

denoted it by Vb = (Vb1, Vb2 , Vb3). Fig. 2 shows the block diagram of the proposed vision-based motion analysis and obstacle avoidance system. We denote...structure analysis often involve computation- intensive computer vision tasks, such as feature extraction and geometric modeling. Computation-intensive...First, we extract a set of features from each block. 2) Second, we compute the distance between these two sets of features. In conventional motion

Machine Learning, deep learning and optimization in computer vision

NASA Astrophysics Data System (ADS)

Canu, Stéphane

2017-03-01

As quoted in the Large Scale Computer Vision Systems NIPS workshop, computer vision is a mature field with a long tradition of research, but recent advances in machine learning, deep learning, representation learning and optimization have provided models with new capabilities to better understand visual content. The presentation will go through these new developments in machine learning covering basic motivations, ideas, models and optimization in deep learning for computer vision, identifying challenges and opportunities. It will focus on issues related with large scale learning that is: high dimensional features, large variety of visual classes, and large number of examples.

Automated Grading of Rough Hardwood Lumber

Treesearch

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

1989-01-01

Any automatic hardwood grading system must have two components. The first of these is a computer vision system for locating and identifying defects on rough lumber. The second is a system for automatically grading boards based on the output of the computer vision system. This paper presents research results aimed at developing the first of these components. The...

Computer vision

NASA Technical Reports Server (NTRS)

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.

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

DTIC Science & Technology

1983-08-15

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

Reinforcement learning in computer vision

NASA Astrophysics Data System (ADS)

Bernstein, A. V.; Burnaev, E. V.

2018-04-01

Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

Computer vision in cell biology.

PubMed

Danuser, Gaudenz

2011-11-23

Computer vision refers to the theory and implementation of artificial systems that extract information from images to understand their content. Although computers are widely used by cell biologists for visualization and measurement, interpretation of image content, i.e., the selection of events worth observing and the definition of what they mean in terms of cellular mechanisms, is mostly left to human intuition. This Essay attempts to outline roles computer vision may play and should play in image-based studies of cellular life. Copyright © 2011 Elsevier Inc. All rights reserved.

Real-time unconstrained object recognition: a processing pipeline based on the mammalian visual system.

PubMed

Aguilar, Mario; Peot, Mark A; Zhou, Jiangying; Simons, Stephen; Liao, Yuwei; Metwalli, Nader; Anderson, Mark B

2012-03-01

The mammalian visual system is still the gold standard for recognition accuracy, flexibility, efficiency, and speed. Ongoing advances in our understanding of function and mechanisms in the visual system can now be leveraged to pursue the design of computer vision architectures that will revolutionize the state of the art in computer vision.

Monitoring system of multiple fire fighting based on computer vision

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

A dental vision system for accurate 3D tooth modeling.

PubMed

Zhang, Li; Alemzadeh, K

2006-01-01

This paper describes an active vision system based reverse engineering approach to extract the three-dimensional (3D) geometric information from dental teeth and transfer this information into Computer-Aided Design/Computer-Aided Manufacture (CAD/CAM) systems to improve the accuracy of 3D teeth models and at the same time improve the quality of the construction units to help patient care. The vision system involves the development of a dental vision rig, edge detection, boundary tracing and fast & accurate 3D modeling from a sequence of sliced silhouettes of physical models. The rig is designed using engineering design methods such as a concept selection matrix and weighted objectives evaluation chart. Reconstruction results and accuracy evaluation are presented on digitizing different teeth models.

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

NASA Astrophysics Data System (ADS)

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

2012-09-01

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

Lumber Grading With A Computer Vision System

Treesearch

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

1989-01-01

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

Sensor Control of Robot Arc Welding

NASA Technical Reports Server (NTRS)

Sias, F. R., Jr.

1983-01-01

The potential for using computer vision as sensory feedback for robot gas-tungsten arc welding is investigated. The basic parameters that must be controlled while directing the movement of an arc welding torch are defined. The actions of a human welder are examined to aid in determining the sensory information that would permit a robot to make reproducible high strength welds. Special constraints imposed by both robot hardware and software are considered. Several sensory modalities that would potentially improve weld quality are examined. Special emphasis is directed to the use of computer vision for controlling gas-tungsten arc welding. Vendors of available automated seam tracking arc welding systems and of computer vision systems are surveyed. An assessment is made of the state of the art and the problems that must be solved in order to apply computer vision to robot controlled arc welding on the Space Shuttle Main Engine.

Knowledge-based machine vision systems for space station automation

NASA Technical Reports Server (NTRS)

Ranganath, Heggere S.; Chipman, Laure J.

1989-01-01

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Operational Assessment of Color Vision

DTIC Science & Technology

2016-06-20

evaluated in this study. 15. SUBJECT TERMS Color vision, aviation, cone contrast test, Colour Assessment & Diagnosis , color Dx, OBVA 16. SECURITY...symbologies are frequently used to aid or direct critical activities such as aircraft landing approaches or railroad right-of-way designations...computer-generated display systems have facilitated the development of computer-based, automated tests of color vision [14,15]. The United Kingdom’s

A real-time camera calibration system based on OpenCV

NASA Astrophysics Data System (ADS)

Zhang, Hui; Wang, Hua; Guo, Huinan; Ren, Long; Zhou, Zuofeng

2015-07-01

Camera calibration is one of the essential steps in the computer vision research. This paper describes a real-time OpenCV based camera calibration system, and developed and implemented in the VS2008 environment. Experimental results prove that the system to achieve a simple and fast camera calibration, compared with MATLAB, higher precision and does not need manual intervention, and can be widely used in various computer vision system.

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

NASA Technical Reports Server (NTRS)

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.

Remote media vision-based computer input device

NASA Astrophysics Data System (ADS)

Arabnia, Hamid R.; Chen, Ching-Yi

1991-11-01

In this paper, we introduce a vision-based computer input device which has been built at the University of Georgia. The user of this system gives commands to the computer without touching any physical device. The system receives input through a CCD camera; it is PC- based and is built on top of the DOS operating system. The major components of the input device are: a monitor, an image capturing board, a CCD camera, and some software (developed by use). These are interfaced with a standard PC running under the DOS operating system.

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

NASA Technical Reports Server (NTRS)

Wehner, Walter S.

2014-01-01

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

Computer Vision Systems for Hardwood Logs and Lumber

Treesearch

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

1991-01-01

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

Parallel computer vision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

ERIC Educational Resources Information Center

Xu, Richard Y. D.; Jin, Jesse S.

2007-01-01

This article presents a schematic application of computer vision technologies to e-learning that is synchronous, peer-to-peer-based, and supports an instructor's interaction with non-computer teaching equipments. The article first discusses the importance of these focused e-learning areas, where the properties include accurate bidirectional…

Development of a Wireless Computer Vision Instrument to Detect Biotic Stress in Wheat

PubMed Central

Casanova, Joaquin J.; O'Shaughnessy, Susan A.; Evett, Steven R.; Rush, Charles M.

2014-01-01

Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat. Digital images of differentially stressed wheat were segmented into soil and vegetation pixels using expectation maximization (EM). In the first season, the algorithm to segment vegetation from soil and distinguish between healthy and stressed wheat was developed and tested using digital images taken in the field and later processed on a desktop computer. In the second season, a wireless camera with near real-time computer vision capabilities was tested in conjunction with the conventional camera and desktop computer. For wheat irrigated at different levels and inoculated with wheat streak mosaic virus (WSMV), vegetation hue determined by the EM algorithm showed significant effects from irrigation level and infection. Unstressed wheat had a higher hue (118.32) than stressed wheat (111.34). In the second season, the hue and cover measured by the wireless computer vision sensor showed significant effects from infection (p = 0.0014), as did the conventional camera (p < 0.0001). Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling. Such a low-cost system could be suitable for use in the field in automated irrigation scheduling applications. PMID:25251410

Design And Implementation Of Integrated Vision-Based Robotic Workcells

NASA Astrophysics Data System (ADS)

Chen, Michael J.

1985-01-01

Reports have been sparse on large-scale, intelligent integration of complete robotic systems for automating the microelectronics industry. This paper describes the application of state-of-the-art computer-vision technology for manufacturing of miniaturized electronic components. The concepts of FMS - Flexible Manufacturing Systems, work cells, and work stations and their control hierarchy are illustrated in this paper. Several computer-controlled work cells used in the production of thin-film magnetic heads are described. These cells use vision for in-process control of head-fixture alignment and real-time inspection of production parameters. The vision sensor and other optoelectronic sensors, coupled with transport mechanisms such as steppers, x-y-z tables, and robots, have created complete sensorimotor systems. These systems greatly increase the manufacturing throughput as well as the quality of the final product. This paper uses these automated work cells as examples to exemplify the underlying design philosophy and principles in the fabrication of vision-based robotic systems.

Survey of computer vision-based natural disaster warning systems

NASA Astrophysics Data System (ADS)

Ko, ByoungChul; Kwak, Sooyeong

2012-07-01

With the rapid development of information technology, natural disaster prevention is growing as a new research field dealing with surveillance systems. To forecast and prevent the damage caused by natural disasters, the development of systems to analyze natural disasters using remote sensing geographic information systems (GIS), and vision sensors has been receiving widespread interest over the last decade. This paper provides an up-to-date review of five different types of natural disasters and their corresponding warning systems using computer vision and pattern recognition techniques such as wildfire smoke and flame detection, water level detection for flood prevention, coastal zone monitoring, and landslide detection. Finally, we conclude with some thoughts about future research directions.

Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances.

PubMed

Ma, Ji; Sun, Da-Wen; Qu, Jia-Huan; Liu, Dan; Pu, Hongbin; Gao, Wen-Hong; Zeng, Xin-An

2016-01-01

With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.

Computer Vision for High-Throughput Quantitative Phenotyping: A Case Study of Grapevine Downy Mildew Sporulation and Leaf Trichomes.

PubMed

Divilov, Konstantin; Wiesner-Hanks, Tyr; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2017-12-01

Quantitative phenotyping of downy mildew sporulation is frequently used in plant breeding and genetic studies, as well as in studies focused on pathogen biology such as chemical efficacy trials. In these scenarios, phenotyping a large number of genotypes or treatments can be advantageous but is often limited by time and cost. We present a novel computational pipeline dedicated to estimating the percent area of downy mildew sporulation from images of inoculated grapevine leaf discs in a manner that is time and cost efficient. The pipeline was tested on images from leaf disc assay experiments involving two F 1 grapevine families, one that had glabrous leaves (Vitis rupestris B38 × 'Horizon' [RH]) and another that had leaf trichomes (Horizon × V. cinerea B9 [HC]). Correlations between computer vision and manual visual ratings reached 0.89 in the RH family and 0.43 in the HC family. Additionally, we were able to use the computer vision system prior to sporulation to measure the percent leaf trichome area. We estimate that an experienced rater scoring sporulation would spend at least 90% less time using the computer vision system compared with the manual visual method. This will allow more treatments to be phenotyped in order to better understand the genetic architecture of downy mildew resistance and of leaf trichome density. We anticipate that this computer vision system will find applications in other pathosystems or traits where responses can be imaged with sufficient contrast from the background.

Heterogeneous compute in computer vision: OpenCL in OpenCV

NASA Astrophysics Data System (ADS)

Gasparakis, Harris

2014-02-01

We explore the relevance of Heterogeneous System Architecture (HSA) in Computer Vision, both as a long term vision, and as a near term emerging reality via the recently ratified OpenCL 2.0 Khronos standard. After a brief review of OpenCL 1.2 and 2.0, including HSA features such as Shared Virtual Memory (SVM) and platform atomics, we identify what genres of Computer Vision workloads stand to benefit by leveraging those features, and we suggest a new mental framework that replaces GPU compute with hybrid HSA APU compute. As a case in point, we discuss, in some detail, popular object recognition algorithms (part-based models), emphasizing the interplay and concurrent collaboration between the GPU and CPU. We conclude by describing how OpenCL has been incorporated in OpenCV, a popular open source computer vision library, emphasizing recent work on the Transparent API, to appear in OpenCV 3.0, which unifies the native CPU and OpenCL execution paths under a single API, allowing the same code to execute either on CPU or on a OpenCL enabled device, without even recompiling.

Near real-time stereo vision system

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

The Development of a Robot-Based Learning Companion: A User-Centered Design Approach

ERIC Educational Resources Information Center

Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong

2015-01-01

A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…

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

NASA Astrophysics Data System (ADS)

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.

Use of 3D vision for fine robot motion

NASA Technical Reports Server (NTRS)

Lokshin, Anatole; Litwin, Todd

1989-01-01

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

A self-learning camera for the validation of highly variable and pseudorandom patterns

NASA Astrophysics Data System (ADS)

Kelley, Michael

2004-05-01

Reliable and productive manufacturing operations have depended on people to quickly detect and solve problems whenever they appear. Over the last 20 years, more and more manufacturing operations have embraced machine vision systems to increase productivity, reliability and cost-effectiveness, including reducing the number of human operators required. Although machine vision technology has long been capable of solving simple problems, it has still not been broadly implemented. The reason is that until now, no machine vision system has been designed to meet the unique demands of complicated pattern recognition. The ZiCAM family was specifically developed to be the first practical hardware to meet these needs. To be able to address non-traditional applications, the machine vision industry must include smart camera technology that meets its users" demands for lower costs, better performance and the ability to address applications of irregular lighting, patterns and color. The next-generation smart cameras will need to evolve as a fundamentally different kind of sensor, with new technology that behaves like a human but performs like a computer. Neural network based systems, coupled with self-taught, n-space, non-linear modeling, promises to be the enabler of the next generation of machine vision equipment. Image processing technology is now available that enables a system to match an operator"s subjectivity. A Zero-Instruction-Set-Computer (ZISC) powered smart camera allows high-speed fuzzy-logic processing, without the need for computer programming. This can address applications of validating highly variable and pseudo-random patterns. A hardware-based implementation of a neural network, Zero-Instruction-Set-Computer, enables a vision system to "think" and "inspect" like a human, with the speed and reliability of a machine.

CT Image Sequence Analysis for Object Recognition - A Rule-Based 3-D Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman

1991-01-01

Research is now underway to create a vision system for hardwood log inspection using a knowledge-based approach. In this paper, we present a rule-based, 3-D vision system for locating and identifying wood defects using topological, geometric, and statistical attributes. A number of different features can be derived from the 3-D input scenes. These features and evidence...

Synthetic Vision Systems

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip

2015-07-01

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

Audible vision for the blind and visually impaired in indoor open spaces.

PubMed

Yu, Xunyi; Ganz, Aura

2012-01-01

In this paper we introduce Audible Vision, a system that can help blind and visually impaired users navigate in large indoor open spaces. The system uses computer vision to estimate the location and orientation of the user, and enables the user to perceive his/her relative position to a landmark through 3D audio. Testing shows that Audible Vision can work reliably in real-life ever-changing environment crowded with people.

Understanding of and applications for robot vision guidance at KSC

NASA Technical Reports Server (NTRS)

Shawaga, Lawrence M.

1988-01-01

The primary thrust of robotics at KSC is for the servicing of Space Shuttle remote umbilical docking functions. In order for this to occur, robots performing servicing operations must be capable of tracking a swaying Orbiter in Six Degrees of Freedom (6-DOF). Currently, in NASA KSC's Robotic Applications Development Laboratory (RADL), an ASEA IRB-90 industrial robot is being equipped with a real-time computer vision (hardware and software) system to allow it to track a simulated Orbiter interface (target) in 6-DOF. The real-time computer vision system effectively becomes the eyes for the lab robot, guiding it through a closed loop visual feedback system to move with the simulated Orbiter interface. This paper will address an understanding of this vision guidance system and how it will be applied to remote umbilical servicing at KSC. In addition, other current and future applications will be addressed.

Review On Applications Of Neural Network To Computer Vision

NASA Astrophysics Data System (ADS)

Li, Wei; Nasrabadi, Nasser M.

1989-03-01

Neural network models have many potential applications to computer vision due to their parallel structures, learnability, implicit representation of domain knowledge, fault tolerance, and ability of handling statistical data. This paper demonstrates the basic principles, typical models and their applications in this field. Variety of neural models, such as associative memory, multilayer back-propagation perceptron, self-stabilized adaptive resonance network, hierarchical structured neocognitron, high order correlator, network with gating control and other models, can be applied to visual signal recognition, reinforcement, recall, stereo vision, motion, object tracking and other vision processes. Most of the algorithms have been simulated on com-puters. Some have been implemented with special hardware. Some systems use features, such as edges and profiles, of images as the data form for input. Other systems use raw data as input signals to the networks. We will present some novel ideas contained in these approaches and provide a comparison of these methods. Some unsolved problems are mentioned, such as extracting the intrinsic properties of the input information, integrating those low level functions to a high-level cognitive system, achieving invariances and other problems. Perspectives of applications of some human vision models and neural network models are analyzed.

Computer vision for general purpose visual inspection: a fuzzy logic approach

NASA Astrophysics Data System (ADS)

Chen, Y. H.

In automatic visual industrial inspection, computer vision systems have been widely used. Such systems are often application specific, and therefore require domain knowledge in order to have a successful implementation. Since visual inspection can be viewed as a decision making process, it is argued that the integration of fuzzy logic analysis and computer vision systems provides a practical approach to general purpose visual inspection applications. This paper describes the development of an integrated fuzzy-rule-based automatic visual inspection system. Domain knowledge about a particular application is represented as a set of fuzzy rules. From the status of predefined fuzzy variables, the set of fuzzy rules are defuzzified to give the inspection results. A practical application where IC marks (often in the forms of English characters and a company logo) inspection is demonstrated, which shows a more consistent result as compared to a conventional thresholding method.

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

PubMed

Kriegeskorte, Nikolaus

2015-11-24

Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

Database Integrity Monitoring for Synthetic Vision Systems Using Machine Vision and SHADE

NASA Technical Reports Server (NTRS)

Cooper, Eric G.; Young, Steven D.

2005-01-01

In an effort to increase situational awareness, the aviation industry is investigating technologies that allow pilots to visualize what is outside of the aircraft during periods of low-visibility. One of these technologies, referred to as Synthetic Vision Systems (SVS), provides the pilot with real-time computer-generated images of obstacles, terrain features, runways, and other aircraft regardless of weather conditions. To help ensure the integrity of such systems, methods of verifying the accuracy of synthetically-derived display elements using onboard remote sensing technologies are under investigation. One such method is based on a shadow detection and extraction (SHADE) algorithm that transforms computer-generated digital elevation data into a reference domain that enables direct comparison with radar measurements. This paper describes machine vision techniques for making this comparison and discusses preliminary results from application to actual flight data.

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

NASA Technical Reports Server (NTRS)

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.

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Two-dimensional (2D) displacement measurement of moving objects using a new MEMS binocular vision system

NASA Astrophysics Data System (ADS)

Di, Si; Lin, Hui; Du, Ruxu

2011-05-01

Displacement measurement of moving objects is one of the most important issues in the field of computer vision. This paper introduces a new binocular vision system (BVS) based on micro-electro-mechanical system (MEMS) technology. The eyes of the system are two microlenses fabricated on a substrate by MEMS technology. The imaging results of two microlenses are collected by one complementary metal-oxide-semiconductor (CMOS) array. An algorithm is developed for computing the displacement. Experimental results show that as long as the object is moving in two-dimensional (2D) space, the system can effectively estimate the 2D displacement without camera calibration. It is also shown that the average error of the displacement measurement is about 3.5% at different object distances ranging from 10 cm to 35 cm. Because of its low cost, small size and simple setting, this new method is particularly suitable for 2D displacement measurement applications such as vision-based electronics assembly and biomedical cell culture.

Three-camera stereo vision for intelligent transportation systems

NASA Astrophysics Data System (ADS)

Bergendahl, Jason; Masaki, Ichiro; Horn, Berthold K. P.

1997-02-01

A major obstacle in the application of stereo vision to intelligent transportation system is high computational cost. In this paper, a PC based three-camera stereo vision system constructed with off-the-shelf components is described. The system serves as a tool for developing and testing robust algorithms which approach real-time performance. We present an edge based, subpixel stereo algorithm which is adapted to permit accurate distance measurements to objects in the field of view using a compact camera assembly. Once computed, the 3D scene information may be directly applied to a number of in-vehicle applications, such as adaptive cruise control, obstacle detection, and lane tracking. Moreover, since the largest computational costs is incurred in generating the 3D scene information, multiple applications that leverage this information can be implemented in a single system with minimal cost. On-road applications, such as vehicle counting and incident detection, are also possible. Preliminary in-vehicle road trial results are presented.

Computer vision-based classification of hand grip variations in neurorehabilitation.

PubMed

Zariffa, José; Steeves, John D

2011-01-01

The complexity of hand function is such that most existing upper limb rehabilitation robotic devices use only simplified hand interfaces. This is in contrast to the importance of the hand in regaining function after neurological injury. Computer vision technology has been used to identify hand posture in the field of Human Computer Interaction, but this approach has not been translated to the rehabilitation context. We describe a computer vision-based classifier that can be used to discriminate rehabilitation-relevant hand postures, and could be integrated into a virtual reality-based upper limb rehabilitation system. The proposed system was tested on a set of video recordings from able-bodied individuals performing cylindrical grasps, lateral key grips, and tip-to-tip pinches. The overall classification success rate was 91.2%, and was above 98% for 6 out of the 10 subjects. © 2011 IEEE

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

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Computer Vision System For Locating And Identifying Defects In Hardwood Lumber

NASA Astrophysics Data System (ADS)

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

1989-03-01

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

Dynamic Estimation of Rigid Motion from Perspective Views via Recursive Identification of Exterior Differential Systems with Parameters on a Topological Manifold

DTIC Science & Technology

1994-02-15

0. Faugeras. Three dimensional vision, a geometric viewpoint. MIT Press, 1993. [19] 0 . D. Faugeras and S. Maybank . Motion from point mathces...multiplicity of solutions. Int. J. of Computer Vision, 1990. 1201 0.D. Faugeras, Q.T. Luong, and S.J. Maybank . Camera self-calibration: theory and...Kalrnan filter-based algorithms for estimating depth from image sequences. Int. J. of computer vision, 1989. [41] S. Maybank . Theory of

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

A trunk ranging system based on binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhao, Xixuan; Kan, Jiangming

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Remote sensing of vegetation structure using computer vision

NASA Astrophysics Data System (ADS)

Dandois, Jonathan P.

High-spatial resolution measurements of vegetation structure are needed for improving understanding of ecosystem carbon, water and nutrient dynamics, the response of ecosystems to a changing climate, and for biodiversity mapping and conservation, among many research areas. Our ability to make such measurements has been greatly enhanced by continuing developments in remote sensing technology---allowing researchers the ability to measure numerous forest traits at varying spatial and temporal scales and over large spatial extents with minimal to no field work, which is costly for large spatial areas or logistically difficult in some locations. Despite these advances, there remain several research challenges related to the methods by which three-dimensional (3D) and spectral datasets are joined (remote sensing fusion) and the availability and portability of systems for frequent data collections at small scale sampling locations. Recent advances in the areas of computer vision structure from motion (SFM) and consumer unmanned aerial systems (UAS) offer the potential to address these challenges by enabling repeatable measurements of vegetation structural and spectral traits at the scale of individual trees. However, the potential advances offered by computer vision remote sensing also present unique challenges and questions that need to be addressed before this approach can be used to improve understanding of forest ecosystems. For computer vision remote sensing to be a valuable tool for studying forests, bounding information about the characteristics of the data produced by the system will help researchers understand and interpret results in the context of the forest being studied and of other remote sensing techniques. This research advances understanding of how forest canopy and tree 3D structure and color are accurately measured by a relatively low-cost and portable computer vision personal remote sensing system: 'Ecosynth'. Recommendations are made for optimal conditions under which forest structure measurements should be obtained with UAS-SFM remote sensing. Ultimately remote sensing of vegetation by computer vision offers the potential to provide an 'ecologist's eye view', capturing not only canopy 3D and spectral properties, but also seeing the trees in the forest and the leaves on the trees.

A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

Treesearch

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...

Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems

PubMed Central

Ehsan, Shoaib; Clark, Adrian F.; ur Rehman, Naveed; McDonald-Maier, Klaus D.

2015-01-01

The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems. PMID:26184211

Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems.

PubMed

Ehsan, Shoaib; Clark, Adrian F; Naveed ur Rehman; McDonald-Maier, Klaus D

2015-07-10

The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Research on an autonomous vision-guided helicopter

NASA Technical Reports Server (NTRS)

Amidi, Omead; Mesaki, Yuji; Kanade, Takeo

1994-01-01

Integration of computer vision with on-board sensors to autonomously fly helicopters was researched. The key components developed were custom designed vision processing hardware and an indoor testbed. The custom designed hardware provided flexible integration of on-board sensors with real-time image processing resulting in a significant improvement in vision-based state estimation. The indoor testbed provided convenient calibrated experimentation in constructing real autonomous systems.

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision.

PubMed

Heinrich, Andreas; Güttler, Felix; Wendt, Sebastian; Schenkl, Sebastian; Hubig, Michael; Wagner, Rebecca; Mall, Gita; Teichgräber, Ulf

2018-06-18

 In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by comparison between antemortem and postmortem PR using computer vision.  The study includes 43 467 PRs from 24 545 patients (46 % females/54 % males). All PRs were filtered and evaluated with Matlab R2014b including the toolboxes image processing and computer vision system. The matching process used the SURF feature to find the corresponding points between two PRs (unknown person and database entry) out of the whole database.  From 40 randomly selected persons, 34 persons (85 %) could be reliably identified by corresponding PR matching points between an already existing scan in the database and the most recent PR. The systematic matching yielded a maximum of 259 points for a successful identification between two different PRs of the same person and a maximum of 12 corresponding matching points for other non-identical persons in the database. Hence 12 matching points are the threshold for reliable assignment.  Operating with an automatic PR system and computer vision could be a successful and reliable tool for identification purposes. The applied method distinguishes itself by virtue of its fast and reliable identification of persons by PR. This Identification method is suitable even if dental characteristics were removed or added in the past. The system seems to be robust for large amounts of data.   · Computer vision allows an automated antemortem and postmortem comparison of panoramic radiographs (PRs) for person identification.. · The present method is able to find identical matching partners among huge datasets (big data) in a short computing time.. · The identification method is suitable even if dental characteristics were removed or added.. · Heinrich A, Güttler F, Wendt S et al. Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision. Fortschr Röntgenstr 2018; DOI: 10.1055/a-0632-4744. © Georg Thieme Verlag KG Stuttgart · New York.

A vision-based end-point control for a two-link flexible manipulator. M.S. Thesis

NASA Technical Reports Server (NTRS)

Obergfell, Klaus

1991-01-01

The measurement and control of the end-effector position of a large two-link flexible manipulator are investigated. The system implementation is described and an initial algorithm for static end-point positioning is discussed. Most existing robots are controlled through independent joint controllers, while the end-effector position is estimated from the joint positions using a kinematic relation. End-point position feedback can be used to compensate for uncertainty and structural deflections. Such feedback is especially important for flexible robots. Computer vision is utilized to obtain end-point position measurements. A look-and-move control structure alleviates the disadvantages of the slow and variable computer vision sampling frequency. This control structure consists of an inner joint-based loop and an outer vision-based loop. A static positioning algorithm was implemented and experimentally verified. This algorithm utilizes the manipulator Jacobian to transform a tip position error to a joint error. The joint error is then used to give a new reference input to the joint controller. The convergence of the algorithm is demonstrated experimentally under payload variation. A Landmark Tracking System (Dickerson, et al 1990) is used for vision-based end-point measurements. This system was modified and tested. A real-time control system was implemented on a PC and interfaced with the vision system and the robot.

Benefit from NASA

NASA Image and Video Library

1985-01-01

The NASA imaging processing technology, an advanced computer technique to enhance images sent to Earth in digital form by distant spacecraft, helped develop a new vision screening process. The Ocular Vision Screening system, an important step in preventing vision impairment, is a portable device designed especially to detect eye problems in children through the analysis of retinal reflexes.

Understanding and preventing computer vision syndrome.

PubMed

Loh, Ky; Redd, Sc

2008-01-01

The invention of computer and advancement in information technology has revolutionized and benefited the society but at the same time has caused symptoms related to its usage such as ocular sprain, irritation, redness, dryness, blurred vision and double vision. This cluster of symptoms is known as computer vision syndrome which is characterized by the visual symptoms which result from interaction with computer display or its environment. Three major mechanisms that lead to computer vision syndrome are extraocular mechanism, accommodative mechanism and ocular surface mechanism. The visual effects of the computer such as brightness, resolution, glare and quality all are known factors that contribute to computer vision syndrome. Prevention is the most important strategy in managing computer vision syndrome. Modification in the ergonomics of the working environment, patient education and proper eye care are crucial in managing computer vision syndrome.

Smartphone, tablet computer and e-reader use by people with vision impairment.

PubMed

Crossland, Michael D; Silva, Rui S; Macedo, Antonio F

2014-09-01

Consumer electronic devices such as smartphones, tablet computers, and e-book readers have become far more widely used in recent years. Many of these devices contain accessibility features such as large print and speech. Anecdotal experience suggests people with vision impairment frequently make use of these systems. Here we survey people with self-identified vision impairment to determine their use of this equipment. An internet-based survey was advertised to people with vision impairment by word of mouth, social media, and online. Respondents were asked demographic information, what devices they owned, what they used these devices for, and what accessibility features they used. One hundred and thirty-two complete responses were received. Twenty-six percent of the sample reported that they had no vision and the remainder reported they had low vision. One hundred and seven people (81%) reported using a smartphone. Those with no vision were as likely to use a smartphone or tablet as those with low vision. Speech was found useful by 59% of smartphone users. Fifty-one percent of smartphone owners used the camera and screen as a magnifier. Forty-eight percent of the sample used a tablet computer, and 17% used an e-book reader. The most frequently cited reason for not using these devices included cost and lack of interest. Smartphones, tablet computers, and e-book readers can be used by people with vision impairment. Speech is used by people with low vision as well as those with no vision. Many of our (self-selected) group used their smartphone camera and screen as a magnifier, and others used the camera flash as a spotlight. © 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists.

A Logical Basis In The Layered Computer Vision Systems Model

NASA Astrophysics Data System (ADS)

Tejwani, Y. J.

1986-03-01

In this paper a four layer computer vision system model is described. The model uses a finite memory scratch pad. In this model planar objects are defined as predicates. Predicates are relations on a k-tuple. The k-tuple consists of primitive points and relationship between primitive points. The relationship between points can be of the direct type or the indirect type. Entities are goals which are satisfied by a set of clauses. The grammar used to construct these clauses is examined.

Head pose estimation in computer vision: a survey.

PubMed

Murphy-Chutorian, Erik; Trivedi, Mohan Manubhai

2009-04-01

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.

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

PubMed Central

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

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems. PMID:28079187

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

PubMed

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

2017-01-12

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

Knowledge-based vision and simple visual machines.

PubMed Central

Cliff, D; Noble, J

1997-01-01

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong. PMID:9304684

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

PubMed Central

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system. PMID:22736956

A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

PubMed

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

Visual Turing test for computer vision systems

PubMed Central

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

2015-01-01

Today, computer vision systems are tested by their accuracy in detecting and localizing instances of objects. As an alternative, and motivated by the ability of humans to provide far richer descriptions and even tell a story about an image, we construct a “visual Turing test”: an operator-assisted device that produces a stochastic sequence of binary questions from a given test image. The query engine proposes a question; the operator either provides the correct answer or rejects the question as ambiguous; the engine proposes the next question (“just-in-time truthing”). The test is then administered to the computer-vision system, one question at a time. After the system’s answer is recorded, the system is provided the correct answer and the next question. Parsing is trivial and deterministic; the system being tested requires no natural language processing. The query engine employs statistical constraints, learned from a training set, to produce questions with essentially unpredictable answers—the answer to a question, given the history of questions and their correct answers, is nearly equally likely to be positive or negative. In this sense, the test is only about vision. The system is designed to produce streams of questions that follow natural story lines, from the instantiation of a unique object, through an exploration of its properties, and on to its relationships with other uniquely instantiated objects. PMID:25755262

Future Automated Rough Mills Hinge on Vision Systems

Treesearch

Philip A. Araman

1996-01-01

The backbone behind major changes to present and future rough mills in dimension, furniture, cabinet or millwork facilities will be computer vision systems. Because of the wide variety of products and the quality of parts produced, the scanning systems and rough mills will vary greatly. The scanners will vary in type. For many complicated applications, multiple scanner...

Microwave vision for robots

NASA Technical Reports Server (NTRS)

Lewandowski, Leon; Struckman, Keith

1994-01-01

Microwave Vision (MV), a concept originally developed in 1985, could play a significant role in the solution to robotic vision problems. Originally our Microwave Vision concept was based on a pattern matching approach employing computer based stored replica correlation processing. Artificial Neural Network (ANN) processor technology offers an attractive alternative to the correlation processing approach, namely the ability to learn and to adapt to changing environments. This paper describes the Microwave Vision concept, some initial ANN-MV experiments, and the design of an ANN-MV system that has led to a second patent disclosure in the robotic vision field.

Analog "neuronal" networks in early vision.

PubMed Central

Koch, C; Marroquin, J; Yuille, A

1986-01-01

Many problems in early vision can be formulated in terms of minimizing a cost function. Examples are shape from shading, edge detection, motion analysis, structure from motion, and surface interpolation. As shown by Poggio and Koch [Poggio, T. & Koch, C. (1985) Proc. R. Soc. London, Ser. B 226, 303-323], quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical, or chemical networks. However, in the presence of discontinuities, the cost function is nonquadratic, raising the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank [Hopfield, J. J. & Tank, D. W. (1985) Biol. Cybern. 52, 141-152] have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. We show how these networks can be generalized to solve the nonconvex energy functionals of early vision. We illustrate this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities. These results suggest a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems. PMID:3459172

HRV based health&sport markers using video from the face.

PubMed

Capdevila, Lluis; Moreno, Jordi; Movellan, Javier; Parrado, Eva; Ramos-Castro, Juan

2012-01-01

Heart Rate Variability (HRV) is an indicator of health status in the general population and of adaptation to stress in athletes. In this paper we compare the performance of two systems to measure HRV: (1) A commercial system based on recording the physiological cardiac signal with (2) A computer vision system that uses a standard video images of the face to estimate RR from changes in skin color of the face. We show that the computer vision system performs surprisingly well. It estimates individual RR intervals in a non-invasive manner and with error levels comparable to those achieved by the physiological based system.

Predicting pork loin intramuscular fat using computer vision system.

PubMed

Liu, J-H; Sun, X; Young, J M; Bachmeier, L A; Newman, D J

2018-09-01

The objective of this study was to investigate the ability of computer vision system to predict pork intramuscular fat percentage (IMF%). Center-cut loin samples (n = 85) were trimmed of subcutaneous fat and connective tissue. Images were acquired and pixels were segregated to estimate image IMF% and 18 image color features for each image. Subjective IMF% was determined by a trained grader. Ether extract IMF% was calculated using ether extract method. Image color features and image IMF% were used as predictors for stepwise regression and support vector machine models. Results showed that subjective IMF% had a correlation of 0.81 with ether extract IMF% while the image IMF% had a 0.66 correlation with ether extract IMF%. Accuracy rates for regression models were 0.63 for stepwise and 0.75 for support vector machine. Although subjective IMF% has shown to have better prediction, results from computer vision system demonstrates the potential of being used as a tool in predicting pork IMF% in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computer vision in roadway transportation systems: a survey

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

PubMed Central

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-01-01

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

PubMed

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-03-20

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

Vector disparity sensor with vergence control for active vision systems.

PubMed

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

2012-01-01

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

Vector Disparity Sensor with Vergence Control for Active Vision Systems

PubMed Central

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

2012-01-01

This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system. PMID:22438737

Clinical efficacy of Ayurvedic management in computer vision syndrome: A pilot study.

PubMed

Dhiman, Kartar Singh; Ahuja, Deepak Kumar; Sharma, Sanjeev Kumar

2012-07-01

Improper use of sense organs, violating the moral code of conduct, and the effect of the time are the three basic causative factors behind all the health problems. Computer, the knowledge bank of modern life, has emerged as a profession causing vision-related discomfort, ocular fatigue, and systemic effects. Computer Vision Syndrome (CVS) is the new nomenclature to the visual, ocular, and systemic symptoms arising due to the long time and improper working on the computer and is emerging as a pandemic in the 21(st) century. On critical analysis of the symptoms of CVS on Tridoshika theory of Ayurveda, as per the road map given by Acharya Charaka, it seems to be a Vata-Pittaja ocular cum systemic disease which needs systemic as well as topical treatment approach. Shatavaryaadi Churna (orally), Go-Ghrita Netra Tarpana (topically), and counseling regarding proper working conditions on computer were tried in 30 patients of CVS. In group I, where oral and local treatment was given, significant improvement in all the symptoms of CVS was observed, whereas in groups II and III, local treatment and counseling regarding proper working conditions, respectively, were given and showed insignificant results. The study verified the hypothesis that CVS in Ayurvedic perspective is a Vata-Pittaja disease affecting mainly eyes and body as a whole and needs a systemic intervention rather than topical ocular medication only.

Clinical efficacy of Ayurvedic management in computer vision syndrome: A pilot study

PubMed Central

Dhiman, Kartar Singh; Ahuja, Deepak Kumar; Sharma, Sanjeev Kumar

2012-01-01

Improper use of sense organs, violating the moral code of conduct, and the effect of the time are the three basic causative factors behind all the health problems. Computer, the knowledge bank of modern life, has emerged as a profession causing vision-related discomfort, ocular fatigue, and systemic effects. Computer Vision Syndrome (CVS) is the new nomenclature to the visual, ocular, and systemic symptoms arising due to the long time and improper working on the computer and is emerging as a pandemic in the 21st century. On critical analysis of the symptoms of CVS on Tridoshika theory of Ayurveda, as per the road map given by Acharya Charaka, it seems to be a Vata–Pittaja ocular cum systemic disease which needs systemic as well as topical treatment approach. Shatavaryaadi Churna (orally), Go-Ghrita Netra Tarpana (topically), and counseling regarding proper working conditions on computer were tried in 30 patients of CVS. In group I, where oral and local treatment was given, significant improvement in all the symptoms of CVS was observed, whereas in groups II and III, local treatment and counseling regarding proper working conditions, respectively, were given and showed insignificant results. The study verified the hypothesis that CVS in Ayurvedic perspective is a Vata–Pittaja disease affecting mainly eyes and body as a whole and needs a systemic intervention rather than topical ocular medication only. PMID:23723647

Method of mobile robot indoor navigation by artificial landmarks with use of computer vision

NASA Astrophysics Data System (ADS)

Glibin, E. S.; Shevtsov, A. A.; Enik, O. A.

2018-05-01

The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.

Bird Vision System

NASA Technical Reports Server (NTRS)

2008-01-01

The Bird Vision system is a multicamera photogrammerty software application that runs on a Microsoft Windows XP platform and was developed at Kennedy Space Center by ASRC Aerospace. This software system collects data about the locations of birds within a volume centered on the Space Shuttle and transmits it in real time to the laptop computer of a test director in the Launch Control Center (LCC) Firing Room.

Color vision testing with a computer graphics system: preliminary results.

PubMed

Arden, G; Gündüz, K; Perry, S

1988-06-01

We report a method for computer enhancement of color vision tests. In our graphics system 256 colors are selected from a much larger range and displayed on a screen divided into 768 x 288 pixels. Eight-bit digital-to-analogue converters drive a high quality monitor with separate inputs to the red, green, and blue amplifiers and calibrated gun chromaticities. The graphics are controlled by a PASCAL program written for a personal computer, which calculates the values of the red, green, and blue signals and specifies them in Commité Internationale d'Eclairage X, Y, and Z fundamentals, so changes in chrominance occur without changes in luminance. The system for measuring color contrast thresholds with gratings is more than adequate in normal observers. In patients with mild retinal damage in whom other tests of visual function are normal, this method of testing color vision shows specific increases in contrast thresholds along tritan color-confusion lines. By the time the Hardy-Rand-Rittler and Farnsworth-Munsell 100-hue tests disclose abnormalities, gross defects in color contrast threshold can be seen with our system.

Smart vision chips: An overview

NASA Technical Reports Server (NTRS)

Koch, Christof

1994-01-01

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

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

NASA Technical Reports Server (NTRS)

Pinz, Axel J.

1991-01-01

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

Optimized feature-detection for on-board vision-based surveillance

NASA Astrophysics Data System (ADS)

Gond, Laetitia; Monnin, David; Schneider, Armin

2012-06-01

The detection and matching of robust features in images is an important step in many computer vision applications. In this paper, the importance of the keypoint detection algorithms and their inherent parameters in the particular context of an image-based change detection system for IED detection is studied. Through extensive application-oriented experiments, we draw an evaluation and comparison of the most popular feature detectors proposed by the computer vision community. We analyze how to automatically adjust these algorithms to changing imaging conditions and suggest improvements in order to achieve more exibility and robustness in their practical implementation.

Autonomic Computing: Panacea or Poppycock?

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

Autonomic Computing arose out of a need for a means to cope with rapidly growing complexity of integrating, managing, and operating computer-based systems as well as a need to reduce the total cost of ownership of today's systems. Autonomic Computing (AC) as a discipline was proposed by IBM in 2001, with the vision to develop self-managing systems. As the name implies, the influence for the new paradigm is the human body's autonomic system, which regulates vital bodily functions such as the control of heart rate, the body's temperature and blood flow-all without conscious effort. The vision is to create selfivare through self-* properties. The initial set of properties, in terms of objectives, were self-configuring, self-healing, self-optimizing and self-protecting, along with attributes of self-awareness, self-monitoring and self-adjusting. This self-* list has grown: self-anticipating, self-critical, self-defining, self-destructing, self-diagnosis, self-governing, self-organized, self-reflecting, and self-simulation, for instance.

A computer architecture for intelligent machines

NASA Technical Reports Server (NTRS)

Lefebvre, D. R.; Saridis, G. N.

1991-01-01

The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Robot computer problem solving system

NASA Technical Reports Server (NTRS)

Merriam, E. W.; Becker, J. D.

1973-01-01

A robot computer problem solving system which represents a robot exploration vehicle in a simulated Mars environment is described. The model exhibits changes and improvements made on a previously designed robot in a city environment. The Martian environment is modeled in Cartesian coordinates; objects are scattered about a plane; arbitrary restrictions on the robot's vision have been removed; and the robot's path contains arbitrary curves. New environmental features, particularly the visual occlusion of objects by other objects, were added to the model. Two different algorithms were developed for computing occlusion. Movement and vision capabilities of the robot were established in the Mars environment, using LISP/FORTRAN interface for computational efficiency. The graphical display program was redesigned to reflect the change to the Mars-like environment.

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

An architecture for real-time vision processing

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong

1994-01-01

To study the feasibility of developing an architecture for real time vision processing, a task queue server and parallel algorithms for two vision operations were designed and implemented on an i860-based Mercury Computing System 860VS array processor. The proposed architecture treats each vision function as a task or set of tasks which may be recursively divided into subtasks and processed by multiple processors coordinated by a task queue server accessible by all processors. Each idle processor subsequently fetches a task and associated data from the task queue server for processing and posts the result to shared memory for later use. Load balancing can be carried out within the processing system without the requirement for a centralized controller. The author concludes that real time vision processing cannot be achieved without both sequential and parallel vision algorithms and a good parallel vision architecture.

A FPGA-based architecture for real-time image matching

NASA Astrophysics Data System (ADS)

Wang, Jianhui; Zhong, Sheng; Xu, Wenhui; Zhang, Weijun; Cao, Zhiguo

2013-10-01

Image matching is a fundamental task in computer vision. It is used to establish correspondence between two images taken at different viewpoint or different time from the same scene. However, its large computational complexity has been a challenge to most embedded systems. This paper proposes a single FPGA-based image matching system, which consists of SIFT feature detection, BRIEF descriptor extraction and BRIEF matching. It optimizes the FPGA architecture for the SIFT feature detection to reduce the FPGA resources utilization. Moreover, we implement BRIEF description and matching on FPGA also. The proposed system can implement image matching at 30fps (frame per second) for 1280x720 images. Its processing speed can meet the demand of most real-life computer vision applications.

Comparison of progressive addition lenses for general purpose and for computer vision: an office field study.

PubMed

Jaschinski, Wolfgang; König, Mirjam; Mekontso, Tiofil M; Ohlendorf, Arne; Welscher, Monique

2015-05-01

Two types of progressive addition lenses (PALs) were compared in an office field study: 1. General purpose PALs with continuous clear vision between infinity and near reading distances and 2. Computer vision PALs with a wider zone of clear vision at the monitor and in near vision but no clear distance vision. Twenty-three presbyopic participants wore each type of lens for two weeks in a double-masked four-week quasi-experimental procedure that included an adaptation phase (Weeks 1 and 2) and a test phase (Weeks 3 and 4). Questionnaires on visual and musculoskeletal conditions as well as preferences regarding the type of lenses were administered. After eight more weeks of free use of the spectacles, the preferences were assessed again. The ergonomic conditions were analysed from photographs. Head inclination when looking at the monitor was significantly lower by 2.3 degrees with the computer vision PALs than with the general purpose PALs. Vision at the monitor was judged significantly better with computer PALs, while distance vision was judged better with general purpose PALs; however, the reported advantage of computer vision PALs differed in extent between participants. Accordingly, 61 per cent of the participants preferred the computer vision PALs, when asked without information about lens design. After full information about lens characteristics and additional eight weeks of free spectacle use, 44 per cent preferred the computer vision PALs. On average, computer vision PALs were rated significantly better with respect to vision at the monitor during the experimental part of the study. In the final forced-choice ratings, approximately half of the participants preferred either the computer vision PAL or the general purpose PAL. Individual factors seem to play a role in this preference and in the rated advantage of computer vision PALs. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Parallel Algorithms for Computer Vision

DTIC Science & Technology

1990-04-01

NA86-1, Thinking Machines Corporation, Cambridge, MA, December 1986. [43] J. Little, G. Blelloch, and T. Cass. How to program the connection machine for... to program the connection machine for computer vision. In Proc. Workshop on Comp. Architecture for Pattern Analysis and Machine Intell., 1987. [92] J...In Proceedings of SPIE Conf. on Advances in Intelligent Robotics Systems, Bellingham, VA, 1987. SPIE. [91] J. Little, G. Blelloch, and T. Cass. How

Image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

NETRA: A parallel architecture for integrated vision systems. 1: Architecture and organization

NASA Technical Reports Server (NTRS)

Choudhary, Alok N.; Patel, Janak H.; Ahuja, Narendra

1989-01-01

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is considered to be a system that uses vision algorithms from all levels of processing for a high level application (such as object recognition). A model of computation is presented for parallel processing for an IVS. Using the model, desired features and capabilities of a parallel architecture suitable for IVSs are derived. Then a multiprocessor architecture (called NETRA) is presented. This architecture is highly flexible without the use of complex interconnection schemes. The topology of NETRA is recursively defined and hence is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. It is a recursively defined tree-type hierarchical architecture where each of the leaf nodes consists of a cluster of processors connected with a programmable crossbar with selective broadcast capability to provide for desired flexibility. A qualitative evaluation of NETRA is presented. Then general schemes are described to map parallel algorithms onto NETRA. Algorithms are classified according to their communication requirements for parallel processing. An extensive analysis of inter-cluster communication strategies in NETRA is presented, and parameters affecting performance of parallel algorithms when mapped on NETRA are discussed. Finally, a methodology to evaluate performance of algorithms on NETRA is described.

Task-focused modeling in automated agriculture

NASA Astrophysics Data System (ADS)

Vriesenga, Mark R.; Peleg, K.; Sklansky, Jack

1993-01-01

Machine vision systems analyze image data to carry out automation tasks. Our interest is in machine vision systems that rely on models to achieve their designed task. When the model is interrogated from an a priori menu of questions, the model need not be complete. Instead, the machine vision system can use a partial model that contains a large amount of information in regions of interest and less information elsewhere. We propose an adaptive modeling scheme for machine vision, called task-focused modeling, which constructs a model having just sufficient detail to carry out the specified task. The model is detailed in regions of interest to the task and is less detailed elsewhere. This focusing effect saves time and reduces the computational effort expended by the machine vision system. We illustrate task-focused modeling by an example involving real-time micropropagation of plants in automated agriculture.

Machine vision system for inspecting characteristics of hybrid rice seed

NASA Astrophysics Data System (ADS)

Cheng, Fang; Ying, Yibin

2004-03-01

Obtaining clear images advantaged of improving the classification accuracy involves many factors, light source, lens extender and background were discussed in this paper. The analysis of rice seed reflectance curves showed that the wavelength of light source for discrimination of the diseased seeds from normal rice seeds in the monochromic image recognition mode was about 815nm for jinyou402 and shanyou10. To determine optimizing conditions for acquiring digital images of rice seed using a computer vision system, an adjustable color machine vision system was developed. The machine vision system with 20mm to 25mm lens extender produce close-up images which made it easy to object recognition of characteristics in hybrid rice seeds. White background was proved to be better than black background for inspecting rice seeds infected by disease and using the algorithms based on shape. Experimental results indicated good classification for most of the characteristics with the machine vision system. The same algorithm yielded better results in optimizing condition for quality inspection of rice seed. Specifically, the image processing can correct for details such as fine fissure with the machine vision system.

Investigation of safety analysis methods using computer vision techniques

NASA Astrophysics Data System (ADS)

Shirazi, Mohammad Shokrolah; Morris, Brendan Tran

2017-09-01

This work investigates safety analysis methods using computer vision techniques. The vision-based tracking system is developed to provide the trajectory of road users including vehicles and pedestrians. Safety analysis methods are developed to estimate time to collision (TTC) and postencroachment time (PET) that are two important safety measurements. Corresponding algorithms are presented and their advantages and drawbacks are shown through their success in capturing the conflict events in real time. The performance of the tracking system is evaluated first, and probability density estimation of TTC and PET are shown for 1-h monitoring of a Las Vegas intersection. Finally, an idea of an intersection safety map is introduced, and TTC values of two different intersections are estimated for 1 day from 8:00 a.m. to 6:00 p.m.

Non-Boolean computing with nanomagnets for computer vision applications

NASA Astrophysics Data System (ADS)

Bhanja, Sanjukta; Karunaratne, D. K.; Panchumarthy, Ravi; Rajaram, Srinath; Sarkar, Sudeep

2016-02-01

The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high-speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms. Here, we harness the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, we develop a magnetic Hamiltonian and implement it in a magnetic system that can identify the salient features of a given image with more than 85% true positive rate. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.

SailSpy: a vision system for yacht sail shape measurement

NASA Astrophysics Data System (ADS)

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

1992-11-01

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

Image segmentation for enhancing symbol recognition in prosthetic vision.

PubMed

Horne, Lachlan; Barnes, Nick; McCarthy, Chris; He, Xuming

2012-01-01

Current and near-term implantable prosthetic vision systems offer the potential to restore some visual function, but suffer from poor resolution and dynamic range of induced phosphenes. This can make it difficult for users of prosthetic vision systems to identify symbolic information (such as signs) except in controlled conditions. Using image segmentation techniques from computer vision, we show it is possible to improve the clarity of such symbolic information for users of prosthetic vision implants in uncontrolled conditions. We use image segmentation to automatically divide a natural image into regions, and using a fixation point controlled by the user, select a region to phosphenize. This technique improves the apparent contrast and clarity of symbolic information over traditional phosphenization approaches.

Vision Based Localization in Urban Environments

NASA Technical Reports Server (NTRS)

McHenry, Michael; Cheng, Yang; Matthies, Larry

2005-01-01

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

Sustainable and Autonomic Space Exploration Missions

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Sterritt, Roy; Rouff, Christopher; Rash, James L.; Truszkowski, Walter

2006-01-01

Visions for future space exploration have long term science missions in sight, resulting in the need for sustainable missions. Survivability is a critical property of sustainable systems and may be addressed through autonomicity, an emerging paradigm for self-management of future computer-based systems based on inspiration from the human autonomic nervous system. This paper examines some of the ongoing research efforts to realize these survivable systems visions, with specific emphasis on developments in Autonomic Policies.

Spatial distribution of clinical computer systems in primary care in England in 2016 and implications for primary care electronic medical record databases: a cross-sectional population study.

PubMed

Kontopantelis, Evangelos; Stevens, Richard John; Helms, Peter J; Edwards, Duncan; Doran, Tim; Ashcroft, Darren M

2018-02-28

UK primary care databases (PCDs) are used by researchers worldwide to inform clinical practice. These databases have been primarily tied to single clinical computer systems, but little is known about the adoption of these systems by primary care practices or their geographical representativeness. We explore the spatial distribution of clinical computing systems and discuss the implications for the longevity and regional representativeness of these resources. Cross-sectional study. English primary care clinical computer systems. 7526 general practices in August 2016. Spatial mapping of family practices in England in 2016 by clinical computer system at two geographical levels, the lower Clinical Commissioning Group (CCG, 209 units) and the higher National Health Service regions (14 units). Data for practices included numbers of doctors, nurses and patients, and area deprivation. Of 7526 practices, Egton Medical Information Systems (EMIS) was used in 4199 (56%), SystmOne in 2552 (34%) and Vision in 636 (9%). Great regional variability was observed for all systems, with EMIS having a stronger presence in the West of England, London and the South; SystmOne in the East and some regions in the South; and Vision in London, the South, Greater Manchester and Birmingham. PCDs based on single clinical computer systems are geographically clustered in England. For example, Clinical Practice Research Datalink and The Health Improvement Network, the most popular primary care databases in terms of research outputs, are based on the Vision clinical computer system, used by <10% of practices and heavily concentrated in three major conurbations and the South. Researchers need to be aware of the analytical challenges posed by clustering, and barriers to accessing alternative PCDs need to be removed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Medical informatics and telemedicine: A vision

NASA Technical Reports Server (NTRS)

Clemmer, Terry P.

1991-01-01

The goal of medical informatics is to improve care. This requires the commitment and harmonious collaboration between the computer scientists and clinicians and an integrated database. The vision described is how medical information systems are going to impact the way medical care is delivered in the future.

Protyping machine vision software on the World Wide Web

NASA Astrophysics Data System (ADS)

Karantalis, George; Batchelor, Bruce G.

1998-10-01

Interactive image processing is a proven technique for analyzing industrial vision applications and building prototype systems. Several of the previous implementations have used dedicated hardware to perform the image processing, with a top layer of software providing a convenient user interface. More recently, self-contained software packages have been devised and these run on a standard computer. The advent of the Java programming language has made it possible to write platform-independent software, operating over the Internet, or a company-wide Intranet. Thus, there arises the possibility of designing at least some shop-floor inspection/control systems, without the vision engineer ever entering the factories where they will be used. It successful, this project will have a major impact on the productivity of vision systems designers.

Development of embedded real-time and high-speed vision platform

NASA Astrophysics Data System (ADS)

Ouyang, Zhenxing; Dong, Yimin; Yang, Hua

2015-12-01

Currently, high-speed vision platforms are widely used in many applications, such as robotics and automation industry. However, a personal computer (PC) whose over-large size is not suitable and applicable in compact systems is an indispensable component for human-computer interaction in traditional high-speed vision platforms. Therefore, this paper develops an embedded real-time and high-speed vision platform, ER-HVP Vision which is able to work completely out of PC. In this new platform, an embedded CPU-based board is designed as substitution for PC and a DSP and FPGA board is developed for implementing image parallel algorithms in FPGA and image sequential algorithms in DSP. Hence, the capability of ER-HVP Vision with size of 320mm x 250mm x 87mm can be presented in more compact condition. Experimental results are also given to indicate that the real-time detection and counting of the moving target at a frame rate of 200 fps at 512 x 512 pixels under the operation of this newly developed vision platform are feasible.

The "Biologically-Inspired Computing" Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2007-01-01

Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.

Computer vision syndrome: a review.

PubMed

Blehm, Clayton; Vishnu, Seema; Khattak, Ashbala; Mitra, Shrabanee; Yee, Richard W

2005-01-01

As computers become part of our everyday life, more and more people are experiencing a variety of ocular symptoms related to computer use. These include eyestrain, tired eyes, irritation, redness, blurred vision, and double vision, collectively referred to as computer vision syndrome. This article describes both the characteristics and treatment modalities that are available at this time. Computer vision syndrome symptoms may be the cause of ocular (ocular-surface abnormalities or accommodative spasms) and/or extraocular (ergonomic) etiologies. However, the major contributor to computer vision syndrome symptoms by far appears to be dry eye. The visual effects of various display characteristics such as lighting, glare, display quality, refresh rates, and radiation are also discussed. Treatment requires a multidirectional approach combining ocular therapy with adjustment of the workstation. Proper lighting, anti-glare filters, ergonomic positioning of computer monitor and regular work breaks may help improve visual comfort. Lubricating eye drops and special computer glasses help relieve ocular surface-related symptoms. More work needs to be done to specifically define the processes that cause computer vision syndrome and to develop and improve effective treatments that successfully address these causes.

High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations

NASA Technical Reports Server (NTRS)

Parks, John (Technical Monitor); Biswas, Rupak; Yan, Jerry C.; Brooks, Walter F.; Sterling, Thomas L.

2003-01-01

Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.

A programmable computational image sensor for high-speed vision

NASA Astrophysics Data System (ADS)

Yang, Jie; Shi, Cong; Long, Xitian; Wu, Nanjian

2013-08-01

In this paper we present a programmable computational image sensor for high-speed vision. This computational image sensor contains four main blocks: an image pixel array, a massively parallel processing element (PE) array, a row processor (RP) array and a RISC core. The pixel-parallel PE is responsible for transferring, storing and processing image raw data in a SIMD fashion with its own programming language. The RPs are one dimensional array of simplified RISC cores, it can carry out complex arithmetic and logic operations. The PE array and RP array can finish great amount of computation with few instruction cycles and therefore satisfy the low- and middle-level high-speed image processing requirement. The RISC core controls the whole system operation and finishes some high-level image processing algorithms. We utilize a simplified AHB bus as the system bus to connect our major components. Programming language and corresponding tool chain for this computational image sensor are also developed.

Quaternions in computer vision and robotics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pervin, E.; Webb, J.A.

1982-01-01

Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many properties of quaternions that are relevant to computer vision and robotics are developed. Examples are given showing how quaternions can be used to simplify derivations in computer vision and robotics.

A Talking Computers System for Persons with Vision and Speech Handicaps. Final Report.

ERIC Educational Resources Information Center

Visek & Maggs, Urbana, IL.

This final report contains a detailed description of six software systems designed to assist individuals with blindness and/or speech disorders in using inexpensive, off-the-shelf computers rather than expensive custom-made devices. The developed software is not written in the native machine language of any particular brand of computer, but in the…

Fuzzy logic control of an AGV

NASA Astrophysics Data System (ADS)

Kelkar, Nikhal; Samu, Tayib; Hall, Ernest L.

1997-09-01

Automated guided vehicles (AGVs) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The controller incorporates a fuzzy logic approach for steering and speed control, a neuro-fuzzy approach for ultrasound sensing (not discussed in this paper) and an overall expert system. The advantages of a modular system are related to portability and transportability, i.e. any vehicle can become autonomous with minimal modifications. A mobile robot test-bed has been constructed using a golf cart base. This cart has full speed control with guidance provided by a vision system and obstacle avoidance using ultrasonic sensors. The speed and steering fuzzy logic controller is supervised by a 486 computer through a multi-axis motion controller. The obstacle avoidance system is based on a micro-controller interfaced with six ultrasonic transducers. This micro- controller independently handles all timing and distance calculations and sends a steering angle correction back to the computer via the serial line. This design yields a portable independent system in which high speed computer communication is not necessary. Vision guidance is accomplished with a CCD camera with a zoom lens. The data is collected by a vision tracking device that transmits the X, Y coordinates of the lane marker to the control computer. Simulation and testing of these systems yielded promising results. This design, in its modularity, creates a portable autonomous fuzzy logic controller applicable to any mobile vehicle with only minor adaptations.

Machine Vision For Industrial Control:The Unsung Opportunity

NASA Astrophysics Data System (ADS)

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.

Benchmarking neuromorphic vision: lessons learnt from computer vision

PubMed Central

Tan, Cheston; Lallee, Stephane; Orchard, Garrick

2015-01-01

Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, while algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision. PMID:26528120

Implementing the President's Vision: JPL and NASA's Exploration Systems Mission Directorate

NASA Technical Reports Server (NTRS)

Sander, Michael J.

2006-01-01

As part of the NASA team the Jet Propulsion Laboratory is involved in the Exploration Systems Mission Directorate (ESMD) work to implement the President's Vision for Space exploration. In this slide presentation the roles that are assigned to the various NASA centers to implement the vision are reviewed. The plan for JPL is to use the Constellation program to advance the combination of science an Constellation program objectives. JPL's current participation is to contribute systems engineering support, Command, Control, Computing and Information (C3I) architecture, Crew Exploration Vehicle, (CEV) Thermal Protection System (TPS) project support/CEV landing assist support, Ground support systems support at JSC and KSC, Exploration Communication and Navigation System (ECANS), Flight prototypes for cabin atmosphere instruments

TU-FG-201-04: Computer Vision in Autonomous Quality Assurance of Linear Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, H; Jenkins, C; Yu, S

Purpose: Routine quality assurance (QA) of linear accelerators represents a critical and costly element of a radiation oncology center. Recently, a system was developed to autonomously perform routine quality assurance on linear accelerators. The purpose of this work is to extend this system and contribute computer vision techniques for obtaining quantitative measurements for a monthly multi-leaf collimator (MLC) QA test specified by TG-142, namely leaf position accuracy, and demonstrate extensibility for additional routines. Methods: Grayscale images of a picket fence delivery on a radioluminescent phosphor coated phantom are captured using a CMOS camera. Collected images are processed to correct formore » camera distortions, rotation and alignment, reduce noise, and enhance contrast. The location of each MLC leaf is determined through logistic fitting and a priori modeling based on knowledge of the delivered beams. Using the data collected and the criteria from TG-142, a decision is made on whether or not the leaf position accuracy of the MLC passes or fails. Results: The locations of all MLC leaf edges are found for three different picket fence images in a picket fence routine to 0.1mm/1pixel precision. The program to correct for image alignment and determination of leaf positions requires a runtime of 21– 25 seconds for a single picket, and 44 – 46 seconds for a group of three pickets on a standard workstation CPU, 2.2 GHz Intel Core i7. Conclusion: MLC leaf edges were successfully found using techniques in computer vision. With the addition of computer vision techniques to the previously described autonomous QA system, the system is able to quickly perform complete QA routines with minimal human contribution.« less

Gesture Therapy: A Vision-Based System for Arm Rehabilitation after Stroke

NASA Astrophysics Data System (ADS)

Sucar, L. Enrique; Azcárate, Gildardo; Leder, Ron S.; Reinkensmeyer, David; Hernández, Jorge; Sanchez, Israel; Saucedo, Pedro

Each year millions of people in the world survive a stroke, in the U.S. alone the figure is over 600,000 people per year. Movement impairments after stroke are typically treated with intensive, hands-on physical and occupational therapy for several weeks after the initial injury. However, due to economic pressures, stroke patients are receiving less therapy and going home sooner, so the potential benefit of the therapy is not completely realized. Thus, it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. Current solutions are too expensive, as they require a robotic system for rehabilitation. We have developed a low-cost, computer vision system that allows individuals with stroke to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a web based virtual environment for facilitating repetitive movement training, with state-of-the art computer vision algorithms that track the hand of a patient and obtain its 3-D coordinates, using two inexpensive cameras and a conventional personal computer. An initial prototype of the system has been evaluated in a pilot clinical study with promising results.

Evaluating the Effects of Dimensionality in Advanced Avionic Display Concepts for Synthetic Vision Systems

NASA Technical Reports Server (NTRS)

Alexander, Amy L.; Prinzel, Lawrence J., III; Wickens, Christopher D.; Kramer, Lynda J.; Arthur, Jarvis J.; Bailey, Randall E.

2007-01-01

Synthetic vision systems provide an in-cockpit view of terrain and other hazards via a computer-generated display representation. Two experiments examined several display concepts for synthetic vision and evaluated how such displays modulate pilot performance. Experiment 1 (24 general aviation pilots) compared three navigational display (ND) concepts: 2D coplanar, 3D, and split-screen. Experiment 2 (12 commercial airline pilots) evaluated baseline 'blue sky/brown ground' or synthetic vision-enabled primary flight displays (PFDs) and three ND concepts: 2D coplanar with and without synthetic vision and a dynamic multi-mode rotatable exocentric format. In general, the results pointed to an overall advantage for a split-screen format, whether it be stand-alone (Experiment 1) or available via rotatable viewpoints (Experiment 2). Furthermore, Experiment 2 revealed benefits associated with utilizing synthetic vision in both the PFD and ND representations and the value of combined ego- and exocentric presentations.

Building a robust vehicle detection and classification module

NASA Astrophysics Data System (ADS)

Grigoryev, Anton; Khanipov, Timur; Koptelov, Ivan; Bocharov, Dmitry; Postnikov, Vassily; Nikolaev, Dmitry

2015-12-01

The growing adoption of intelligent transportation systems (ITS) and autonomous driving requires robust real-time solutions for various event and object detection problems. Most of real-world systems still cannot rely on computer vision algorithms and employ a wide range of costly additional hardware like LIDARs. In this paper we explore engineering challenges encountered in building a highly robust visual vehicle detection and classification module that works under broad range of environmental and road conditions. The resulting technology is competitive to traditional non-visual means of traffic monitoring. The main focus of the paper is on software and hardware architecture, algorithm selection and domain-specific heuristics that help the computer vision system avoid implausible answers.

Synthetic vision in the cockpit: 3D systems for general aviation

NASA Astrophysics Data System (ADS)

Hansen, Andrew J.; Rybacki, Richard M.; Smith, W. Garth

2001-08-01

Synthetic vision has the potential to improve safety in aviation through better pilot situational awareness and enhanced navigational guidance. The technological advances enabling synthetic vision are GPS based navigation (position and attitude) systems and efficient graphical systems for rendering 3D displays in the cockpit. A benefit for military, commercial, and general aviation platforms alike is the relentless drive to miniaturize computer subsystems. Processors, data storage, graphical and digital signal processing chips, RF circuitry, and bus architectures are at or out-pacing Moore's Law with the transition to mobile computing and embedded systems. The tandem of fundamental GPS navigation services such as the US FAA's Wide Area and Local Area Augmentation Systems (WAAS) and commercially viable mobile rendering systems puts synthetic vision well with the the technological reach of general aviation. Given the appropriate navigational inputs, low cost and power efficient graphics solutions are capable of rendering a pilot's out-the-window view into visual databases with photo-specific imagery and geo-specific elevation and feature content. Looking beyond the single airframe, proposed aviation technologies such as ADS-B would provide a communication channel for bringing traffic information on-board and into the cockpit visually via the 3D display for additional pilot awareness. This paper gives a view of current 3D graphics system capability suitable for general aviation and presents a potential road map following the current trends.

Modeling of the First Layers in the Fly's Eye

NASA Technical Reports Server (NTRS)

Moya, J. A.; Wilcox, M. J.; Donohoe, G. W.

1997-01-01

Increased autonomy of robots would yield significant advantages in the exploration of space. The shortfalls of computer vision can, however, pose significant limitations on a robot's potential. At the same time, simple insects which are largely hard-wired have effective visual systems. The understanding of insect vision systems thus may lead to improved approaches to visual tasks. A good starting point for the study of a vision system is its eye. In this paper, a model of the sensory portion of the fly's eye is presented. The effectiveness of the model is briefly addressed by a comparison of its performance to experimental data.

Robotic space simulation integration of vision algorithms into an orbital operations simulation

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1987-01-01

In order to successfully plan and analyze future space activities, computer-based simulations of activities in low earth orbit will be required to model and integrate vision and robotic operations with vehicle dynamics and proximity operations procedures. The orbital operations simulation (OOS) is configured and enhanced as a testbed for robotic space operations. Vision integration algorithms are being developed in three areas: preprocessing, recognition, and attitude/attitude rates. The vision program (Rice University) was modified for use in the OOS. Systems integration testing is now in progress.

Low Cost Night Vision System for Intruder Detection

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

The Cyborg Astrobiologist: scouting red beds for uncommon features with geological significance

NASA Astrophysics Data System (ADS)

McGuire, Patrick Charles; Díaz-Martínez, Enrique; Ormö, Jens; Gómez-Elvira, Javier; Rodríguez-Manfredi, José Antonio; Sebastián-Martínez, Eduardo; Ritter, Helge; Haschke, Robert; Oesker, Markus; Ontrup, Jörg

2005-04-01

The `Cyborg Astrobiologist' has undergone a second geological field trial, at a site in northern Guadalajara, Spain, near Riba de Santiuste. The site at Riba de Santiuste is dominated by layered deposits of red sandstones. The Cyborg Astrobiologist is a wearable computer and video camera system that has demonstrated a capability to find uncommon interest points in geological imagery in real time in the field. In this second field trial, the computer vision system of the Cyborg Astrobiologist was tested at seven different tripod positions, on three different geological structures. The first geological structure was an outcrop of nearly homogeneous sandstone, which exhibits oxidized-iron impurities in red areas and an absence of these iron impurities in white areas. The white areas in these `red beds' have turned white because the iron has been removed. The iron removal from the sandstone can proceed once the iron has been chemically reduced, perhaps by a biological agent. In one instance the computer vision system found several (iron-free) white spots to be uncommon and therefore interesting, as well as several small and dark nodules. The second geological structure was another outcrop some 600 m to the east, with white, textured mineral deposits on the surface of the sandstone, at the bottom of the outcrop. The computer vision system found these white, textured mineral deposits to be interesting. We acquired samples of the mineral deposits for geochemical analysis in the laboratory. This laboratory analysis of the crust identifies a double layer, consisting of an internal millimetre-size layering of calcite and an external centimetre-size efflorescence of gypsum. The third geological structure was a 50 cm thick palaeosol layer, with fossilized root structures of some plants. The computer vision system also found certain areas of these root structures to be interesting. A quasi-blind comparison of the Cyborg Astrobiologist's interest points for these images with the interest points determined afterwards by a human geologist shows that the Cyborg Astrobiologist concurred with the human geologist 68% of the time (true-positive rate), with a 32% false-positive rate and a 32% false-negative rate. The performance of the Cyborg Astrobiologist's computer vision system was by no means perfect, so there is plenty of room for improvement. However, these tests validate the image-segmentation and uncommon-mapping technique that we first employed at a different geological site (Rivas Vaciamadrid) with somewhat different properties for the imagery.

Bio-Inspired Sensing and Imaging of Polarization Information in Nature

DTIC Science & Technology

2008-05-04

polarization imaging,” Appl. Opt. 36, 150–155 (1997). 5. L. B. Wolff, “Polarization camera for computer vision with a beam splitter ,” J. Opt. Soc. Am. A...vision with a beam splitter ,” J. Opt. Soc. Am. A 11, 2935–2945 (1994). 2. L. B. Wolff and A. G. Andreou, “Polarization camera sensors,” Image Vis. Comput...group we have been developing various man-made, non -invasive imaging methodologies, sensing schemes, camera systems, and visualization and display

Feasibility Study and Cost Benefit Analysis of Thin-Client Computer System Implementation Onboard United States Navy Ships

DTIC Science & Technology

2007-06-01

management issues he encountered ruled out the Expanion as a viable option for thin-client computing in the Navy. An improvement in thin-client...44 Requirements to capabilities (2004). Retrieved April 29, 2007, from Vision Presence Power: A Program Guide to the U.S. Navy – 2004...Retrieved April 29, 2007, from Vision Presence Power: A Program Guide to the U.S. Navy – 2004 Edition, p. 128. Web site: http://www.chinfo.navy.mil

A PIC microcontroller-based system for real-life interfacing of external peripherals with a mobile robot

NASA Astrophysics Data System (ADS)

Singh, N. Nirmal; Chatterjee, Amitava; Rakshit, Anjan

2010-02-01

The present article describes the development of a peripheral interface controller (PIC) microcontroller-based system for interfacing external add-on peripherals with a real mobile robot, for real life applications. This system serves as an important building block of a complete integrated vision-based mobile robot system, integrated indigenously in our laboratory. The system is composed of the KOALA mobile robot in conjunction with a personal computer (PC) and a two-camera-based vision system where the PIC microcontroller is used to drive servo motors, in interrupt-driven mode, to control additional degrees of freedom of the vision system. The performance of the developed system is tested by checking it under the control of several user-specified commands, issued from the PC end.

Gesture therapy: a vision-based system for upper extremity stroke rehabilitation.

PubMed

Sucar, L; Luis, Roger; Leder, Ron; Hernandez, Jorge; Sanchez, Israel

2010-01-01

Stroke is the main cause of motor and cognitive disabilities requiring therapy in the world. Therefor it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. We have developed a low-cost vision-based system that allows stroke survivors to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a virtual environment for facilitating repetitive movement training, with computer vision algorithms that track the hand of a patient, using an inexpensive camera and a personal computer. This system, called Gesture Therapy, includes a gripper with a pressure sensor to include hand and finger rehabilitation; and it tracks the head of the patient to detect and avoid trunk compensation. It has been evaluated in a controlled clinical trial at the National Institute for Neurology and Neurosurgery in Mexico City, comparing it with conventional occupational therapy. In this paper we describe the latest version of the Gesture Therapy System and summarize the results of the clinical trail.

Remote-controlled vision-guided mobile robot system

NASA Astrophysics Data System (ADS)

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

1997-09-01

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

IPLIB (Image processing library) user's manual

NASA Technical Reports Server (NTRS)

Faulcon, N. D.; Monteith, J. H.; Miller, K.

1985-01-01

IPLIB is a collection of HP FORTRAN 77 subroutines and functions that facilitate the use of a COMTAL image processing system driven by an HP-1000 computer. It is intended for programmers who want to use the HP 1000 to drive the COMTAL Vision One/20 system. It is assumed that the programmer knows HP 1000 FORTRAN 77 or at least one FORTRAN dialect. It is also assumed that the programmer has some familiarity with the COMTAL Vision One/20 system.

Computer vision applications for coronagraphic optical alignment and image processing.

PubMed

Savransky, Dmitry; Thomas, Sandrine J; Poyneer, Lisa A; Macintosh, Bruce A

2013-05-10

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

Near real-time, on-the-move software PED using VPEF

NASA Astrophysics Data System (ADS)

Green, Kevin; Geyer, Chris; Burnette, Chris; Agarwal, Sanjeev; Swett, Bruce; Phan, Chung; Deterline, Diane

2015-05-01

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

Precision of computer-assisted core decompression drilling of the knee.

PubMed

Beckmann, J; Goetz, J; Bäthis, H; Kalteis, T; Grifka, J; Perlick, L

2006-06-01

Core decompression by exact drilling into the ischemic areas is the treatment of choice in early stages of osteonecrosis of the femoral condyle. Computer-aided surgery might enhance the precision of the drilling and lower the radiation exposure time of both staff and patients. The aim of this study was to evaluate the precision of the fluoroscopically based VectorVision-navigation system in an in vitro model. Thirty sawbones were prepared with a defect filled up with a radiopaque gypsum sphere mimicking the osteonecrosis. 20 sawbones were drilled by guidance of an intraoperative navigation system VectorVision (BrainLAB, Munich, Germany). Ten sawbones were drilled by fluoroscopic control only. A statistically significant difference with a mean distance of 0.58 mm in the navigated group and 0.98 mm in the control group regarding the distance to the desired mid-point of the lesion could be stated. Significant difference was further found in the number of drilling corrections as well as radiation time needed. The fluoroscopic-based VectorVision-navigation system shows a high feasibility and precision of computer-guided drilling with simultaneously reduction of radiation time and therefore could be integrated into clinical routine.

3D visual mechinism by neural networkings

NASA Astrophysics Data System (ADS)

Sugiyama, Shigeki

2007-04-01

There are some computer vision systems that are available on a market but those are quite far from a real usage of our daily life in a sense of security guard or in a sense of a usage of recognition of a target object behaviour. Because those surroundings' sensing might need to recognize a detail description of an object, like "the distance to an object" and "an object detail figure" and "its figure of edging", which are not possible to have a clear picture of the mechanisms of them with the present recognition system. So for doing this, here studies on mechanisms of how a pair of human eyes can recognize a distance apart, an object edging, and an object in order to get basic essences of vision mechanisms. And those basic mechanisms of object recognition are simplified and are extended logically for applying to a computer vision system. Some of the results of these studies are introduced on this paper.

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

NASA Technical Reports Server (NTRS)

Brockers, Roland; Ma, Jeremy C.; Matthies, Larry H.; Bouffard, Patrick

2012-01-01

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

Magician Simulator: A Realistic Simulator for Heterogenous Teams of Autonomous Robots. MAGIC 2010 Challenge

DTIC Science & Technology

2011-02-07

Sensor UGVs (SUGV) or Disruptor UGVs, depending on their payload. The SUGVs included vision, GPS/IMU, and LIDAR systems for identifying and tracking...employed by all the MAGICian research groups. Objects of interest were tracked using standard LIDAR and Computer Vision template-based feature...tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous Locali- zation and Mapping ( SLAM ). Our system contains

Machine vision methods for use in grain variety discrimination and quality analysis

NASA Astrophysics Data System (ADS)

Winter, Philip W.; Sokhansanj, Shahab; Wood, Hugh C.

1996-12-01

Decreasing cost of computer technology has made it feasible to incorporate machine vision technology into the agriculture industry. The biggest attraction to using a machine vision system is the computer's ability to be completely consistent and objective. One use is in the variety discrimination and quality inspection of grains. Algorithms have been developed using Fourier descriptors and neural networks for use in variety discrimination of barley seeds. RGB and morphology features have been used in the quality analysis of lentils, and probability distribution functions and L,a,b color values for borage dockage testing. These methods have been shown to be very accurate and have a high potential for agriculture. This paper presents the techniques used and results obtained from projects including: a lentil quality discriminator, a barley variety classifier, a borage dockage tester, a popcorn quality analyzer, and a pistachio nut grading system.

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

PubMed Central

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms. PMID:22164069

FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

PubMed

Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

Evaluation of the Waggoner Computerized Color Vision Test.

PubMed

Ng, Jason S; Self, Eriko; Vanston, John E; Nguyen, Andrew L; Crognale, Michael A

2015-04-01

Clinical color vision evaluation has been based primarily on the same set of tests for the past several decades. Recently, computer-based color vision tests have been devised, and these have several advantages but are still not widely used. In this study, we evaluated the Waggoner Computerized Color Vision Test (CCVT), which was developed for widespread use with common computer systems. A sample of subjects with (n = 59) and without (n = 361) color vision deficiency (CVD) were tested on the CCVT, the anomaloscope, the Richmond HRR (Hardy-Rand-Rittler) (4th edition), and the Ishihara test. The CCVT was administered in two ways: (1) on a computer monitor using its default settings and (2) on one standardized to a correlated color temperature (CCT) of 6500 K. Twenty-four subjects with CVD performed the CCVT both ways. Sensitivity, specificity, and correct classification rates were determined. The screening performance of the CCVT was good (95% sensitivity, 100% specificity). The CCVT classified subjects as deutan or protan in agreement with anomaloscopy 89% of the time. It generally classified subjects as having a more severe defect compared with other tests. Results from 18 of the 24 subjects with CVD tested under both default and calibrated CCT conditions were the same, whereas the results from 6 subjects had better agreement with other test results when the CCT was set. The Waggoner CCVT is an adequate color vision screening test with several advantages and appears to provide a fairly accurate diagnosis of deficiency type. Used in conjunction with other color vision tests, it may be a useful addition to a color vision test battery.

On the performances of computer vision algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Battiato, S.; Farinella, G. M.; Messina, E.; Puglisi, G.; Ravì, D.; Capra, A.; Tomaselli, V.

2012-01-01

Computer Vision enables mobile devices to extract the meaning of the observed scene from the information acquired with the onboard sensor cameras. Nowadays, there is a growing interest in Computer Vision algorithms able to work on mobile platform (e.g., phone camera, point-and-shot-camera, etc.). Indeed, bringing Computer Vision capabilities on mobile devices open new opportunities in different application contexts. The implementation of vision algorithms on mobile devices is still a challenging task since these devices have poor image sensors and optics as well as limited processing power. In this paper we have considered different algorithms covering classic Computer Vision tasks: keypoint extraction, face detection, image segmentation. Several tests have been done to compare the performances of the involved mobile platforms: Nokia N900, LG Optimus One, Samsung Galaxy SII.

The Print and Computer Enlargement System--PACE. Final Report.

ERIC Educational Resources Information Center

Morford, Ronald A.

The Print and Computer Enlargement (PACE) System is being designed as a portable computerized reading and writing system that enables a low-vision person to read regular print and then create and edit text using large-print computerized output. The design goal was to develop a system that: weighed no more than 12 pounds so it could be easily…

Real-time machine vision system using FPGA and soft-core processor

NASA Astrophysics Data System (ADS)

Malik, Abdul Waheed; Thörnberg, Benny; Meng, Xiaozhou; Imran, Muhammad

2012-06-01

This paper presents a machine vision system for real-time computation of distance and angle of a camera from reference points in the environment. Image pre-processing, component labeling and feature extraction modules were modeled at Register Transfer (RT) level and synthesized for implementation on field programmable gate arrays (FPGA). The extracted image component features were sent from the hardware modules to a soft-core processor, MicroBlaze, for computation of distance and angle. A CMOS imaging sensor operating at a clock frequency of 27MHz was used in our experiments to produce a video stream at the rate of 75 frames per second. Image component labeling and feature extraction modules were running in parallel having a total latency of 13ms. The MicroBlaze was interfaced with the component labeling and feature extraction modules through Fast Simplex Link (FSL). The latency for computing distance and angle of camera from the reference points was measured to be 2ms on the MicroBlaze, running at 100 MHz clock frequency. In this paper, we present the performance analysis, device utilization and power consumption for the designed system. The FPGA based machine vision system that we propose has high frame speed, low latency and a power consumption that is much lower compared to commercially available smart camera solutions.

Semiautonomous teleoperation system with vision guidance

NASA Astrophysics Data System (ADS)

Yu, Wai; Pretlove, John R. G.

1998-12-01

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

Object and Facial Recognition in Augmented and Virtual Reality: Investigation into Software, Hardware and Potential Uses

NASA Technical Reports Server (NTRS)

Schulte, Erin

2017-01-01

As augmented and virtual reality grows in popularity, and more researchers focus on its development, other fields of technology have grown in the hopes of integrating with the up-and-coming hardware currently on the market. Namely, there has been a focus on how to make an intuitive, hands-free human-computer interaction (HCI) utilizing AR and VR that allows users to control their technology with little to no physical interaction with hardware. Computer vision, which is utilized in devices such as the Microsoft Kinect, webcams and other similar hardware has shown potential in assisting with the development of a HCI system that requires next to no human interaction with computing hardware and software. Object and facial recognition are two subsets of computer vision, both of which can be applied to HCI systems in the fields of medicine, security, industrial development and other similar areas.

An assembly system based on industrial robot with binocular stereo vision

NASA Astrophysics Data System (ADS)

Tang, Hong; Xiao, Nanfeng

2017-01-01

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

The Pixhawk Open-Source Computer Vision Framework for Mavs

NASA Astrophysics Data System (ADS)

Meier, L.; Tanskanen, P.; Fraundorfer, F.; Pollefeys, M.

2011-09-01

Unmanned aerial vehicles (UAV) and micro air vehicles (MAV) are already intensively used in geodetic applications. State of the art autonomous systems are however geared towards the application area in safe and obstacle-free altitudes greater than 30 meters. Applications at lower altitudes still require a human pilot. A new application field will be the reconstruction of structures and buildings, including the facades and roofs, with semi-autonomous MAVs. Ongoing research in the MAV robotics field is focusing on enabling this system class to operate at lower altitudes in proximity to nearby obstacles and humans. PIXHAWK is an open source and open hardware toolkit for this purpose. The quadrotor design is optimized for onboard computer vision and can connect up to four cameras to its onboard computer. The validity of the system design is shown with a fully autonomous capture flight along a building.

Computer vision system for egg volume prediction using backpropagation neural network

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Data-driven indexing mechanism for the recognition of polyhedral objects

NASA Astrophysics Data System (ADS)

McLean, Stewart; Horan, Peter; Caelli, Terry M.

1992-02-01

This paper is concerned with the problem of searching large model databases. To date, most object recognition systems have concentrated on the problem of matching using simple searching algorithms. This is quite acceptable when the number of object models is small. However, in the future, general purpose computer vision systems will be required to recognize hundreds or perhaps thousands of objects and, in such circumstances, efficient searching algorithms will be needed. The problem of searching a large model database is one which must be addressed if future computer vision systems are to be at all effective. In this paper we present a method we call data-driven feature-indexed hypothesis generation as one solution to the problem of searching large model databases.

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

PubMed Central

Xu, Xin; Tang, Jinshan; Zhang, Xiaolong; Liu, Xiaoming; Zhang, Hong; Qiu, Yimin

2013-01-01

With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activities, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation of the performance of human activity recognition. PMID:23353144

Virtual Vision

NASA Astrophysics Data System (ADS)

Terzopoulos, Demetri; Qureshi, Faisal Z.

Computer vision and sensor networks researchers are increasingly motivated to investigate complex multi-camera sensing and control issues that arise in the automatic visual surveillance of extensive, highly populated public spaces such as airports and train stations. However, they often encounter serious impediments to deploying and experimenting with large-scale physical camera networks in such real-world environments. We propose an alternative approach called "Virtual Vision", which facilitates this type of research through the virtual reality simulation of populated urban spaces, camera sensor networks, and computer vision on commodity computers. We demonstrate the usefulness of our approach by developing two highly automated surveillance systems comprising passive and active pan/tilt/zoom cameras that are deployed in a virtual train station environment populated by autonomous, lifelike virtual pedestrians. The easily reconfigurable virtual cameras distributed in this environment generate synthetic video feeds that emulate those acquired by real surveillance cameras monitoring public spaces. The novel multi-camera control strategies that we describe enable the cameras to collaborate in persistently observing pedestrians of interest and in acquiring close-up videos of pedestrians in designated areas.

Electronic health records (EHRs): supporting ASCO's vision of cancer care.

PubMed

Yu, Peter; Artz, David; Warner, Jeremy

2014-01-01

ASCO's vision for cancer care in 2030 is built on the expanding importance of panomics and big data, and envisions enabling better health for patients with cancer by the rapid transformation of systems biology knowledge into cancer care advances. This vision will be heavily dependent on the use of health information technology for computational biology and clinical decision support systems (CDSS). Computational biology will allow us to construct models of cancer biology that encompass the complexity of cancer panomics data and provide us with better understanding of the mechanisms governing cancer behavior. The Agency for Healthcare Research and Quality promotes CDSS based on clinical practice guidelines, which are knowledge bases that grow too slowly to match the rate of panomic-derived knowledge. CDSS that are based on systems biology models will be more easily adaptable to rapid advancements and translational medicine. We describe the characteristics of health data representation, a model for representing molecular data that supports data extraction and use for panomic-based clinical research, and argue for CDSS that are based on systems biology and are algorithm-based.

Active vision and image/video understanding with decision structures based on the network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2003-08-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

Vision 20/20: Automation and advanced computing in clinical radiation oncology.

PubMed

Moore, Kevin L; Kagadis, George C; McNutt, Todd R; Moiseenko, Vitali; Mutic, Sasa

2014-01-01

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

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

PubMed

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

2017-06-01

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. 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 [Formula: see text] 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. The classification accuracy in the offline tests reached [Formula: see text] for the seen and [Formula: see text] 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 [Formula: see text] 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 Ultra TM prosthetic hand and a motion control TM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to [Formula: see text]. 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. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

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

NASA Astrophysics Data System (ADS)

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 conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Help for the Visually Impaired

NASA Technical Reports Server (NTRS)

1995-01-01

The Low Vision Enhancement System (LVES) is a video headset that offers people with low vision a view of their surroundings equivalent to the image on a five-foot television screen four feet from the viewer. It will not make the blind see but for many people with low vision, it eases everyday activities such as reading, watching TV and shopping. LVES was developed over almost a decade of cooperation between Stennis Space Center, the Wilmer Eye Institute of the Johns Hopkins Medical Institutions, the Department of Veteran Affairs, and Visionics Corporation. With the aid of Stennis scientists, Wilmer researchers used NASA technology for computer processing of satellite images and head-mounted vision enhancement systems originally intended for the space station. The unit consists of a head-mounted video display, three video cameras, and a control unit for the cameras. The cameras feed images to the video display in the headset.

Computing motion using resistive networks

NASA Technical Reports Server (NTRS)

Koch, Christof; Luo, Jin; Mead, Carver; Hutchinson, James

1988-01-01

Recent developments in the theory of early vision are described which lead from the formulation of the motion problem as an ill-posed one to its solution by minimizing certain 'cost' functions. These cost or energy functions can be mapped onto simple analog and digital resistive networks. It is shown how the optical flow can be computed by injecting currents into resistive networks and recording the resulting stationary voltage distribution at each node. These networks can be implemented in cMOS VLSI circuits and represent plausible candidates for biological vision systems.

Keeping Student Performance Central: The New York Assessment Collection. Studies on Exhibitions.

ERIC Educational Resources Information Center

Allen, David; McDonald, Joseph

This report describes a computer tool used by the state of New York to assess student performance in elementary and secondary grades. Based on the premise that every assessment is a system of interacting elements, the tool examines students on six dimensions: vision, prompt, coaching context, performance, standards, and reflection. Vision, which…

Computer vision in the poultry industry

USDA-ARS?s Scientific Manuscript database

Computer vision is becoming increasingly important in the poultry industry due to increasing use and speed of automation in processing operations. Growing awareness of food safety concerns has helped add food safety inspection to the list of tasks that automated computer vision can assist. Researc...

A Computer-Based System Integrating Instruction and Information Retrieval: A Description of Some Methodological Considerations.

ERIC Educational Resources Information Center

Selig, Judith A.; And Others

This report, summarizing the activities of the Vision Information Center (VIC) in the field of computer-assisted instruction from December, 1966 to August, 1967, describes the methodology used to load a large body of information--a programed text on basic opthalmology--onto a computer for subsequent information retrieval and computer-assisted…

Comparison of diagnosis of early retinal lesions of diabetic retinopathy between a computer system and human experts.

PubMed

Lee, S C; Lee, E T; Kingsley, R M; Wang, Y; Russell, D; Klein, R; Warn, A

2001-04-01

To investigate whether a computer vision system is comparable with humans in detecting early retinal lesions of diabetic retinopathy using color fundus photographs. A computer system has been developed using image processing and pattern recognition techniques to detect early lesions of diabetic retinopathy (hemorrhages and microaneurysms, hard exudates, and cotton-wool spots). Color fundus photographs obtained from American Indians in Oklahoma were used in developing and testing the system. A set of 369 color fundus slides were used to train the computer system using 3 diagnostic categories: lesions present, questionable, or absent (Y/Q/N). A different set of 428 slides were used to test and evaluate the system, and its diagnostic results were compared with those of 2 human experts-the grader at the University of Wisconsin Fundus Photograph Reading Center (Madison) and a general ophthalmologist. The experiments included comparisons using 3 (Y/Q/N) and 2 diagnostic categories (Y/N) (questionable cases excluded in the latter). In the training phase, the agreement rates, sensitivity, and specificity in detecting the 3 lesions between the retinal specialist and the computer system were all above 90%. The kappa statistics were high (0.75-0.97), indicating excellent agreement between the specialist and the computer system. In the testing phase, the results obtained between the computer system and human experts were consistent with those of the training phase, and they were comparable with those between the human experts. The performance of the computer vision system in diagnosing early retinal lesions was comparable with that of human experts. Therefore, this mobile, electronically easily accessible, and noninvasive computer system, could become a mass screening tool and a clinical aid in diagnosing early lesions of diabetic retinopathy.

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

[Comparison study between biological vision and computer vision].

PubMed

Liu, W; Yuan, X G; Yang, C X; Liu, Z Q; Wang, R

2001-08-01

The development and bearing of biology vision in structure and mechanism were discussed, especially on the aspects including anatomical structure of biological vision, tentative classification of reception field, parallel processing of visual information, feedback and conformity effect of visual cortical, and so on. The new advance in the field was introduced through the study of the morphology of biological vision. Besides, comparison between biological vision and computer vision was made, and their similarities and differences were pointed out.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

NASA Technical Reports Server (NTRS)

Liu, Xuan; Furrer, David; Kosters, Jared; Holmes, Jack

2018-01-01

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

Fast and robust generation of feature maps for region-based visual attention.

PubMed

Aziz, Muhammad Zaheer; Mertsching, Bärbel

2008-05-01

Visual attention is one of the important phenomena in biological vision which can be followed to achieve more efficiency, intelligence, and robustness in artificial vision systems. This paper investigates a region-based approach that performs pixel clustering prior to the processes of attention in contrast to late clustering as done by contemporary methods. The foundation steps of feature map construction for the region-based attention model are proposed here. The color contrast map is generated based upon the extended findings from the color theory, the symmetry map is constructed using a novel scanning-based method, and a new algorithm is proposed to compute a size contrast map as a formal feature channel. Eccentricity and orientation are computed using the moments of obtained regions and then saliency is evaluated using the rarity criteria. The efficient design of the proposed algorithms allows incorporating five feature channels while maintaining a processing rate of multiple frames per second. Another salient advantage over the existing techniques is the reusability of the salient regions in the high-level machine vision procedures due to preservation of their shapes and precise locations. The results indicate that the proposed model has the potential to efficiently integrate the phenomenon of attention into the main stream of machine vision and systems with restricted computing resources such as mobile robots can benefit from its advantages.

Local spatio-temporal analysis in vision systems

NASA Astrophysics Data System (ADS)

Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

1994-07-01

The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

Vision-Based People Detection System for Heavy Machine Applications

PubMed Central

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-01

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. PMID:26805838

Vision-Based People Detection System for Heavy Machine Applications.

PubMed

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-20

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.

Testing and evaluation of a wearable augmented reality system for natural outdoor environments

NASA Astrophysics Data System (ADS)

Roberts, David; Menozzi, Alberico; Cook, James; Sherrill, Todd; Snarski, Stephen; Russler, Pat; Clipp, Brian; Karl, Robert; Wenger, Eric; Bennett, Matthew; Mauger, Jennifer; Church, William; Towles, Herman; MacCabe, Stephen; Webb, Jeffrey; Lupo, Jasper; Frahm, Jan-Michael; Dunn, Enrique; Leslie, Christopher; Welch, Greg

2013-05-01

This paper describes performance evaluation of a wearable augmented reality system for natural outdoor environments. Applied Research Associates (ARA), as prime integrator on the DARPA ULTRA-Vis (Urban Leader Tactical, Response, Awareness, and Visualization) program, is developing a soldier-worn system to provide intuitive `heads-up' visualization of tactically-relevant geo-registered icons. Our system combines a novel pose estimation capability, a helmet-mounted see-through display, and a wearable processing unit to accurately overlay geo-registered iconography (e.g., navigation waypoints, sensor points of interest, blue forces, aircraft) on the soldier's view of reality. We achieve accurate pose estimation through fusion of inertial, magnetic, GPS, terrain data, and computer-vision inputs. We leverage a helmet-mounted camera and custom computer vision algorithms to provide terrain-based measurements of absolute orientation (i.e., orientation of the helmet with respect to the earth). These orientation measurements, which leverage mountainous terrain horizon geometry and mission planning landmarks, enable our system to operate robustly in the presence of external and body-worn magnetic disturbances. Current field testing activities across a variety of mountainous environments indicate that we can achieve high icon geo-registration accuracy (<10mrad) using these vision-based methods.

Stereo Vision Inside Tire

DTIC Science & Technology

2015-08-21

using the Open Computer Vision ( OpenCV ) libraries [6] for computer vision and the Qt library [7] for the user interface. The software has the...depth. The software application calibrates the cameras using the plane based calibration model from the OpenCV calib3D module and allows the...6] OpenCV . 2015. OpenCV Open Source Computer Vision. [Online]. Available at: opencv.org [Accessed]: 09/01/2015. [7] Qt. 2015. Qt Project home

The software for automatic creation of the formal grammars used by speech recognition, computer vision, editable text conversion systems, and some new functions

NASA Astrophysics Data System (ADS)

Kardava, Irakli; Tadyszak, Krzysztof; Gulua, Nana; Jurga, Stefan

2017-02-01

For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.

Toward detection of marine vehicles on horizon from buoy camera

NASA Astrophysics Data System (ADS)

Fefilatyev, Sergiy; Goldgof, Dmitry B.; Langebrake, Lawrence

2007-10-01

This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

Chapter 11. Quality evaluation of apple by computer vision

USDA-ARS?s Scientific Manuscript database

Apple is one of the most consumed fruits in the world, and there is a critical need for enhanced computer vision technology for quality assessment of apples. This chapter gives a comprehensive review on recent advances in various computer vision techniques for detecting surface and internal defects ...

Deep Learning for Computer Vision: A Brief Review

PubMed Central

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Before They Can Speak, They Must Know.

ERIC Educational Resources Information Center

Cromie, William J.; Edson, Lee

1984-01-01

Intelligent relationships with people are among the goals for tomorrow's computers. Knowledge-based systems used and being developed to achieve these goals are discussed. Automatic learning, producing inferences, parallelism, program languages, friendly machines, computer vision, and biomodels are among the topics considered. (JN)

On the efficacy of cinema, or what the visual system did not evolve to do

NASA Technical Reports Server (NTRS)

Cutting, James E.

1989-01-01

Spatial displays, and a constraint that they do not place on the use of spatial instruments are discussed. Much of the work done in visual perception by psychologists and by computer scientists has concerned displays that show the motion of rigid objects. Typically, if one assumes that objects are rigid, one can then proceed to understand how the constant shape of the object can be perceived (or computed) as it moves through space. The author maintains that photographs and cinema are visual displays that are also powerful forms of art. Their efficacy, in part, stems from the fact that, although viewpoint is constrained when composing them, it is not nearly so constrained when viewing them. It is obvious, according to the author, that human visual systems did not evolve to watch movies or look at photographs. Thus, what photographs and movies present must be allowed in the rule-governed system under which vision evolved. Machine-vision algorithms, to be applicable to human vision, should show the same types of tolerance.

Computing Visible-Surface Representations,

DTIC Science & Technology

1985-03-01

Terzopoulos N00014-75-C-0643 9. PERFORMING ORGANIZATION NAME AMC ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK Artificial Inteligence Laboratory AREA A...Massachusetts Institute of lechnolog,. Support lbr the laboratory’s Artificial Intelligence research is provided in part by the Advanced Rtccarcl Proj...dynamically maintaining visible surface representations. Whether the intention is to model human vision or to design competent artificial vision systems

The Role of Prototype Learning in Hierarchical Models of Vision

ERIC Educational Resources Information Center

Thomure, Michael David

2014-01-01

I conduct a study of learning in HMAX-like models, which are hierarchical models of visual processing in biological vision systems. Such models compute a new representation for an image based on the similarity of image sub-parts to a number of specific patterns, called prototypes. Despite being a central piece of the overall model, the issue of…

New Visions of Reality: Multimedia and Education.

ERIC Educational Resources Information Center

Ambron, Sueann

1986-01-01

Multimedia is a powerful tool that will change both the way we look at knowledge and our vision of reality, as well as our educational system and the business world. Multimedia as used here refers to the innovation of mixing text, audio, and video through the use of a computer. Not only will there be new products emerging from multimedia uses, but…

Identifying the computational requirements of an integrated top-down-bottom-up model for overt visual attention within an active vision system.

PubMed

McBride, Sebastian; Huelse, Martin; Lee, Mark

2013-01-01

Computational visual attention systems have been constructed in order for robots and other devices to detect and locate regions of interest in their visual world. Such systems often attempt to take account of what is known of the human visual system and employ concepts, such as 'active vision', to gain various perceived advantages. However, despite the potential for gaining insights from such experiments, the computational requirements for visual attention processing are often not clearly presented from a biological perspective. This was the primary objective of this study, attained through two specific phases of investigation: 1) conceptual modeling of a top-down-bottom-up framework through critical analysis of the psychophysical and neurophysiological literature, 2) implementation and validation of the model into robotic hardware (as a representative of an active vision system). Seven computational requirements were identified: 1) transformation of retinotopic to egocentric mappings, 2) spatial memory for the purposes of medium-term inhibition of return, 3) synchronization of 'where' and 'what' information from the two visual streams, 4) convergence of top-down and bottom-up information to a centralized point of information processing, 5) a threshold function to elicit saccade action, 6) a function to represent task relevance as a ratio of excitation and inhibition, and 7) derivation of excitation and inhibition values from object-associated feature classes. The model provides further insight into the nature of data representation and transfer between brain regions associated with the vertebrate 'active' visual attention system. In particular, the model lends strong support to the functional role of the lateral intraparietal region of the brain as a primary area of information consolidation that directs putative action through the use of a 'priority map'.

Synthetic Vision Displays for Planetary and Lunar Lander Vehicles

NASA Technical Reports Server (NTRS)

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

2008-01-01

Aviation research has demonstrated that Synthetic Vision (SV) technology can substantially enhance situation awareness, reduce pilot workload, improve aviation safety, and promote flight path control precision. SV, and related flight deck technologies are currently being extended for application in planetary exploration vehicles. SV, in particular, holds significant potential for many planetary missions since the SV presentation provides a computer-generated view for the flight crew of the terrain and other significant environmental characteristics independent of the outside visibility conditions, window locations, or vehicle attributes. SV allows unconstrained control of the computer-generated scene lighting, terrain coloring, and virtual camera angles which may provide invaluable visual cues to pilots/astronauts, not available from other vision technologies. In addition, important vehicle state information may be conformally displayed on the view such as forward and down velocities, altitude, and fuel remaining to enhance trajectory control and vehicle system status. The paper accompanies a conference demonstration that introduced a prototype NASA Synthetic Vision system for lunar lander spacecraft. The paper will describe technical challenges and potential solutions to SV applications for the lunar landing mission, including the requirements for high-resolution lunar terrain maps, accurate positioning and orientation, and lunar cockpit display concepts to support projected mission challenges.

Vision 20/20: Automation and advanced computing in clinical radiation oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Kevin L., E-mail: kevinmoore@ucsd.edu; Moiseenko, Vitali; Kagadis, George C.

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authorsmore » contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.« less

Vision 20/20: Automation and advanced computing in clinical radiation oncology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Kevin L., E-mail: kevinmoore@ucsd.edu; Moiseenko, Vitali; Kagadis, George C.

2014-01-15

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authorsmore » contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.« less

A computer vision for animal ecology.

PubMed

Weinstein, Ben G

2018-05-01

A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis. © 2017 The Author. Journal of Animal Ecology © 2017 British Ecological Society.

Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications

NASA Astrophysics Data System (ADS)

Fang, Wai-Chi; Udomkesmalee, Gabriel; Alkalai, Leon

1997-04-01

A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological vision systems. This electronic eye- brain computer is targeted for real-time machine vision applications which require both high-bandwidth communication and high-performance computing for data sensing, synergy of multiple types of sensory information, feature extraction, target detection, target recognition, and control functions. The neural computer is based on a composite structure which combines Annealing Cellular Neural Network (ACNN) and Hierarchical Self-Organization Neural Network (HSONN). The ACNN architecture is a programmable and scalable multi- dimensional array of annealing neurons which are locally connected with their local neurons. Meanwhile, the HSONN adopts a hierarchical structure with nonlinear basis functions. The ACNN+HSONN neural computer is effectively designed to perform programmable functions for machine vision processing in all levels with its embedded host processor. It provides a two order-of-magnitude increase in computation power over the state-of-the-art microcomputer and DSP microelectronics. A compact current-mode VLSI design feasibility of the ACNN+HSONN neural computer is demonstrated by a 3D 16X8X9-cube neural processor chip design in a 2-micrometers CMOS technology. Integration of this neural computer as one slice of a 4'X4' multichip module into the 3D MCM based avionics architecture for NASA's New Millennium Program is also described.

Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.

NASA Astrophysics Data System (ADS)

Battiti, Roberto

1990-01-01

This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from multiple-purpose modules. In the last part of the thesis a well known optimization method (the Broyden-Fletcher-Goldfarb-Shanno memoryless quasi -Newton method) is applied to simple classification problems and shown to be superior to the "error back-propagation" algorithm for numerical stability, automatic selection of parameters, and convergence properties.

Improved stereo matching applied to digitization of greenhouse plants

NASA Astrophysics Data System (ADS)

Zhang, Peng; Xu, Lihong; Li, Dawei; Gu, Xiaomeng

2015-03-01

The digitization of greenhouse plants is an important aspect of digital agriculture. Its ultimate aim is to reconstruct a visible and interoperable virtual plant model on the computer by using state-of-the-art image process and computer graphics technologies. The most prominent difficulties of the digitization of greenhouse plants include how to acquire the three-dimensional shape data of greenhouse plants and how to carry out its realistic stereo reconstruction. Concerning these issues an effective method for the digitization of greenhouse plants is proposed by using a binocular stereo vision system in this paper. Stereo vision is a technique aiming at inferring depth information from two or more cameras; it consists of four parts: calibration of the cameras, stereo rectification, search of stereo correspondence and triangulation. Through the final triangulation procedure, the 3D point cloud of the plant can be achieved. The proposed stereo vision system can facilitate further segmentation of plant organs such as stems and leaves; moreover, it can provide reliable digital samples for the visualization of greenhouse tomato plants.

Landmark navigation and autonomous landing approach with obstacle detection for aircraft

NASA Astrophysics Data System (ADS)

Fuerst, Simon; Werner, Stefan; Dickmanns, Dirk; Dickmanns, Ernst D.

1997-06-01

A machine perception system for aircraft and helicopters using multiple sensor data for state estimation is presented. By combining conventional aircraft sensor like gyros, accelerometers, artificial horizon, aerodynamic measuring devices and GPS with vision data taken by conventional CCD-cameras mounted on a pan and tilt platform, the position of the craft can be determined as well as the relative position to runways and natural landmarks. The vision data of natural landmarks are used to improve position estimates during autonomous missions. A built-in landmark management module decides which landmark should be focused on by the vision system, depending on the distance to the landmark and the aspect conditions. More complex landmarks like runways are modeled with different levels of detail that are activated dependent on range. A supervisor process compares vision data and GPS data to detect mistracking of the vision system e.g. due to poor visibility and tries to reinitialize the vision system or to set focus on another landmark available. During landing approach obstacles like trucks and airplanes can be detected on the runway. The system has been tested in real-time within a hardware-in-the-loop simulation. Simulated aircraft measurements corrupted by noise and other characteristic sensor errors have been fed into the machine perception system; the image processing module for relative state estimation was driven by computer generated imagery. Results from real-time simulation runs are given.

Computer-based System for the Virtual-Endoscopic Guidance of Bronchoscopy.

PubMed

Helferty, J P; Sherbondy, A J; Kiraly, A P; Higgins, W E

2007-11-01

The standard procedure for diagnosing lung cancer involves two stages: three-dimensional (3D) computed-tomography (CT) image assessment, followed by interventional bronchoscopy. In general, the physician has no link between the 3D CT image assessment results and the follow-on bronchoscopy. Thus, the physician essentially performs bronchoscopic biopsy of suspect cancer sites blindly. We have devised a computer-based system that greatly augments the physician's vision during bronchoscopy. The system uses techniques from computer graphics and computer vision to enable detailed 3D CT procedure planning and follow-on image-guided bronchoscopy. The procedure plan is directly linked to the bronchoscope procedure, through a live registration and fusion of the 3D CT data and bronchoscopic video. During a procedure, the system provides many visual tools, fused CT-video data, and quantitative distance measures; this gives the physician considerable visual feedback on how to maneuver the bronchoscope and where to insert the biopsy needle. Central to the system is a CT-video registration technique, based on normalized mutual information. Several sets of results verify the efficacy of the registration technique. In addition, we present a series of test results for the complete system for phantoms, animals, and human lung-cancer patients. The results indicate that not only is the variation in skill level between different physicians greatly reduced by the system over the standard procedure, but that biopsy effectiveness increases.

Comparison of tests of accommodation for computer users.

PubMed

Kolker, David; Hutchinson, Robert; Nilsen, Erik

2002-04-01

With the increased use of computers in the workplace and at home, optometrists are finding more patients presenting with symptoms of Computer Vision Syndrome. Among these symptomatic individuals, research supports that accommodative disorders are the most common vision finding. A prepresbyopic group (N= 30) and a presbyopic group (N = 30) were selected from a private practice. Assignment to a group was determined by age, accommodative amplitude, and near visual acuity with their distance prescription. Each subject was given a thorough vision and ocular health examination, then administered several nearpoint tests of accommodation at a computer working distance. All the tests produced similar results in the presbyopic group. For the prepresbyopic group, the tests yielded very different results. To effectively treat symptomatic VDT users, optometrists must assess the accommodative system along with the binocular and refractive status. For presbyopic patients, all nearpoint tests studied will yield virtually the same result. However, the method of testing accommodation, as well as the test stimulus presented, will yield significantly different responses for prepresbyopic patients. Previous research indicates that a majority of patients prefer the higher plus prescription yielded by the Gaussian image test.

Harnessing vision for computation.

PubMed

Changizi, Mark

2008-01-01

Might it be possible to harness the visual system to carry out artificial computations, somewhat akin to how DNA has been harnessed to carry out computation? I provide the beginnings of a research programme attempting to do this. In particular, new techniques are described for building 'visual circuits' (or 'visual software') using wire, NOT, OR, and AND gates in a visual 6modality such that our visual system acts as 'visual hardware' computing the circuit, and generating a resultant perception which is the output.

Intelligent vision system for autonomous vehicle operations

NASA Technical Reports Server (NTRS)

Scholl, Marija S.

1991-01-01

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

Vision-Aided RAIM: A New Method for GPS Integrity Monitoring in Approach and Landing Phase

PubMed Central

Fu, Li; Zhang, Jun; Li, Rui; Cao, Xianbin; Wang, Jinling

2015-01-01

In the 1980s, Global Positioning System (GPS) receiver autonomous integrity monitoring (RAIM) was proposed to provide the integrity of a navigation system by checking the consistency of GPS measurements. However, during the approach and landing phase of a flight path, where there is often low GPS visibility conditions, the performance of the existing RAIM method may not meet the stringent aviation requirements for availability and integrity due to insufficient observations. To solve this problem, a new RAIM method, named vision-aided RAIM (VA-RAIM), is proposed for GPS integrity monitoring in the approach and landing phase. By introducing landmarks as pseudo-satellites, the VA-RAIM enriches the navigation observations to improve the performance of RAIM. In the method, a computer vision system photographs and matches these landmarks to obtain additional measurements for navigation. Nevertheless, the challenging issue is that such additional measurements may suffer from vision errors. To ensure the reliability of the vision measurements, a GPS-based calibration algorithm is presented to reduce the time-invariant part of the vision errors. Then, the calibrated vision measurements are integrated with the GPS observations for integrity monitoring. Simulation results show that the VA-RAIM outperforms the conventional RAIM with a higher level of availability and fault detection rate. PMID:26378533

Vision-Aided RAIM: A New Method for GPS Integrity Monitoring in Approach and Landing Phase.

PubMed

Fu, Li; Zhang, Jun; Li, Rui; Cao, Xianbin; Wang, Jinling

2015-09-10

In the 1980s, Global Positioning System (GPS) receiver autonomous integrity monitoring (RAIM) was proposed to provide the integrity of a navigation system by checking the consistency of GPS measurements. However, during the approach and landing phase of a flight path, where there is often low GPS visibility conditions, the performance of the existing RAIM method may not meet the stringent aviation requirements for availability and integrity due to insufficient observations. To solve this problem, a new RAIM method, named vision-aided RAIM (VA-RAIM), is proposed for GPS integrity monitoring in the approach and landing phase. By introducing landmarks as pseudo-satellites, the VA-RAIM enriches the navigation observations to improve the performance of RAIM. In the method, a computer vision system photographs and matches these landmarks to obtain additional measurements for navigation. Nevertheless, the challenging issue is that such additional measurements may suffer from vision errors. To ensure the reliability of the vision measurements, a GPS-based calibration algorithm is presented to reduce the time-invariant part of the vision errors. Then, the calibrated vision measurements are integrated with the GPS observations for integrity monitoring. Simulation results show that the VA-RAIM outperforms the conventional RAIM with a higher level of availability and fault detection rate.

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

PubMed Central

Indiveri, Giacomo

2008-01-01

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention. PMID:27873818

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

PubMed

Indiveri, Giacomo

2008-09-03

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

Computer interfaces for the visually impaired

NASA Technical Reports Server (NTRS)

Higgins, Gerry

1991-01-01

Information access via computer terminals extends to blind and low vision persons employed in many technical and nontechnical disciplines. Two aspects are detailed of providing computer technology for persons with a vision related handicap. First, research into the most effective means of integrating existing adaptive technologies into information systems was made. This was conducted to integrate off the shelf products with adaptive equipment for cohesive integrated information processing systems. Details are included that describe the type of functionality required in software to facilitate its incorporation into a speech and/or braille system. The second aspect is research into providing audible and tactile interfaces to graphics based interfaces. Parameters are included for the design and development of the Mercator Project. The project will develop a prototype system for audible access to graphics based interfaces. The system is being built within the public domain architecture of X windows to show that it is possible to provide access to text based applications within a graphical environment. This information will be valuable to suppliers to ADP equipment since new legislation requires manufacturers to provide electronic access to the visually impaired.

Computer vision-based sorting of Atlantic salmon (Salmo salar) fillets according to their color level.

PubMed

Misimi, E; Mathiassen, J R; Erikson, U

2007-01-01

Computer vision method was used to evaluate the color of Atlantic salmon (Salmo salar) fillets. Computer vision-based sorting of fillets according to their color was studied on 2 separate groups of salmon fillets. The images of fillets were captured using a digital camera of high resolution. Images of salmon fillets were then segmented in the regions of interest and analyzed in red, green, and blue (RGB) and CIE Lightness, redness, and yellowness (Lab) color spaces, and classified according to the Roche color card industrial standard. Comparisons of fillet color between visual evaluations were made by a panel of human inspectors, according to the Roche SalmoFan lineal standard, and the color scores generated from computer vision algorithm showed that there were no significant differences between the methods. Overall, computer vision can be used as a powerful tool to sort fillets by color in a fast and nondestructive manner. The low cost of implementing computer vision solutions creates the potential to replace manual labor in fish processing plants with automation.

Quality Control by Artificial Vision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, Edmond Y.; Gleason, Shaun Scott; Niel, Kurt S.

2010-01-01

Computational technology has fundamentally changed many aspects of our lives. One clear evidence is the development of artificial-vision systems, which have effectively automated many manual tasks ranging from quality inspection to quantitative assessment. In many cases, these machine-vision systems are even preferred over manual ones due to their repeatability and high precision. Such advantages come from significant research efforts in advancing sensor technology, illumination, computational hardware, and image-processing algorithms. Similar to the Special Section on Quality Control by Artificial Vision published two years ago in Volume 17, Issue 3 of the Journal of Electronic Imaging, the present one invited papersmore » relevant to fundamental technology improvements to foster quality control by artificial vision, and fine-tuned the technology for specific applications. We aim to balance both theoretical and applied work pertinent to this special section theme. Consequently, we have seven high-quality papers resulting from the stringent peer-reviewing process in place at the Journal of Electronic Imaging. Some of the papers contain extended treatment of the authors work presented at the SPIE Image Processing: Machine Vision Applications conference and the International Conference on Quality Control by Artificial Vision. On the broad application side, Liu et al. propose an unsupervised texture image segmentation scheme. Using a multilayer data condensation spectral clustering algorithm together with wavelet transform, they demonstrate the effectiveness of their approach on both texture and synthetic aperture radar images. A problem related to image segmentation is image extraction. For this, O'Leary et al. investigate the theory of polynomial moments and show how these moments can be compared to classical filters. They also show how to use the discrete polynomial-basis functions for the extraction of 3-D embossed digits, demonstrating superiority over Fourier-basis functions for this task. Image registration is another important task for machine vision. Bingham and Arrowood investigate the implementation and results in applying Fourier phase matching for projection registration, with a particular focus on nondestructive testing using computed tomography. Readers interested in enriching their arsenal of image-processing algorithms for machine-vision tasks should find these papers enriching. Meanwhile, we have four papers dealing with more specific machine-vision tasks. The first one, Yahiaoui et al., is quantitative in nature, using machine vision for real-time passenger counting. Occulsion is a common problem in counting objects and people, and they circumvent this issue with a dense stereovision system, achieving 97 to 99% accuracy in their tests. On the other hand, the second paper by Oswald-Tranta et al. focuses on thermographic crack detection. An infrared camera is used to detect inhomogeneities, which may indicate surface cracks. They describe the various steps in developing fully automated testing equipment aimed at a high throughput. Another paper describing an inspection system is Molleda et al., which handles flatness inspection of rolled products. They employ optical-laser triangulation and 3-D surface reconstruction for this task, showing how these can be achieved in real time. Last but not least, Presles et al. propose a way to monitor the particle-size distribution of batch crystallization processes. This is achieved through a new in situ imaging probe and image-analysis methods. While it is unlikely any reader may be working on these four specific problems at the same time, we are confident that readers will find these papers inspiring and potentially helpful to their own machine-vision system developments.« less

The loss and recovery of vertebrate vision examined in microplates.

PubMed

Thorn, Robert J; Clift, Danielle E; Ojo, Oladele; Colwill, Ruth M; Creton, Robbert

2017-01-01

Regenerative medicine offers potentially ground-breaking treatments of blindness and low vision. However, as new methodologies are developed, a critical question will need to be addressed: how do we monitor in vivo for functional success? In the present study, we developed novel behavioral assays to examine vision in a vertebrate model system. In the assays, zebrafish larvae are imaged in multiwell or multilane plates while various red, green, blue, yellow or cyan objects are presented to the larvae on a computer screen. The assays were used to examine a loss of vision at 4 or 5 days post-fertilization and a gradual recovery of vision in subsequent days. The developed assays are the first to measure the loss and recovery of vertebrate vision in microplates and provide an efficient platform to evaluate novel treatments of visual impairment.

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

PubMed

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

2004-01-01

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

The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home.

PubMed

Mihailidis, Alex; Carmichael, Brent; Boger, Jennifer

2004-09-01

This paper discusses the use of computer vision in pervasive healthcare systems, specifically in the design of a sensing agent for an intelligent environment that assists older adults with dementia during an activity of daily living. An overview of the techniques applied in this particular example is provided, along with results from preliminary trials completed using the new sensing agent. A discussion of the results obtained to date is presented, including technical and social issues that remain for the advancement and acceptance of this type of technology within pervasive healthcare.

Capsule endoscope localization based on computer vision technique.

PubMed

Liu, Li; Hu, Chao; Cai, Wentao; Meng, Max Q H

2009-01-01

To build a new type of wireless capsule endoscope with interactive gastrointestinal tract examination, a localization and orientation system is needed for tracking 3D location and 3D orientation of the capsule movement. The magnetic localization and orientation method produces only 5 DOF, but misses the information of rotation angle along capsule's main axis. In this paper, we presented a complementary orientation approach for the capsule endoscope, and the 3D rotation can be determined by applying computer vision technique on the captured endoscopic images. The experimental results show that the complementary orientation method has good accuracy and high feasibility.

Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

DTIC Science & Technology

1983-10-28

Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

Development and testing of an automated computer tablet-based method for self-testing of high and low contrast near visual acuity in ophthalmic patients.

PubMed

Aslam, Tariq M; Parry, Neil R A; Murray, Ian J; Salleh, Mahani; Col, Caterina Dal; Mirza, Naznin; Czanner, Gabriela; Tahir, Humza J

2016-05-01

Many eye diseases require on-going assessment for optimal management, creating an ever-increasing burden on patients and hospitals that could potentially be reduced through home vision monitoring. However, there is limited evidence for the utility of current applications and devices for this. To address this, we present a new automated, computer tablet-based method for self-testing near visual acuity (VA) for both high and low contrast targets. We report on its reliability and agreement with gold standard measures. The Mobile Assessment of Vision by intERactIve Computer (MAVERIC) system consists of a calibrated computer tablet housed in a bespoke viewing chamber. Purpose-built software automatically elicits touch-screen responses from subjects to measure their near VA for either low or high contrast acuity. Near high contrast acuity was measured using both the MAVERIC system and a near Landolt C chart in one eye for 81 patients and low contrast acuity using the MAVERIC system and a 25 % contrast near EDTRS chart in one eye of a separate 95 patients. The MAVERIC near acuity was also retested after 20 min to evaluate repeatability. Repeatability of both high and low contrast MAVERIC acuity measures, and their agreement with the chart tests, was assessed using the Bland-Altman comparison method. One hundred and seventy-three patients (96 %) completed the self- testing MAVERIC system without formal assistance. The resulting MAVERIC vision demonstrated good repeatability and good agreement with the gold-standard near chart measures. This study demonstrates the potential utility of the MAVERIC system for patients with ophthalmic disease to self-test their high and low contrast VA. The technique has a high degree of reliability and agreement with gold standard chart based measurements.

Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enqvist, Andreas; Koppal, Sanjeev

2015-07-01

A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for themore » purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and accounted for. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked. Infrared, laser or stereoscopic vision sensors are all options for computer-vision implementation depending on interior vs exterior deployment, resolution desired and other factors. Similarly the radiation sensors will be focused on gamma-ray or neutron detection due to the long travel length and ability to penetrate even moderate shielding. There is a significant difference between the vision sensors and radiation sensors in the way the 'source' or signals are generated. A vision sensor needs an external light-source to illuminate the object and then detects the re-emitted illumination (or lack thereof). However, for a radiation detector, the radioactive material is the source itself. The only exception to this is the field of active interrogations where radiation is beamed into a material to entice new/additional radiation emission beyond what the material would emit spontaneously. The aspect of the nuclear material being the source itself means that all other objects in the environment are 'illuminated' or irradiated by the source. Most radiation will readily penetrate regular material, scatter in new directions or be absorbed. Thus if a radiation source is located near a larger object that object will in turn scatter some radiation that was initially emitted in a direction other than the direction of the radiation detector, this can add to the count rate that is observed. The effect of these scatter is a deviation from the traditional distance dependence of the radiation signal and is a key challenge that needs a combined system calibration solution and algorithms. Thus both an algebraic approach as well as a statistical approach have been developed and independently evaluated to investigate the sensitivity to this deviation from the simplified radiation fall-off as a function of distance. The resulting calibrated system algorithms are used and demonstrated in various laboratory scenarios, and later in realistic tracking scenarios. The selection and testing of radiological and computer-vision sensors for the additional specific scenarios will be the subject of ongoing and future work. (authors)« less

Comparing visual representations across human fMRI and computational vision

PubMed Central

Leeds, Daniel D.; Seibert, Darren A.; Pyles, John A.; Tarr, Michael J.

2013-01-01

Feedforward visual object perception recruits a cortical network that is assumed to be hierarchical, progressing from basic visual features to complete object representations. However, the nature of the intermediate features related to this transformation remains poorly understood. Here, we explore how well different computer vision recognition models account for neural object encoding across the human cortical visual pathway as measured using fMRI. These neural data, collected during the viewing of 60 images of real-world objects, were analyzed with a searchlight procedure as in Kriegeskorte, Goebel, and Bandettini (2006): Within each searchlight sphere, the obtained patterns of neural activity for all 60 objects were compared to model responses for each computer recognition algorithm using representational dissimilarity analysis (Kriegeskorte et al., 2008). Although each of the computer vision methods significantly accounted for some of the neural data, among the different models, the scale invariant feature transform (Lowe, 2004), encoding local visual properties gathered from “interest points,” was best able to accurately and consistently account for stimulus representations within the ventral pathway. More generally, when present, significance was observed in regions of the ventral-temporal cortex associated with intermediate-level object perception. Differences in model effectiveness and the neural location of significant matches may be attributable to the fact that each model implements a different featural basis for representing objects (e.g., more holistic or more parts-based). Overall, we conclude that well-known computer vision recognition systems may serve as viable proxies for theories of intermediate visual object representation. PMID:24273227

Normative values for a tablet computer-based application to assess chromatic contrast sensitivity.

PubMed

Bodduluri, Lakshmi; Boon, Mei Ying; Ryan, Malcolm; Dain, Stephen J

2018-04-01

Tablet computer displays are amenable for the development of vision tests in a portable form. Assessing color vision using an easily accessible and portable test may help in the self-monitoring of vision-related changes in ocular/systemic conditions and assist in the early detection of disease processes. Tablet computer-based games were developed with different levels of gamification as a more portable option to assess chromatic contrast sensitivity. Game 1 was designed as a clinical version with no gaming elements. Game 2 was a gamified version of game 1 (added fun elements: feedback, scores, and sounds) and game 3 was a complete game with vision task nested within. The current study aimed to determine the normative values and evaluate repeatability of the tablet computer-based games in comparison with an established test, the Cambridge Colour Test (CCT) Trivector test. Normally sighted individuals [N = 100, median (range) age 19.0 years (18-56 years)] had their chromatic contrast sensitivity evaluated binocularly using the three games and the CCT. Games 1 and 2 and the CCT showed similar absolute thresholds and tolerance intervals, and game 3 had significantly lower values than games 1, 2, and the CCT, due to visual task differences. With the exception of game 3 for blue-yellow, the CCT and tablet computer-based games showed similar repeatability with comparable 95% limits of agreement. The custom-designed games are portable, rapid, and may find application in routine clinical practice, especially for testing younger populations.

Final Report on Video Log Data Mining Project

DOT National Transportation Integrated Search

2012-06-01

This report describes the development of an automated computer vision system that identities and inventories road signs : from imagery acquired from the Kansas Department of Transportations road profiling system that takes images every 26.4 : feet...

The Cyborg Astrobiologist: testing a novelty detection algorithm on two mobile exploration systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

NASA Astrophysics Data System (ADS)

McGuire, P. C.; Gross, C.; Wendt, L.; Bonnici, A.; Souza-Egipsy, V.; Ormö, J.; Díaz-Martínez, E.; Foing, B. H.; Bose, R.; Walter, S.; Oesker, M.; Ontrup, J.; Haschke, R.; Ritter, H.

2010-01-01

In previous work, a platform was developed for testing computer-vision algorithms for robotic planetary exploration. This platform consisted of a digital video camera connected to a wearable computer for real-time processing of images at geological and astrobiological field sites. The real-time processing included image segmentation and the generation of interest points based upon uncommonness in the segmentation maps. Also in previous work, this platform for testing computer-vision algorithms has been ported to a more ergonomic alternative platform, consisting of a phone camera connected via the Global System for Mobile Communications (GSM) network to a remote-server computer. The wearable-computer platform has been tested at geological and astrobiological field sites in Spain (Rivas Vaciamadrid and Riba de Santiuste), and the phone camera has been tested at a geological field site in Malta. In this work, we (i) apply a Hopfield neural-network algorithm for novelty detection based upon colour, (ii) integrate a field-capable digital microscope on the wearable computer platform, (iii) test this novelty detection with the digital microscope at Rivas Vaciamadrid, (iv) develop a Bluetooth communication mode for the phone-camera platform, in order to allow access to a mobile processing computer at the field sites, and (v) test the novelty detection on the Bluetooth-enabled phone camera connected to a netbook computer at the Mars Desert Research Station in Utah. This systems engineering and field testing have together allowed us to develop a real-time computer-vision system that is capable, for example, of identifying lichens as novel within a series of images acquired in semi-arid desert environments. We acquired sequences of images of geologic outcrops in Utah and Spain consisting of various rock types and colours to test this algorithm. The algorithm robustly recognized previously observed units by their colour, while requiring only a single image or a few images to learn colours as familiar, demonstrating its fast learning capability.

Experimental validation of docking and capture using space robotics testbeds

NASA Technical Reports Server (NTRS)

Spofford, John; Schmitz, Eric; Hoff, William

1991-01-01

This presentation describes the application of robotic and computer vision systems to validate docking and capture operations for space cargo transfer vehicles. Three applications are discussed: (1) air bearing systems in two dimensions that yield high quality free-flying, flexible, and contact dynamics; (2) validation of docking mechanisms with misalignment and target dynamics; and (3) computer vision technology for target location and real-time tracking. All the testbeds are supported by a network of engineering workstations for dynamic and controls analyses. Dynamic simulation of multibody rigid and elastic systems are performed with the TREETOPS code. MATRIXx/System-Build and PRO-MATLAB/Simulab are the tools for control design and analysis using classical and modern techniques such as H-infinity and LQG/LTR. SANDY is a general design tool to optimize numerically a multivariable robust compensator with a user-defined structure. Mathematica and Macsyma are used to derive symbolically dynamic and kinematic equations.

Development of a Computer Vision Technology for the Forest Products Manufacturing Industry

Treesearch

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

1992-01-01

The goal of this research is to create an automated processing/grading system for hardwood lumber that will be of use to the forest products industry. The objective of creating a full scale machine vision prototype for inspecting hardwood lumber will become a reality in calendar year 1992. Space for the full scale prototype has been created at the Brooks Forest...

Experiences Using an Open Source Software Library to Teach Computer Vision Subjects

ERIC Educational Resources Information Center

Cazorla, Miguel; Viejo, Diego

2015-01-01

Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with emphasis on readability and…

Flexible Wing Base Micro Aerial Vehicles: Vision-Guided Flight Stability and Autonomy for Micro Air Vehicles

NASA Technical Reports Server (NTRS)

Ettinger, Scott M.; Nechyba, Michael C.; Ifju, Peter G.; Wazak, Martin

2002-01-01

Substantial progress has been made recently towards design building and test-flying remotely piloted Micro Air Vehicle's (MAVs). We seek to complement this progress in overcoming the aerodynamic obstacles to.flight at very small scales with a vision stability and autonomy system. The developed system based on a robust horizon detection algorithm which we discuss in greater detail in a companion paper. In this paper, we first motivate the use of computer vision for MAV autonomy arguing that given current sensor technology, vision may he the only practical approach to the problem. We then briefly review our statistical vision-based horizon detection algorithm, which has been demonstrated at 30Hz with over 99.9% correct horizon identification. Next we develop robust schemes for the detection of extreme MAV attitudes, where no horizon is visible, and for the detection of horizon estimation errors, due to external factors such as video transmission noise. Finally, we discuss our feed-back controller for self-stabilized flight, and report results on vision autonomous flights of duration exceeding ten minutes.

Cutting tool form compensation system and method

DOEpatents

Barkman, W.E.; Babelay, E.F. Jr.; Klages, E.J.

1993-10-19

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed. 9 figures.

Cutting tool form compensaton system and method

DOEpatents

Barkman, William E.; Babelay, Jr., Edwin F.; Klages, Edward J.

1993-01-01

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed.

Data, Analysis, and Visualization | Computational Science | NREL

Science.gov Websites

Data, Analysis, and Visualization Data, Analysis, and Visualization Data management, data analysis . At NREL, our data management, data analysis, and scientific visualization capabilities help move the approaches to image analysis and computer vision. Data Management and Big Data Systems, software, and tools

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.

PubMed

Orchard, Garrick; Jayawant, Ajinkya; Cohen, Gregory K; Thakor, Nitish

2015-01-01

Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.

Notes from a clinical information system program manager. A solid vision makes all the difference.

PubMed

Staggers, N

1997-01-01

Today's CIS manager will create a vision that connects computerization in ambulatory, home and community-based care with increased responsibility for patients to assume self-care. Patients will be faced with a glut of information and they will need nursing help in determining the validity of information. The new vision in this environment will focus on integration, interoperability, and a new definition for patient-centered information. Creating a well-articulated vision is the first skill in the repertoire of a CIS manager's tool set. A vision provides the firm structure upon which the entire project can be built, and provides for links to life-cycle planning. This first step in project planning begins to bring order to the chaos of dynamic demands in clinical computing.

Vision based flight procedure stereo display system

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Mobile camera-space manipulation

NASA Technical Reports Server (NTRS)

Seelinger, Michael J. (Inventor); Yoder, John-David S. (Inventor); Skaar, Steven B. (Inventor)

2001-01-01

The invention is a method of using computer vision to control systems consisting of a combination of holonomic and nonholonomic degrees of freedom such as a wheeled rover equipped with a robotic arm, a forklift, and earth-moving equipment such as a backhoe or a front-loader. Using vision sensors mounted on the mobile system and the manipulator, the system establishes a relationship between the internal joint configuration of the holonomic degrees of freedom of the manipulator and the appearance of features on the manipulator in the reference frames of the vision sensors. Then, the system, perhaps with the assistance of an operator, identifies the locations of the target object in the reference frames of the vision sensors. Using this target information, along with the relationship described above, the system determines a suitable trajectory for the nonholonomic degrees of freedom of the base to follow towards the target object. The system also determines a suitable pose or series of poses for the holonomic degrees of freedom of the manipulator. With additional visual samples, the system automatically updates the trajectory and final pose of the manipulator so as to allow for greater precision in the overall final position of the system.

Computer vision challenges and technologies for agile manufacturing

NASA Astrophysics Data System (ADS)

Molley, Perry A.

1996-02-01

Sandia National Laboratories, a Department of Energy laboratory, is responsible for maintaining the safety, security, reliability, and availability of the nuclear weapons stockpile for the United States. Because of the changing national and global political climates and inevitable budget cuts, Sandia is changing the methods and processes it has traditionally used in the product realization cycle for weapon components. Because of the increasing age of the nuclear stockpile, it is certain that the reliability of these weapons will degrade with time unless eventual action is taken to repair, requalify, or renew them. Furthermore, due to the downsizing of the DOE weapons production sites and loss of technical personnel, the new product realization process is being focused on developing and deploying advanced automation technologies in order to maintain the capability for producing new components. The goal of Sandia's technology development program is to create a product realization environment that is cost effective, has improved quality and reduced cycle time for small lot sizes. The new environment will rely less on the expertise of humans and more on intelligent systems and automation to perform the production processes. The systems will be robust in order to provide maximum flexibility and responsiveness for rapidly changing component or product mixes. An integrated enterprise will allow ready access to and use of information for effective and efficient product and process design. Concurrent engineering methods will allow a speedup of the product realization cycle, reduce costs, and dramatically lessen the dependency on creating and testing physical prototypes. Virtual manufacturing will allow production processes to be designed, integrated, and programed off-line before a piece of hardware ever moves. The overriding goal is to be able to build a large variety of new weapons parts on short notice. Many of these technologies that are being developed are also applicable to commercial production processes and applications. Computer vision will play a critical role in the new agile production environment for automation of processes such as inspection, assembly, welding, material dispensing and other process control tasks. Although there are many academic and commercial solutions that have been developed, none have had widespread adoption considering the huge potential number of applications that could benefit from this technology. The reason for this slow adoption is that the advantages of computer vision for automation can be a double-edged sword. The benefits can be lost if the vision system requires an inordinate amount of time for reprogramming by a skilled operator to account for different parts, changes in lighting conditions, background clutter, changes in optics, etc. Commercially available solutions typically require an operator to manually program the vision system with features used for the recognition. In a recent survey, we asked a number of commercial manufacturers and machine vision companies the question, 'What prevents machine vision systems from being more useful in factories?' The number one (and unanimous) response was that vision systems require too much skill to set up and program to be cost effective.

Method and apparatus for predicting the direction of movement in machine vision

NASA Technical Reports Server (NTRS)

Lawton, Teri B. (Inventor)

1992-01-01

A computer-simulated cortical network is presented. The network is capable of computing the visibility of shifts in the direction of movement. Additionally, the network can compute the following: (1) the magnitude of the position difference between the test and background patterns; (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern; and (3) the direction of a test pattern moved relative to a textured background. The direction of movement of an object in the field of view of a robotic vision system is detected in accordance with nonlinear Gabor function algorithms. The movement of objects relative to their background is used to infer the 3-dimensional structure and motion of object surfaces.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Integrated Imaging and Vision Techniques for Industrial Inspection: A Special Issue on Machine Vision and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2010-06-05

Imaging- and vision-based techniques play an important role in industrial inspection. The sophistication of the techniques assures high- quality performance of the manufacturing process through precise positioning, online monitoring, and real-time classification. Advanced systems incorporating multiple imaging and/or vision modalities provide robust solutions to complex situations and problems in industrial applications. A diverse range of industries, including aerospace, automotive, electronics, pharmaceutical, biomedical, semiconductor, and food/beverage, etc., have benefited from recent advances in multi-modal imaging, data fusion, and computer vision technologies. Many of the open problems in this context are in the general area of image analysis methodologies (preferably in anmore » automated fashion). This editorial article introduces a special issue of this journal highlighting recent advances and demonstrating the successful applications of integrated imaging and vision technologies in industrial inspection.« less

Artificial Intelligence and the High School Computer Curriculum.

ERIC Educational Resources Information Center

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…

Hypertext-based computer vision teaching packages

NASA Astrophysics Data System (ADS)

Marshall, A. David

1994-10-01

The World Wide Web Initiative has provided a means for providing hypertext and multimedia based information across the whole INTERNET. Many applications have been developed on such http servers. At Cardiff we have developed a http hypertext based multimedia server, the Cardiff Information Server, using the widely available Mosaic system. The server provides a variety of information ranging from the provision of teaching modules, on- line documentation, timetables for departmental activities to more light hearted hobby interests. One important and novel development to the server has been the development of courseware facilities. This ranges from the provision of on-line lecture notes, exercises and their solutions to more interactive teaching packages. A variety of disciplines have benefitted notably Computer Vision, and Image Processing but also C programming, X Windows, Computer Graphics and Parallel Computing. This paper will address the issues of the implementation of the Computer Vision and Image Processing packages, the advantages gained from using a hypertext based system and also will relate practical experiences of using the packages in a class environment. The paper addresses issues of how best to provide information in such a hypertext based system and how interactive image processing packages can be developed and integrated into courseware. The suite of tools developed facilitates a flexible and powerful courseware package that has proved popular in the classroom and over the Internet. The paper will also detail many future developments we see possible. One of the key points raised in the paper is that Mosaic's hypertext language (html) is extremely powerful and yet relatively straightforward to use. It is also possible to link in Unix calls so that programs and shells can be executed. This provides a powerful suite of utilities that can be exploited to develop many packages.

Vision System Measures Motions of Robot and External Objects

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Matthies, Larry

2008-01-01

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Sensory Interactive Teleoperator Robotic Grasping

NASA Technical Reports Server (NTRS)

Alark, Keli; Lumia, Ron

1997-01-01

As the technological world strives for efficiency, the need for economical equipment that increases operator proficiency in minimal time is fundamental. This system links a CCD camera, a controller and a robotic arm to a computer vision system to provide an alternative method of image analysis. The machine vision system which was employed possesses software tools for acquiring and analyzing images which are received through a CCD camera. After feature extraction on the object in the image was performed, information about the object's location, orientation and distance from the robotic gripper is sent to the robot controller so that the robot can manipulate the object.

Quality grading of Atlantic salmon (Salmo salar) by computer vision.

PubMed

Misimi, E; Erikson, U; Skavhaug, A

2008-06-01

In this study, we present a promising method of computer vision-based quality grading of whole Atlantic salmon (Salmo salar). Using computer vision, it was possible to differentiate among different quality grades of Atlantic salmon based on the external geometrical information contained in the fish images. Initially, before the image acquisition, the fish were subjectively graded and labeled into grading classes by a qualified human inspector in the processing plant. Prior to classification, the salmon images were segmented into binary images, and then feature extraction was performed on the geometrical parameters of the fish from the grading classes. The classification algorithm was a threshold-based classifier, which was designed using linear discriminant analysis. The performance of the classifier was tested by using the leave-one-out cross-validation method, and the classification results showed a good agreement between the classification done by human inspectors and by the computer vision. The computer vision-based method classified correctly 90% of the salmon from the data set as compared with the classification by human inspector. Overall, it was shown that computer vision can be used as a powerful tool to grade Atlantic salmon into quality grades in a fast and nondestructive manner by a relatively simple classifier algorithm. The low cost of implementation of today's advanced computer vision solutions makes this method feasible for industrial purposes in fish plants as it can replace manual labor, on which grading tasks still rely.

Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

PubMed

Wolff, J Gerard

2014-01-01

The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

Object extraction in photogrammetric computer vision

NASA Astrophysics Data System (ADS)

Mayer, Helmut

This paper discusses state and promising directions of automated object extraction in photogrammetric computer vision considering also practical aspects arising for digital photogrammetric workstations (DPW). A review of the state of the art shows that there are only few practically successful systems on the market. Therefore, important issues for a practical success of automated object extraction are identified. A sound and most important powerful theoretical background is the basis. Here, we particularly point to statistical modeling. Testing makes clear which of the approaches are suited best and how useful they are for praxis. A key for commercial success of a practical system is efficient user interaction. As the means for data acquisition are changing, new promising application areas such as extremely detailed three-dimensional (3D) urban models for virtual television or mission rehearsal evolve.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

NASA Astrophysics Data System (ADS)

Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

2015-10-01

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing.

PubMed

Stone, Erik E; Skubic, Marjorie

2011-01-01

We present an analysis of measuring stride-to-stride gait variability passively, in a home setting using two vision based monitoring techniques: anonymized video data from a system of two web-cameras, and depth imagery from a single Microsoft Kinect. Millions of older adults fall every year. The ability to assess the fall risk of elderly individuals is essential to allowing them to continue living safely in independent settings as they age. Studies have shown that measures of stride-to-stride gait variability are predictive of falls in older adults. For this analysis, a set of participants were asked to perform a number of short walks while being monitored by the two vision based systems, along with a marker based Vicon motion capture system for ground truth. Measures of stride-to-stride gait variability were computed using each of the systems and compared against those obtained from the Vicon.

Convolutional neural networks and face recognition task

NASA Astrophysics Data System (ADS)

Sochenkova, A.; Sochenkov, I.; Makovetskii, A.; Vokhmintsev, A.; Melnikov, A.

2017-09-01

Computer vision tasks are remaining very important for the last couple of years. One of the most complicated problems in computer vision is face recognition that could be used in security systems to provide safety and to identify person among the others. There is a variety of different approaches to solve this task, but there is still no universal solution that would give adequate results in some cases. Current paper presents following approach. Firstly, we extract an area containing face, then we use Canny edge detector. On the next stage we use convolutional neural networks (CNN) to finally solve face recognition and person identification task.

Colour calibration of a laboratory computer vision system for quality evaluation of pre-sliced hams.

PubMed

Valous, Nektarios A; Mendoza, Fernando; Sun, Da-Wen; Allen, Paul

2009-01-01

Due to the high variability and complex colour distribution in meats and meat products, the colour signal calibration of any computer vision system used for colour quality evaluations, represents an essential condition for objective and consistent analyses. This paper compares two methods for CIE colour characterization using a computer vision system (CVS) based on digital photography; namely the polynomial transform procedure and the transform proposed by the sRGB standard. Also, it presents a procedure for evaluating the colour appearance and presence of pores and fat-connective tissue on pre-sliced hams made from pork, turkey and chicken. Our results showed high precision, in colour matching, for device characterization when the polynomial transform was used to match the CIE tristimulus values in comparison with the sRGB standard approach as indicated by their ΔE(ab)(∗) values. The [3×20] polynomial transfer matrix yielded a modelling accuracy averaging below 2.2 ΔE(ab)(∗) units. Using the sRGB transform, high variability was appreciated among the computed ΔE(ab)(∗) (8.8±4.2). The calibrated laboratory CVS, implemented with a low-cost digital camera, exhibited reproducible colour signals in a wide range of colours capable of pinpointing regions-of-interest and allowed the extraction of quantitative information from the overall ham slice surface with high accuracy. The extracted colour and morphological features showed potential for characterizing the appearance of ham slice surfaces. CVS is a tool that can objectively specify colour and appearance properties of non-uniformly coloured commercial ham slices.

Can Humans Fly Action Understanding with Multiple Classes of Actors

DTIC Science & Technology

2015-06-08

recognition using structure from motion point clouds. In European Conference on Computer Vision, 2008. [5] R. Caruana. Multitask learning. Machine Learning...tonomous driving ? the kitti vision benchmark suite. In IEEE Conference on Computer Vision and Pattern Recognition, 2012. [12] L. Gorelick, M. Blank

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Design of an efficient framework for fast prototyping of customized human-computer interfaces and virtual environments for rehabilitation.

PubMed

Avola, Danilo; Spezialetti, Matteo; Placidi, Giuseppe

2013-06-01

Rehabilitation is often required after stroke, surgery, or degenerative diseases. It has to be specific for each patient and can be easily calibrated if assisted by human-computer interfaces and virtual reality. Recognition and tracking of different human body landmarks represent the basic features for the design of the next generation of human-computer interfaces. The most advanced systems for capturing human gestures are focused on vision-based techniques which, on the one hand, may require compromises from real-time and spatial precision and, on the other hand, ensure natural interaction experience. The integration of vision-based interfaces with thematic virtual environments encourages the development of novel applications and services regarding rehabilitation activities. The algorithmic processes involved during gesture recognition activity, as well as the characteristics of the virtual environments, can be developed with different levels of accuracy. This paper describes the architectural aspects of a framework supporting real-time vision-based gesture recognition and virtual environments for fast prototyping of customized exercises for rehabilitation purposes. The goal is to provide the therapist with a tool for fast implementation and modification of specific rehabilitation exercises for specific patients, during functional recovery. Pilot examples of designed applications and preliminary system evaluation are reported and discussed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Progress in building a cognitive vision system

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Yue, Hong

2016-05-01

We are building a cognitive vision system for mobile robots that works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion to create a local dynamic spatial model. These local 3D models are composed to create an overall 3D model of the robot and its environment. This approach turns the computer vision problem into a search problem whose goal is the acquisition of sufficient spatial understanding for the robot to succeed at its tasks. The research hypothesis of this work is that the movements of the robot's cameras are only those that are necessary to build a sufficiently accurate world model for the robot's current goals. For example, if the goal is to navigate through a room, the model needs to contain any obstacles that would be encountered, giving their approximate positions and sizes. Other information does not need to be rendered into the virtual world, so this approach trades model accuracy for speed.

Automated egg grading system using computer vision: Investigation on weight measure versus shape parameters

NASA Astrophysics Data System (ADS)

Nasir, Ahmad Fakhri Ab; Suhaila Sabarudin, Siti; Majeed, Anwar P. P. Abdul; Ghani, Ahmad Shahrizan Abdul

2018-04-01

Chicken egg is a source of food of high demand by humans. Human operators cannot work perfectly and continuously when conducting egg grading. Instead of an egg grading system using weight measure, an automatic system for egg grading using computer vision (using egg shape parameter) can be used to improve the productivity of egg grading. However, early hypothesis has indicated that more number of egg classes will change when using egg shape parameter compared with using weight measure. This paper presents the comparison of egg classification by the two above-mentioned methods. Firstly, 120 images of chicken eggs of various grades (A–D) produced in Malaysia are captured. Then, the egg images are processed using image pre-processing techniques, such as image cropping, smoothing and segmentation. Thereafter, eight egg shape features, including area, major axis length, minor axis length, volume, diameter and perimeter, are extracted. Lastly, feature selection (information gain ratio) and feature extraction (principal component analysis) are performed using k-nearest neighbour classifier in the classification process. Two methods, namely, supervised learning (using weight measure as graded by egg supplier) and unsupervised learning (using egg shape parameters as graded by ourselves), are conducted to execute the experiment. Clustering results reveal many changes in egg classes after performing shape-based grading. On average, the best recognition results using shape-based grading label is 94.16% while using weight-based label is 44.17%. As conclusion, automated egg grading system using computer vision is better by implementing shape-based features since it uses image meanwhile the weight parameter is more suitable by using weight grading system.

Smartphones as image processing systems for prosthetic vision.

PubMed

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

2013-01-01

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

Vision based assistive technology for people with dementia performing activities of daily living (ADLs): an overview

NASA Astrophysics Data System (ADS)

As'ari, M. A.; Sheikh, U. U.

2012-04-01

The rapid development of intelligent assistive technology for replacing a human caregiver in assisting people with dementia performing activities of daily living (ADLs) promises in the reduction of care cost especially in training and hiring human caregiver. The main problem however, is the various kinds of sensing agents used in such system and is dependent on the intent (types of ADLs) and environment where the activity is performed. In this paper on overview of the potential of computer vision based sensing agent in assistive system and how it can be generalized and be invariant to various kind of ADLs and environment. We find that there exists a gap from the existing vision based human action recognition method in designing such system due to cognitive and physical impairment of people with dementia.

Image-Based Modeling Techniques for Architectural Heritage 3d Digitalization: Limits and Potentialities

NASA Astrophysics Data System (ADS)

Santagati, C.; Inzerillo, L.; Di Paola, F.

2013-07-01

3D reconstruction from images has undergone a revolution in the last few years. Computer vision techniques use photographs from data set collection to rapidly build detailed 3D models. The simultaneous applications of different algorithms (MVS), the different techniques of image matching, feature extracting and mesh optimization are inside an active field of research in computer vision. The results are promising: the obtained models are beginning to challenge the precision of laser-based reconstructions. Among all the possibilities we can mainly distinguish desktop and web-based packages. Those last ones offer the opportunity to exploit the power of cloud computing in order to carry out a semi-automatic data processing, thus allowing the user to fulfill other tasks on its computer; whereas desktop systems employ too much processing time and hard heavy approaches. Computer vision researchers have explored many applications to verify the visual accuracy of 3D model but the approaches to verify metric accuracy are few and no one is on Autodesk 123D Catch applied on Architectural Heritage Documentation. Our approach to this challenging problem is to compare the 3Dmodels by Autodesk 123D Catch and 3D models by terrestrial LIDAR considering different object size, from the detail (capitals, moldings, bases) to large scale buildings for practitioner purpose.

Beyond the computer-based patient record: re-engineering with a vision.

PubMed

Genn, B; Geukers, L

1995-01-01

In order to achieve real benefit from the potential offered by a Computer-Based Patient Record, the capabilities of the technology must be applied along with true re-engineering of healthcare delivery processes. University Hospital recognizes this and is using systems implementation projects, such as the catalyst, for transforming the way we care for our patients. Integration is fundamental to the success of these initiatives and this must be explicitly planned against an organized systems architecture whose standards are market-driven. University Hospital also recognizes that Community Health Information Networks will offer improved quality of patient care at a reduced overall cost to the system. All of these implementation factors are considered up front as the hospital makes its initial decisions on to how to computerize its patient records. This improves our chances for success and will provide a consistent vision to guide the hospital's development of new and better patient care.

Determination of high temperature strains using a PC based vision system

NASA Astrophysics Data System (ADS)

McNeill, Stephen R.; Sutton, Michael A.; Russell, Samuel S.

1992-09-01

With the widespread availability of video digitizers and cheap personal computers, the use of computer vision as an experimental tool is becoming common place. These systems are being used to make a wide variety of measurements that range from simple surface characterization to velocity profiles. The Sub-Pixel Digital Image Correlation technique has been developed to measure full field displacement and gradients of the surface of an object subjected to a driving force. The technique has shown its utility by measuring the deformation and movement of objects that range from simple translation to fluid velocity profiles to crack tip deformation of solid rocket fuel. This technique has recently been improved and used to measure the surface displacement field of an object at high temperature. The development of a PC based Sub-Pixel Digital Image Correlation system has yielded an accurate and easy to use system for measuring surface displacements and gradients. Experiments have been performed to show the system is viable for measuring thermal strain.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-01-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Astrophysics Data System (ADS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-02-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

Handheld pose tracking using vision-inertial sensors with occlusion handling

NASA Astrophysics Data System (ADS)

Li, Juan; Slembrouck, Maarten; Deboeverie, Francis; Bernardos, Ana M.; Besada, Juan A.; Veelaert, Peter; Aghajan, Hamid; Casar, José R.; Philips, Wilfried

2016-07-01

Tracking of a handheld device's three-dimensional (3-D) position and orientation is fundamental to various application domains, including augmented reality (AR), virtual reality, and interaction in smart spaces. Existing systems still offer limited performance in terms of accuracy, robustness, computational cost, and ease of deployment. We present a low-cost, accurate, and robust system for handheld pose tracking using fused vision and inertial data. The integration of measurements from embedded accelerometers reduces the number of unknown parameters in the six-degree-of-freedom pose calculation. The proposed system requires two light-emitting diode (LED) markers to be attached to the device, which are tracked by external cameras through a robust algorithm against illumination changes. Three data fusion methods have been proposed, including the triangulation-based stereo-vision system, constraint-based stereo-vision system with occlusion handling, and triangulation-based multivision system. Real-time demonstrations of the proposed system applied to AR and 3-D gaming are also included. The accuracy assessment of the proposed system is carried out by comparing with the data generated by the state-of-the-art commercial motion tracking system OptiTrack. Experimental results show that the proposed system has achieved high accuracy of few centimeters in position estimation and few degrees in orientation estimation.

Applications of wavelets in interferometry and artificial vision

NASA Astrophysics Data System (ADS)

Escalona Z., Rafael A.

2001-08-01

In this paper we present a different point of view of phase measurements performed in interferometry, image processing and intelligent vision using Wavelet Transform. In standard and white-light interferometry, the phase function is retrieved by using phase-shifting, Fourier-Transform, cosinus-inversion and other known algorithms. Our novel technique presented here is faster, robust and shows excellent accuracy in phase determinations. Finally, in our second application, fringes are no more generate by some light interaction but result from the observation of adapted strip set patterns directly printed on the target of interest. The moving target is simply observed by a conventional vision system and usual phase computation algorithms are adapted to an image processing by wavelet transform, in order to sense target position and displacements with a high accuracy. In general, we have determined that wavelet transform presents properties of robustness, relative speed of calculus and very high accuracy in phase computations.

Computer Vision Syndrome.

PubMed

Randolph, Susan A

2017-07-01

With the increased use of electronic devices with visual displays, computer vision syndrome is becoming a major public health issue. Improving the visual status of workers using computers results in greater productivity in the workplace and improved visual comfort.

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

Dirt detection on brown eggs by means of color computer vision.

PubMed

Mertens, K; De Ketelaere, B; Kamers, B; Bamelis, F R; Kemps, B J; Verhoelst, E M; De Baerdemaeker, J G; Decuypere, E M

2005-10-01

In the last 20 yr, different methods for detecting defects in eggs were developed. Until now, no satisfying technique existed to sort and quantify dirt on eggshells. The work presented here focuses on the design of an off-line computer vision system to differentiate and quantify the presence of different dirt stains on brown eggs: dark (feces), white (uric acid), blood, and yolk stains. A system that provides uniform light exposure around the egg was designed. In this uniform light, pictures of dirty and clean eggs were taken, stored, and analyzed. The classification was based on a few standard logical operators, allowing for a quick implementation in an online set-up. In an experiment, 100 clean and 100 dirty eggs were used to validate the classification algorithm. The designed vision system showed an accuracy of 99% for the detection of dirt stains. Two percent of the clean eggs had a light-colored eggshell and were subsequently mistaken for showing large white stains. The accuracy of differentiation of the different kinds of dirt stains was 91%. Of the eggs with dark stains, 10.81% were mistaken for having bloodstains, and 33.33% of eggs with bloodstains were mistaken for having dark stains. The developed system is possibly a first step toward an on line dirt evaluation technique for brown eggs.

Video control system for a drilling in furniture workpiece

NASA Astrophysics Data System (ADS)

Khmelev, V. L.; Satarov, R. N.; Zavyalova, K. V.

2018-05-01

During last 5 years, Russian industry has being starting to be a robotic, therefore scientific groups got new tasks. One of new tasks is machine vision systems, which should solve problem of automatic quality control. This type of systems has a cost of several thousand dollars each. The price is impossible for regional small business. In this article, we describe principle and algorithm of cheap video control system, which one uses web-cameras and notebook or desktop computer as a computing unit.

Measuring exertion time, duty cycle and hand activity level for industrial tasks using computer vision.

PubMed

Akkas, Oguz; Lee, Cheng Hsien; Hu, Yu Hen; Harris Adamson, Carisa; Rempel, David; Radwin, Robert G

2017-12-01

Two computer vision algorithms were developed to automatically estimate exertion time, duty cycle (DC) and hand activity level (HAL) from videos of workers performing 50 industrial tasks. The average DC difference between manual frame-by-frame analysis and the computer vision DC was -5.8% for the Decision Tree (DT) algorithm, and 1.4% for the Feature Vector Training (FVT) algorithm. The average HAL difference was 0.5 for the DT algorithm and 0.3 for the FVT algorithm. A sensitivity analysis, conducted to examine the influence that deviations in DC have on HAL, found it remained unaffected when DC error was less than 5%. Thus, a DC error less than 10% will impact HAL less than 0.5 HAL, which is negligible. Automatic computer vision HAL estimates were therefore comparable to manual frame-by-frame estimates. Practitioner Summary: Computer vision was used to automatically estimate exertion time, duty cycle and hand activity level from videos of workers performing industrial tasks.

Three-Dimensional Images For Robot Vision

NASA Astrophysics Data System (ADS)

McFarland, William D.

1983-12-01

Robots are attracting increased attention in the industrial productivity crisis. As one significant approach for this nation to maintain technological leadership, the need for robot vision has become critical. The "blind" robot, while occupying an economical niche at present is severely limited and job specific, being only one step up from the numerical controlled machines. To successfully satisfy robot vision requirements a three dimensional representation of a real scene must be provided. Several image acquistion techniques are discussed with more emphasis on the laser radar type instruments. The autonomous vehicle is also discussed as a robot form, and the requirements for these applications are considered. The total computer vision system requirement is reviewed with some discussion of the major techniques in the literature for three dimensional scene analysis.

Surpassing Humans and Computers with JellyBean: Crowd-Vision-Hybrid Counting Algorithms.

PubMed

Sarma, Akash Das; Jain, Ayush; Nandi, Arnab; Parameswaran, Aditya; Widom, Jennifer

2015-11-01

Counting objects is a fundamental image processisng primitive, and has many scientific, health, surveillance, security, and military applications. Existing supervised computer vision techniques typically require large quantities of labeled training data, and even with that, fail to return accurate results in all but the most stylized settings. Using vanilla crowd-sourcing, on the other hand, can lead to significant errors, especially on images with many objects. In this paper, we present our JellyBean suite of algorithms, that combines the best of crowds and computer vision to count objects in images, and uses judicious decomposition of images to greatly improve accuracy at low cost. Our algorithms have several desirable properties: (i) they are theoretically optimal or near-optimal , in that they ask as few questions as possible to humans (under certain intuitively reasonable assumptions that we justify in our paper experimentally); (ii) they operate under stand-alone or hybrid modes, in that they can either work independent of computer vision algorithms, or work in concert with them, depending on whether the computer vision techniques are available or useful for the given setting; (iii) they perform very well in practice, returning accurate counts on images that no individual worker or computer vision algorithm can count correctly, while not incurring a high cost.

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

A light-stimulated synaptic device based on graphene hybrid phototransistor

NASA Astrophysics Data System (ADS)

Qin, Shuchao; Wang, Fengqiu; Liu, Yujie; Wan, Qing; Wang, Xinran; Xu, Yongbing; Shi, Yi; Wang, Xiaomu; Zhang, Rong

2017-09-01

Neuromorphic chips refer to an unconventional computing architecture that is modelled on biological brains. They are increasingly employed for processing sensory data for machine vision, context cognition, and decision making. Despite rapid advances, neuromorphic computing has remained largely an electronic technology, making it a challenge to access the superior computing features provided by photons, or to directly process vision data that has increasing importance to artificial intelligence. Here we report a novel light-stimulated synaptic device based on a graphene-carbon nanotube hybrid phototransistor. Significantly, the device can respond to optical stimuli in a highly neuron-like fashion and exhibits flexible tuning of both short- and long-term plasticity. These features combined with the spatiotemporal processability make our device a capable counterpart to today’s electrically-driven artificial synapses, with superior reconfigurable capabilities. In addition, our device allows for generic optical spike processing, which provides a foundation for more sophisticated computing. The silicon-compatible, multifunctional photosensitive synapse opens up a new opportunity for neural networks enabled by photonics and extends current neuromorphic systems in terms of system complexities and functionalities.

MER-DIMES : a planetary landing application of computer vision

NASA Technical Reports Server (NTRS)

Cheng, Yang; Johnson, Andrew; Matthies, Larry

2005-01-01

During the Mars Exploration Rovers (MER) landings, the Descent Image Motion Estimation System (DIMES) was used for horizontal velocity estimation. The DIMES algorithm combines measurements from a descent camera, a radar altimeter and an inertial measurement unit. To deal with large changes in scale and orientation between descent images, the algorithm uses altitude and attitude measurements to rectify image data to level ground plane. Feature selection and tracking is employed in the rectified data to compute the horizontal motion between images. Differences of motion estimates are then compared to inertial measurements to verify correct feature tracking. DIMES combines sensor data from multiple sources in a novel way to create a low-cost, robust and computationally efficient velocity estimation solution, and DIMES is the first use of computer vision to control a spacecraft during planetary landing. In this paper, the detailed implementation of the DIMES algorithm and the results from the two landings on Mars are presented.

Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges

PubMed Central

Lee, Junhwa; Lee, Kyoung-Chan; Cho, Soojin

2017-01-01

The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a low-cost and non-contact displacement measurement that converts the movement of an object, mostly an attached marker, in the captured images into structural displacement. However, there is limited research on addressing light-induced measurement error caused by the inevitable sunlight in field-testing conditions. This study presents a computer vision-based displacement measurement approach tailored to a field-testing environment with enhanced robustness to strong sunlight. An image-processing algorithm with an adaptive region-of-interest (ROI) is proposed to reliably determine a marker’s location even when the marker is indistinct due to unfavorable light. The performance of the proposed system is experimentally validated in both laboratory-scale and field experiments. PMID:29019950

Computer vision cracks the leaf code

PubMed Central

Wilf, Peter; Zhang, Shengping; Chikkerur, Sharat; Little, Stefan A.; Wing, Scott L.; Serre, Thomas

2016-01-01

Understanding the extremely variable, complex shape and venation characters of angiosperm leaves is one of the most challenging problems in botany. Machine learning offers opportunities to analyze large numbers of specimens, to discover novel leaf features of angiosperm clades that may have phylogenetic significance, and to use those characters to classify unknowns. Previous computer vision approaches have primarily focused on leaf identification at the species level. It remains an open question whether learning and classification are possible among major evolutionary groups such as families and orders, which usually contain hundreds to thousands of species each and exhibit many times the foliar variation of individual species. Here, we tested whether a computer vision algorithm could use a database of 7,597 leaf images from 2,001 genera to learn features of botanical families and orders, then classify novel images. The images are of cleared leaves, specimens that are chemically bleached, then stained to reveal venation. Machine learning was used to learn a codebook of visual elements representing leaf shape and venation patterns. The resulting automated system learned to classify images into families and orders with a success rate many times greater than chance. Of direct botanical interest, the responses of diagnostic features can be visualized on leaf images as heat maps, which are likely to prompt recognition and evolutionary interpretation of a wealth of novel morphological characters. With assistance from computer vision, leaves are poised to make numerous new contributions to systematic and paleobotanical studies. PMID:26951664

Optomechatronic System For Automated Intra Cytoplasmic Sperm Injection

NASA Astrophysics Data System (ADS)

Shulev, Assen; Tiankov, Tihomir; Ignatova, Detelina; Kostadinov, Kostadin; Roussev, Ilia; Trifonov, Dimitar; Penchev, Valentin

2015-12-01

This paper presents a complex optomechatronic system for In-Vitro Fertilization (IVF), offering almost complete automation of the Intra Cytoplasmic Sperm Injection (ICSI) procedure. The compound parts and sub-systems, as well as some of the computer vision algorithms, are described below. System capabilities for ICSI have been demonstrated on infertile oocyte cells.

An Operationally Based Vision Assessment Simulator for Domes

NASA Technical Reports Server (NTRS)

Archdeacon, John; Gaska, James; Timoner, Samson

2012-01-01

The Operational Based Vision Assessment (OBVA) simulator was designed and built by NASA and the United States Air Force (USAF) to provide the Air Force School of Aerospace Medicine (USAFSAM) with a scientific testing laboratory to study human vision and testing standards in an operationally relevant environment. This paper describes the general design objectives and implementation characteristics of the simulator visual system being created to meet these requirements. A key design objective for the OBVA research simulator is to develop a real-time computer image generator (IG) and display subsystem that can display and update at 120 frame s per second (design target), or at a minimum, 60 frames per second, with minimal transport delay using commercial off-the-shelf (COTS) technology. There are three key parts of the OBVA simulator that are described in this paper: i) the real-time computer image generator, ii) the various COTS technology used to construct the simulator, and iii) the spherical dome display and real-time distortion correction subsystem. We describe the various issues, possible COTS solutions, and remaining problem areas identified by NASA and the USAF while designing and building the simulator for future vision research. We also describe the critically important relationship of the physical display components including distortion correction for the dome consistent with an objective of minimizing latency in the system. The performance of the automatic calibration system used in the dome is also described. Various recommendations for possible future implementations shall also be discussed.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

PubMed

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

Research on three-dimensional reconstruction method based on binocular vision

NASA Astrophysics Data System (ADS)

Li, Jinlin; Wang, Zhihui; Wang, Minjun

2018-03-01

As the hot and difficult issue in computer vision, binocular stereo vision is an important form of computer vision,which has a broad application prospects in many computer vision fields,such as aerial mapping,vision navigation,motion analysis and industrial inspection etc.In this paper, a research is done into binocular stereo camera calibration, image feature extraction and stereo matching. In the binocular stereo camera calibration module, the internal parameters of a single camera are obtained by using the checkerboard lattice of zhang zhengyou the field of image feature extraction and stereo matching, adopted the SURF operator in the local feature operator and the SGBM algorithm in the global matching algorithm are used respectively, and the performance are compared. After completed the feature points matching, we can build the corresponding between matching points and the 3D object points using the camera parameters which are calibrated, which means the 3D information.

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Classification of Normal and Pathological Gait in Young Children Based on Foot Pressure Data.

PubMed

Guo, Guodong; Guffey, Keegan; Chen, Wenbin; Pergami, Paola

2017-01-01

Human gait recognition, an active research topic in computer vision, is generally based on data obtained from images/videos. We applied computer vision technology to classify pathology-related changes in gait in young children using a foot-pressure database collected using the GAITRite walkway system. As foot positioning changes with children's development, we also investigated the possibility of age estimation based on this data. Our results demonstrate that the data collected by the GAITRite system can be used for normal/pathological gait classification. Combining age information and normal/pathological gait classification increases the accuracy of the classifier. This novel approach could support the development of an accurate, real-time, and economic measure of gait abnormalities in children, able to provide important feedback to clinicians regarding the effect of rehabilitation interventions, and to support targeted treatment modifications.

Proteus: a reconfigurable computational network for computer vision

NASA Astrophysics Data System (ADS)

Haralick, Robert M.; Somani, Arun K.; Wittenbrink, Craig M.; Johnson, Robert; Cooper, Kenneth; Shapiro, Linda G.; Phillips, Ihsin T.; Hwang, Jenq N.; Cheung, William; Yao, Yung H.; Chen, Chung-Ho; Yang, Larry; Daugherty, Brian; Lorbeski, Bob; Loving, Kent; Miller, Tom; Parkins, Larye; Soos, Steven L.

1992-04-01

The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

An automated miniaturized Haploscope for testing binocular visual function

NASA Technical Reports Server (NTRS)

Decker, T. A.; Williams, R. E.; Kuether, C. L.; Wyman-Cornsweet, D.

1976-01-01

A computer-controlled binocular vision testing device has been developed as one part of a system designed for NASA to test the vision of astronauts during spaceflight. The device, called the Mark III Haploscope, utilizes semi-automated psychophysical test procedures to measure visual acuity, stereopsis, phorias, fixation disparity and accommodation/convergence relationships. All tests are self-administered, yield quantitative data and may be used repeatedly without subject memorization. Future applications of this programmable, compact device include its use as a clinical instrument to perform routine eye examinations or vision screening, and as a research tool to examine the effects of environment or work-cycle upon visual function.

A clinical information systems strategy for a large integrated delivery network.

PubMed Central

Kuperman, G. J.; Spurr, C.; Flammini, S.; Bates, D.; Glaser, J.

2000-01-01

Integrated delivery networks (IDNs) are an emerging class of health care institutions. IDNs are formed from the affiliation of individual health care institutions and are intended to be more efficient in the current fiscal health care environment. To realize efficiencies and support their strategic visions, IDNs rely critically on excellent information technology (IT). Because of its importance to the mission of the IDN, strategic decisions about IT are made by the top leadership of the IDN. At Partners HealthCare System, a large IDN in Boston, MA, a clinical information systems strategy has been created to support the Partners clinical vision. In this paper, we discuss the Partners' structure, clinical vision, and current IT initiatives in place to address the clinical vision. The initiatives are: a clinical data repository, inpatient process support, electronic medical records, a portal strategy, referral applications, knowledge resources, support for product lines, patient computing, confidentiality, and clinical decision support. We address several of the issues encountered in trying to bring excellent information technology to a large IDN. PMID:11079921

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

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

Gas flow parameters in laser cutting of wood- nozzle design

Treesearch

Kali Mukherjee; Tom Grendzwell; Parwaiz A.A. Khan; Charles McMillin

1990-01-01

The Automated Lumber Processing System (ALPS) is an ongoing team research effort to optimize the yield of parts in a furniture rough mill. The process is designed to couple aspects of computer vision, computer optimization of yield, and laser cutting. This research is focused on optimizing laser wood cutting. Laser machining of lumber has the advantage over...

The Use of Spatialized Speech in Auditory Interfaces for Computer Users Who Are Visually Impaired

ERIC Educational Resources Information Center

Sodnik, Jaka; Jakus, Grega; Tomazic, Saso

2012-01-01

Introduction: This article reports on a study that explored the benefits and drawbacks of using spatially positioned synthesized speech in auditory interfaces for computer users who are visually impaired (that is, are blind or have low vision). The study was a practical application of such systems--an enhanced word processing application compared…

Computer vision-based analysis of foods: a non-destructive colour measurement tool to monitor quality and safety.

PubMed

Mogol, Burçe Ataç; Gökmen, Vural

2014-05-01

Computer vision-based image analysis has been widely used in food industry to monitor food quality. It allows low-cost and non-contact measurements of colour to be performed. In this paper, two computer vision-based image analysis approaches are discussed to extract mean colour or featured colour information from the digital images of foods. These types of information may be of particular importance as colour indicates certain chemical changes or physical properties in foods. As exemplified here, the mean CIE a* value or browning ratio determined by means of computer vision-based image analysis algorithms can be correlated with acrylamide content of potato chips or cookies. Or, porosity index as an important physical property of breadcrumb can be calculated easily. In this respect, computer vision-based image analysis provides a useful tool for automatic inspection of food products in a manufacturing line, and it can be actively involved in the decision-making process where rapid quality/safety evaluation is needed. © 2013 Society of Chemical Industry.

The Health Improvement Network (THIN)

Cancer.gov

The Health Improvement Network is a collaboration between Cegedim Strategic Data EPIC, an expert in the provision of UK primary care patient data that is used for medical research, and In Practice Systems (InPS), who continue to develop and supply the widely-used Vision general practice computer system.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jha, Sumit Kumar; Pullum, Laura L; Ramanathan, Arvind

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 studyingmore » 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.« less

Ubiquitous computing technology for just-in-time motivation of behavior change.

PubMed

Intille, Stephen S

2004-01-01

This paper describes a vision of health care where "just-in-time" user interfaces are used to transform people from passive to active consumers of health care. Systems that use computational pattern recognition to detect points of decision, behavior, or consequences automatically can present motivational messages to encourage healthy behavior at just the right time. Further, new ubiquitous computing and mobile computing devices permit information to be conveyed to users at just the right place. In combination, computer systems that present messages at the right time and place can be developed to motivate physical activity and healthy eating. Computational sensing technologies can also be used to measure the impact of the motivational technology on behavior.

Edge detection

NASA Astrophysics Data System (ADS)

Hildreth, E. C.

1985-09-01

For both biological systems and machines, vision begins with a large and unwieldly array of measurements of the amount of light reflected from surfaces in the environment. The goal of vision is to recover physical properties of objects in the scene such as the location of object boundaries and the structure, color and texture of object surfaces, from the two-dimensional image that is projected onto the eye or camera. This goal is not achieved in a single step: vision proceeds in stages, with each stage producing increasingly more useful descriptions of the image and then the scene. The first clues about the physical properties of the scene are provided by the changes of intensity in the image. The importance of intensity changes and edges in early visual processing has led to extensive research on their detection, description and use, both in computer and biological vision systems. This article reviews some of the theory that underlies the detection of edges, and the methods used to carry out this analysis.

Job-shop scheduling applied to computer vision

NASA Astrophysics Data System (ADS)

Sebastian y Zuniga, Jose M.; Torres-Medina, Fernando; Aracil, Rafael; Reinoso, Oscar; Jimenez, Luis M.; Garcia, David

1997-09-01

This paper presents a method for minimizing the total elapsed time spent by n tasks running on m differents processors working in parallel. The developed algorithm not only minimizes the total elapsed time but also reduces the idle time and waiting time of in-process tasks. This condition is very important in some applications of computer vision in which the time to finish the total process is particularly critical -- quality control in industrial inspection, real- time computer vision, guided robots. The scheduling algorithm is based on the use of two matrices, obtained from the precedence relationships between tasks, and the data obtained from the two matrices. The developed scheduling algorithm has been tested in one application of quality control using computer vision. The results obtained have been satisfactory in the application of different image processing algorithms.

Creating photorealistic virtual model with polarization-based vision system

NASA Astrophysics Data System (ADS)

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

2005-08-01

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

Development of a Stereo Vision Measurement System for a 3D Three-Axial Pneumatic Parallel Mechanism Robot Arm

PubMed Central

Chiang, Mao-Hsiung; Lin, Hao-Ting; Hou, Chien-Lun

2011-01-01

In this paper, a stereo vision 3D position measurement system for a three-axial pneumatic parallel mechanism robot arm is presented. The stereo vision 3D position measurement system aims to measure the 3D trajectories of the end-effector of the robot arm. To track the end-effector of the robot arm, the circle detection algorithm is used to detect the desired target and the SAD algorithm is used to track the moving target and to search the corresponding target location along the conjugate epipolar line in the stereo pair. After camera calibration, both intrinsic and extrinsic parameters of the stereo rig can be obtained, so images can be rectified according to the camera parameters. Thus, through the epipolar rectification, the stereo matching process is reduced to a horizontal search along the conjugate epipolar line. Finally, 3D trajectories of the end-effector are computed by stereo triangulation. The experimental results show that the stereo vision 3D position measurement system proposed in this paper can successfully track and measure the fifth-order polynomial trajectory and sinusoidal trajectory of the end-effector of the three- axial pneumatic parallel mechanism robot arm. PMID:22319408

Monocular Stereo Measurement Using High-Speed Catadioptric Tracking

PubMed Central

Hu, Shaopeng; Matsumoto, Yuji; Takaki, Takeshi; Ishii, Idaku

2017-01-01

This paper presents a novel concept of real-time catadioptric stereo tracking using a single ultrafast mirror-drive pan-tilt active vision system that can simultaneously switch between hundreds of different views in a second. By accelerating video-shooting, computation, and actuation at the millisecond-granularity level for time-division multithreaded processing in ultrafast gaze control, the active vision system can function virtually as two or more tracking cameras with different views. It enables a single active vision system to act as virtual left and right pan-tilt cameras that can simultaneously shoot a pair of stereo images for the same object to be observed at arbitrary viewpoints by switching the direction of the mirrors of the active vision system frame by frame. We developed a monocular galvano-mirror-based stereo tracking system that can switch between 500 different views in a second, and it functions as a catadioptric active stereo with left and right pan-tilt tracking cameras that can virtually capture 8-bit color 512×512 images each operating at 250 fps to mechanically track a fast-moving object with a sufficient parallax for accurate 3D measurement. Several tracking experiments for moving objects in 3D space are described to demonstrate the performance of our monocular stereo tracking system. PMID:28792483

Advanced flight computers for planetary exploration

NASA Technical Reports Server (NTRS)

Stephenson, R. Rhoads

1988-01-01

Research concerning flight computers for use on interplanetary probes is reviewed. The history of these computers from the Viking mission to the present is outlined. The differences between ground commercial computers and computers for planetary exploration are listed. The development of a computer for the Mariner Mark II comet rendezvous asteroid flyby mission is described. Various aspects of recently developed computer systems are examined, including the Max real time, embedded computer, a hypercube distributed supercomputer, a SAR data processor, a processor for the High Resolution IR Imaging Spectrometer, and a robotic vision multiresolution pyramid machine for processsing images obtained by a Mars Rover.

Real time AI expert system for robotic applications

NASA Technical Reports Server (NTRS)

Follin, John F.

1987-01-01

A computer controlled multi-robot process cell to demonstrate advanced technologies for the demilitarization of obsolete chemical munitions was developed. The methods through which the vision system and other sensory inputs were used by the artificial intelligence to provide the information required to direct the robots to complete the desired task are discussed. The mechanisms that the expert system uses to solve problems (goals), the different rule data base, and the methods for adapting this control system to any device that can be controlled or programmed through a high level computer interface are discussed.

Enhanced computer vision with Microsoft Kinect sensor: a review.

PubMed

Han, Jungong; Shao, Ling; Xu, Dong; Shotton, Jamie

2013-10-01

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Chen, Alexander Y. K.

1991-01-01

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.

Texture and art with deep neural networks.

PubMed

Gatys, Leon A; Ecker, Alexander S; Bethge, Matthias

2017-10-01

Although the study of biological vision and computer vision attempt to understand powerful visual information processing from different angles, they have a long history of informing each other. Recent advances in texture synthesis that were motivated by visual neuroscience have led to a substantial advance in image synthesis and manipulation in computer vision using convolutional neural networks (CNNs). Here, we review these recent advances and discuss how they can in turn inspire new research in visual perception and computational neuroscience. Copyright © 2017. Published by Elsevier Ltd.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications.

PubMed

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-09-14

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments.

Pose Self-Calibration of Stereo Vision Systems for Autonomous Vehicle Applications

PubMed Central

Musleh, Basam; Martín, David; Armingol, José María; de la Escalera, Arturo

2016-01-01

Nowadays, intelligent systems applied to vehicles have grown very rapidly; their goal is not only the improvement of safety, but also making autonomous driving possible. Many of these intelligent systems are based on making use of computer vision in order to know the environment and act accordingly. It is of great importance to be able to estimate the pose of the vision system because the measurement matching between the perception system (pixels) and the vehicle environment (meters) depends on the relative position between the perception system and the environment. A new method of camera pose estimation for stereo systems is presented in this paper, whose main contribution regarding the state of the art on the subject is the estimation of the pitch angle without being affected by the roll angle. The validation of the self-calibration method is accomplished by comparing it with relevant methods of camera pose estimation, where a synthetic sequence is used in order to measure the continuous error with a ground truth. This validation is enriched by the experimental results of the method in real traffic environments. PMID:27649178

Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models

PubMed Central

Azzopardi, George; Petkov, Nicolai

2014-01-01

The remarkable abilities of the primate visual system have inspired the construction of computational models of some visual neurons. We propose a trainable hierarchical object recognition model, which we call S-COSFIRE (S stands for Shape and COSFIRE stands for Combination Of Shifted FIlter REsponses) and use it to localize and recognize objects of interests embedded in complex scenes. It is inspired by the visual processing in the ventral stream (V1/V2 → V4 → TEO). Recognition and localization of objects embedded in complex scenes is important for many computer vision applications. Most existing methods require prior segmentation of the objects from the background which on its turn requires recognition. An S-COSFIRE filter is automatically configured to be selective for an arrangement of contour-based features that belong to a prototype shape specified by an example. The configuration comprises selecting relevant vertex detectors and determining certain blur and shift parameters. The response is computed as the weighted geometric mean of the blurred and shifted responses of the selected vertex detectors. S-COSFIRE filters share similar properties with some neurons in inferotemporal cortex, which provided inspiration for this work. We demonstrate the effectiveness of S-COSFIRE filters in two applications: letter and keyword spotting in handwritten manuscripts and object spotting in complex scenes for the computer vision system of a domestic robot. S-COSFIRE filters are effective to recognize and localize (deformable) objects in images of complex scenes without requiring prior segmentation. They are versatile trainable shape detectors, conceptually simple and easy to implement. The presented hierarchical shape representation contributes to a better understanding of the brain and to more robust computer vision algorithms. PMID:25126068

An Omnidirectional Vision Sensor Based on a Spherical Mirror Catadioptric System.

PubMed

Barone, Sandro; Carulli, Marina; Neri, Paolo; Paoli, Alessandro; Razionale, Armando Viviano

2018-01-31

The combination of mirrors and lenses, which defines a catadioptric sensor, is widely used in the computer vision field. The definition of a catadioptric sensors is based on three main features: hardware setup, projection modelling and calibration process. In this paper, a complete description of these aspects is given for an omnidirectional sensor based on a spherical mirror. The projection model of a catadioptric system can be described by the forward projection task (FP, from 3D scene point to 2D pixel coordinates) and backward projection task (BP, from 2D coordinates to 3D direction of the incident light). The forward projection of non-central catadioptric vision systems, typically obtained by using curved mirrors, is usually modelled by using a central approximation and/or by adopting iterative approaches. In this paper, an analytical closed-form solution to compute both forward and backward projection for a non-central catadioptric system with a spherical mirror is presented. In particular, the forward projection is reduced to a 4th order polynomial by determining the reflection point on the mirror surface through the intersection between a sphere and an ellipse. A matrix format of the implemented models, suitable for fast point clouds handling, is also described. A robust calibration procedure is also proposed and applied to calibrate a catadioptric sensor by determining the mirror radius and center with respect to the camera.

An Omnidirectional Vision Sensor Based on a Spherical Mirror Catadioptric System

PubMed Central

Barone, Sandro; Carulli, Marina; Razionale, Armando Viviano

2018-01-01

The combination of mirrors and lenses, which defines a catadioptric sensor, is widely used in the computer vision field. The definition of a catadioptric sensors is based on three main features: hardware setup, projection modelling and calibration process. In this paper, a complete description of these aspects is given for an omnidirectional sensor based on a spherical mirror. The projection model of a catadioptric system can be described by the forward projection task (FP, from 3D scene point to 2D pixel coordinates) and backward projection task (BP, from 2D coordinates to 3D direction of the incident light). The forward projection of non-central catadioptric vision systems, typically obtained by using curved mirrors, is usually modelled by using a central approximation and/or by adopting iterative approaches. In this paper, an analytical closed-form solution to compute both forward and backward projection for a non-central catadioptric system with a spherical mirror is presented. In particular, the forward projection is reduced to a 4th order polynomial by determining the reflection point on the mirror surface through the intersection between a sphere and an ellipse. A matrix format of the implemented models, suitable for fast point clouds handling, is also described. A robust calibration procedure is also proposed and applied to calibrate a catadioptric sensor by determining the mirror radius and center with respect to the camera. PMID:29385051

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Visual tracking strategies for intelligent vehicle highway systems

NASA Astrophysics Data System (ADS)

Smith, Christopher E.; Papanikolopoulos, Nikolaos P.; Brandt, Scott A.; Richards, Charles

1995-01-01

The complexity and congestion of current transportation systems often produce traffic situations that jeopardize the safety of the people involved. These situations vary from maintaining a safe distance behind a leading vehicle to safely allowing a pedestrian to cross a busy street. Environmental sensing plays a critical role in virtually all of these situations. Of the sensors available, vision sensors provide information that is richer and more complete than other sensors, making them a logical choice for a multisensor transportation system. In this paper we present robust techniques for intelligent vehicle-highway applications where computer vision plays a crucial role. In particular, we demonstrate that the controlled active vision framework can be utilized to provide a visual sensing modality to a traffic advisory system in order to increase the overall safety margin in a variety of common traffic situations. We have selected two application examples, vehicle tracking and pedestrian tracking, to demonstrate that the framework can provide precisely the type of information required to effectively manage the given situation.

Impact of computer use on children's vision.

PubMed

Kozeis, N

2009-10-01

Today, millions of children use computers on a daily basis. Extensive viewing of the computer screen can lead to eye discomfort, fatigue, blurred vision and headaches, dry eyes and other symptoms of eyestrain. These symptoms may be caused by poor lighting, glare, an improper work station set-up, vision problems of which the person was not previously aware, or a combination of these factors. Children can experience many of the same symptoms related to computer use as adults. However, some unique aspects of how children use computers may make them more susceptible than adults to the development of these problems. In this study, the most common eye symptoms related to computer use in childhood, the possible causes and ways to avoid them are reviewed.

Developing the Vision: Preparing Teachers to Deliver a Digital World-Class Education System

ERIC Educational Resources Information Center

Lane, Jenny M.

2012-01-01

In 2008 Australians were promised a "Digital Education Revolution" by the government to dramatically change classroom education and build a "world-class education system". Eight billion dollars have been spent providing computer equipment for upper secondary classrooms, yet there is little evidence that a revolution has…

Computational Unification: a Vision for Connecting Researchers

NASA Astrophysics Data System (ADS)

Troy, R. M.; Kingrey, O. J.

2002-12-01

Computational Unification of science, once only a vision, is becoming a reality. This technology is based upon a scientifically defensible, general solution for Earth Science data management and processing. The computational unification of science offers a real opportunity to foster inter and intra-discipline cooperation, and the end of 're-inventing the wheel'. As we move forward using computers as tools, it is past time to move from computationally isolating, "one-off" or discipline-specific solutions into a unified framework where research can be more easily shared, especially with researchers in other disciplines. The author will discuss how distributed meta-data, distributed processing and distributed data objects are structured to constitute a working interdisciplinary system, including how these resources lead to scientific defensibility through known lineage of all data products. Illustration of how scientific processes are encapsulated and executed illuminates how previously written processes and functions are integrated into the system efficiently and with minimal effort. Meta-data basics will illustrate how intricate relationships may easily be represented and used to good advantage. Retrieval techniques will be discussed including trade-offs of using meta-data versus embedded data, how the two may be integrated, and how simplifying assumptions may or may not help. This system is based upon the experience of the Sequoia 2000 and BigSur research projects at the University of California, Berkeley, whose goals were to find an alternative to the Hughes EOS-DIS system and is presently offered by Science Tools corporation, of which the author is a principal.

Development of a mobile robot for the 1995 AUVS competition

NASA Astrophysics Data System (ADS)

Matthews, Bradley O.; Ruthemeyer, Michael A.; Perdue, David; Hall, Ernest L.

1995-12-01

Automated guided vehicles (AGVs) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The advantages of a modular system are related to portability and the fact that any vehicle can become autonomous with minimal modifications. A mobile robot test-bed has been constructed using a golf cart base. This cart has full speed control with guidance provided by a vision system and obstacle avoidance using ultrasonic sensors systems. The speed and steering control are supervised by a 486 computer through a 3-axis motion controller. The obstacle avoidance system is based on a micro-controller interfaced with six ultrasonic transducers. The is micro-controller independently handles all timing and distance calculations and sends a steering angle correction back to the computer via the serial line. This design yields a portable independent system, where even computer communication is not necessary. Vision guidance is accomplished with a CCD camera with a zoom lens. The data is collected through a commercial tracking device, communicating with the computer the X,Y coordinates of the lane marker. Testing of these systems yielded positive results by showing that at five mph the vehicle can follow a line and at the same time avoid obstacles. This design, in its modularity, creates a portable autonomous controller applicable for any mobile vehicle with only minor adaptations.

Vision-Aided Inertial Navigation

NASA Technical Reports Server (NTRS)

Roumeliotis, Stergios I. (Inventor); Mourikis, Anastasios I. (Inventor)

2017-01-01

This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.

Development of Moire machine vision

NASA Technical Reports Server (NTRS)

Harding, Kevin G.

1987-01-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

NASA Technical Reports Server (NTRS)

Almeida, Eduardo DeBrito

2012-01-01

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

Development of Moire machine vision

NASA Astrophysics Data System (ADS)

Harding, Kevin G.

1987-10-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

Gradual cut detection using low-level vision for digital video

NASA Astrophysics Data System (ADS)

Lee, Jae-Hyun; Choi, Yeun-Sung; Jang, Ok-bae

1996-09-01

Digital video computing and organization is one of the important issues in multimedia system, signal compression, or database. Video should be segmented into shots to be used for identification and indexing. This approach requires a suitable method to automatically locate cut points in order to separate shot in a video. Automatic cut detection to isolate shots in a video has received considerable attention due to many practical applications; our video database, browsing, authoring system, retrieval and movie. Previous studies are based on a set of difference mechanisms and they measured the content changes between video frames. But they could not detect more special effects which include dissolve, wipe, fade-in, fade-out, and structured flashing. In this paper, a new cut detection method for gradual transition based on computer vision techniques is proposed. And then, experimental results applied to commercial video are presented and evaluated.

Neo-Symbiosis: The Next Stage in the Evolution of Human Information Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Griffith, Douglas; Greitzer, Frank L.

We re-address the vision of human-computer symbiosis expressed by J. C. R. Licklider nearly a half-century ago, when he wrote: “The hope is that in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” (Licklider, 1960). Unfortunately, little progress was made toward this vision over four decades following Licklider’s challenge, despite significant advancements in the fields of human factors and computer science. Licklider’s vision wasmore » largely forgotten. However, recent advances in information science and technology, psychology, and neuroscience have rekindled the potential of making the Licklider’s vision a reality. This paper provides a historical context for and updates the vision, and it argues that such a vision is needed as a unifying framework for advancing IS&T.« less

Development of a Configurable Growth Chamber with a Computer Vision System to Study Circadian Rhythm in Plants

PubMed Central

Navarro, Pedro J.; Fernández, Carlos; Weiss, Julia; Egea-Cortines, Marcos

2012-01-01

Plant development is the result of an endogenous morphogenetic program that integrates environmental signals. The so-called circadian clock is a set of genes that integrates environmental inputs into an internal pacing system that gates growth and other outputs. Study of circadian growth responses requires high sampling rates to detect changes in growth and avoid aliasing. We have developed a flexible configurable growth chamber comprising a computer vision system that allows sampling rates ranging between one image per 30 s to hours/days. The vision system has a controlled illumination system, which allows the user to set up different configurations. The illumination system used emits a combination of wavelengths ensuring the optimal growth of species under analysis. In order to obtain high contrast of captured images, the capture system is composed of two CCD cameras, for day and night periods. Depending on the sample type, a flexible image processing software calculates different parameters based on geometric calculations. As a proof of concept we tested the system in three different plant tissues, growth of petunia- and snapdragon (Antirrhinum majus) flowers and of cladodes from the cactus Opuntia ficus-indica. We found that petunia flowers grow at a steady pace and display a strong growth increase in the early morning, whereas Opuntia cladode growth turned out not to follow a circadian growth pattern under the growth conditions imposed. Furthermore we were able to identify a decoupling of increase in area and length indicating that two independent growth processes are responsible for the final size and shape of the cladode. PMID:23202214

Automated detection and classification of dice

NASA Astrophysics Data System (ADS)

Correia, Bento A. B.; Silva, Jeronimo A.; Carvalho, Fernando D.; Guilherme, Rui; Rodrigues, Fernando C.; de Silva Ferreira, Antonio M.

1995-03-01

This paper describes a typical machine vision system in an unusual application, the automated visual inspection of a Casino's playing tables. The SORTE computer vision system was developed at INETI under a contract with the Portuguese Gaming Inspection Authorities IGJ. It aims to automate the tasks of detection and classification of the dice's scores on the playing tables of the game `Banca Francesa' (which means French Banking) in Casinos. The system is based on the on-line analysis of the images captured by a monochrome CCD camera placed over the playing tables, in order to extract relevant information concerning the score indicated by the dice. Image processing algorithms for real time automatic throwing detection and dice classification were developed and implemented.

Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification.

PubMed

Unger, Jakob; Merhof, Dorit; Renner, Susanne

2016-11-16

Global Plants, a collaborative between JSTOR and some 300 herbaria, now contains about 2.48 million high-resolution images of plant specimens, a number that continues to grow, and collections that are digitizing their specimens at high resolution are allocating considerable recourses to the maintenance of computer hardware (e.g., servers) and to acquiring digital storage space. We here apply machine learning, specifically the training of a Support-Vector-Machine, to classify specimen images into categories, ideally at the species level, using the 26 most common tree species in Germany as a test case. We designed an analysis pipeline and classification system consisting of segmentation, normalization, feature extraction, and classification steps and evaluated the system in two test sets, one with 26 species, the other with 17, in each case using 10 images per species of plants collected between 1820 and 1995, which simulates the empirical situation that most named species are represented in herbaria and databases, such as JSTOR, by few specimens. We achieved 73.21% accuracy of species assignments in the larger test set, and 84.88% in the smaller test set. The results of this first application of a computer vision algorithm trained on images of herbarium specimens shows that despite the problem of overlapping leaves, leaf-architectural features can be used to categorize specimens to species with good accuracy. Computer vision is poised to play a significant role in future rapid identification at least for frequently collected genera or species in the European flora.

A computer vision system for diagnosing scoliosis using moiré images.

PubMed

Batouche, M; Benlamri, R; Kholladi, M K

1996-07-01

For young people, scoliosis deformities are an evolving process which must be detected and treated as early as possible. The moiré technique is simple, inexpensive, not aggressive and especially convenient for detecting spinal deformations. Doctors make their diagnosis by analysing the symmetry of fringes obtained by such techniques. In this paper, we present a computer vision system for help diagnosing spinal deformations using noisy moiré images of the human back. The approach adopted in this paper consists of extracting fringe contours from moiré images, then localizing some anatomical features (the spinal column, lumbar hollow and shoulder blades) which are crucial for 3D surface generation carried out using Mota's relaxation operator. Finally, rules furnished by doctors are used to derive the kind of spinal deformation and to yield the diagnosis. The proposed system has been tested on a set of noisy moiré images, and the experimental result have shown its robustness and reliability for the recognition of most scoliosis deformities.

USC orthogonal multiprocessor for image processing with neural networks

NASA Astrophysics Data System (ADS)

Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

1990-07-01

This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

CT Image Sequence Processing For Wood Defect Recognition

Treesearch

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

1991-01-01

The research reported in this paper explores a non-destructive testing application of x-ray computed tomography (CT) in the forest products industry. This application involves a computer vision system that uses CT to locate and identify internal defects in hardwood logs. The knowledge of log defects is critical in deciding whether to veneer or to saw up a log, and how...

Computer Vision Syndrome: Implications for the Occupational Health Nurse.

PubMed

Lurati, Ann Regina

2018-02-01

Computers and other digital devices are commonly used both in the workplace and during leisure time. Computer vision syndrome (CVS) is a new health-related condition that negatively affects workers. This article reviews the pathology of and interventions for CVS with implications for the occupational health nurse.

New design environment for defect detection in web inspection systems

NASA Astrophysics Data System (ADS)

Hajimowlana, S. Hossain; Muscedere, Roberto; Jullien, Graham A.; Roberts, James W.

1997-09-01

One of the aims of industrial machine vision is to develop computer and electronic systems destined to replace human vision in the process of quality control of industrial production. In this paper we discuss the development of a new design environment developed for real-time defect detection using reconfigurable FPGA and DSP processor mounted inside a DALSA programmable CCD camera. The FPGA is directly connected to the video data-stream and outputs data to a low bandwidth output bus. The system is targeted for web inspection but has the potential for broader application areas. We describe and show test results of the prototype system board, mounted inside a DALSA camera and discuss some of the algorithms currently simulated and implemented for web inspection applications.

A multidisciplinary approach to solving computer related vision problems.

PubMed

Long, Jennifer; Helland, Magne

2012-09-01

This paper proposes a multidisciplinary approach to solving computer related vision issues by including optometry as a part of the problem-solving team. Computer workstation design is increasing in complexity. There are at least ten different professions who contribute to workstation design or who provide advice to improve worker comfort, safety and efficiency. Optometrists have a role identifying and solving computer-related vision issues and in prescribing appropriate optical devices. However, it is possible that advice given by optometrists to improve visual comfort may conflict with other requirements and demands within the workplace. A multidisciplinary approach has been advocated for solving computer related vision issues. There are opportunities for optometrists to collaborate with ergonomists, who coordinate information from physical, cognitive and organisational disciplines to enact holistic solutions to problems. This paper proposes a model of collaboration and examples of successful partnerships at a number of professional levels including individual relationships between optometrists and ergonomists when they have mutual clients/patients, in undergraduate and postgraduate education and in research. There is also scope for dialogue between optometry and ergonomics professional associations. A multidisciplinary approach offers the opportunity to solve vision related computer issues in a cohesive, rather than fragmented way. Further exploration is required to understand the barriers to these professional relationships. © 2012 The College of Optometrists.

Directly Comparing Computer and Human Performance in Language Understanding and Visual Reasoning.

ERIC Educational Resources Information Center

Baker, Eva L.; And Others

Evaluation models are being developed for assessing artificial intelligence (AI) systems in terms of similar performance by groups of people. Natural language understanding and vision systems are the areas of concentration. In simplest terms, the goal is to norm a given natural language system's performance on a sample of people. The specific…

A Framework for People Re-Identification in Multi-Camera Surveillance Systems

ERIC Educational Resources Information Center

Ammar, Sirine; Zaghden, Nizar; Neji, Mahmoud

2017-01-01

People re-identification has been a very active research topic recently in computer vision. It is an important application in surveillance system with disjoint cameras. This paper is focused on the implementation of a human re-identification system. First the face of detected people is divided into three parts and some soft-biometric traits are…

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

PubMed

Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

2018-05-01

A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

1 kHz 2D Visual Motion Sensor Using 20 × 20 Silicon Retina Optical Sensor and DSP Microcontroller.

PubMed

Liu, Shih-Chii; Yang, MinHao; Steiner, Andreas; Moeckel, Rico; Delbruck, Tobi

2015-04-01

Optical flow sensors have been a long running theme in neuromorphic vision sensors which include circuits that implement the local background intensity adaptation mechanism seen in biological retinas. This paper reports a bio-inspired optical motion sensor aimed towards miniature robotic and aerial platforms. It combines a 20 × 20 continuous-time CMOS silicon retina vision sensor with a DSP microcontroller. The retina sensor has pixels that have local gain control and adapt to background lighting. The system allows the user to validate various motion algorithms without building dedicated custom solutions. Measurements are presented to show that the system can compute global 2D translational motion from complex natural scenes using one particular algorithm: the image interpolation algorithm (I2A). With this algorithm, the system can compute global translational motion vectors at a sample rate of 1 kHz, for speeds up to ±1000 pixels/s, using less than 5 k instruction cycles (12 instructions per pixel) per frame. At 1 kHz sample rate the DSP is 12% occupied with motion computation. The sensor is implemented as a 6 g PCB consuming 170 mW of power.

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

PubMed

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.

Evolution of attention mechanisms for early visual processing

NASA Astrophysics Data System (ADS)

Müller, Thomas; Knoll, Alois

2011-03-01

Early visual processing as a method to speed up computations on visual input data has long been discussed in the computer vision community. The general target of a such approaches is to filter nonrelevant information from the costly higher-level visual processing algorithms. By insertion of this additional filter layer the overall approach can be speeded up without actually changing the visual processing methodology. Being inspired by the layered architecture of the human visual processing apparatus, several approaches for early visual processing have been recently proposed. Most promising in this field is the extraction of a saliency map to determine regions of current attention in the visual field. Such saliency can be computed in a bottom-up manner, i.e. the theory claims that static regions of attention emerge from a certain color footprint, and dynamic regions of attention emerge from connected blobs of textures moving in a uniform way in the visual field. Top-down saliency effects are either unconscious through inherent mechanisms like inhibition-of-return, i.e. within a period of time the attention level paid to a certain region automatically decreases if the properties of that region do not change, or volitional through cognitive feedback, e.g. if an object moves consistently in the visual field. These bottom-up and top-down saliency effects have been implemented and evaluated in a previous computer vision system for the project JAST. In this paper an extension applying evolutionary processes is proposed. The prior vision system utilized multiple threads to analyze the regions of attention delivered from the early processing mechanism. Here, in addition, multiple saliency units are used to produce these regions of attention. All of these saliency units have different parameter-sets. The idea is to let the population of saliency units create regions of attention, then evaluate the results with cognitive feedback and finally apply the genetic mechanism: mutation and cloning of the best performers and extinction of the worst performers considering computation of regions of attention. A fitness function can be derived by evaluating, whether relevant objects are found in the regions created. It can be seen from various experiments, that the approach significantly speeds up visual processing, especially regarding robust ealtime object recognition, compared to an approach not using saliency based preprocessing. Furthermore, the evolutionary algorithm improves the overall performance of the preprocessing system in terms of quality, as the system automatically and autonomously tunes the saliency parameters. The computational overhead produced by periodical clone/delete/mutation operations can be handled well within the realtime constraints of the experimental computer vision system. Nevertheless, limitations apply whenever the visual field does not contain any significant saliency information for some time, but the population still tries to tune the parameters - overfitting avoids generalization in this case and the evolutionary process may be reset by manual intervention.

Telescience testbed experiments for biomedical studies: fertilization potential recording of amphibian eggs using tele-manipulation under stereoscopic vision.

PubMed

Watanabe, S; Tanaka, M; Wada, Y; Suzuki, H; Takagi, S; Mori, S; Fukai, K; Kanazawa, Y; Takagi, M; Hirakawa, K; Ogasawara, K; Tsumura, K; Ogawa, K; Matsumoto, K; Nagaoka, S; Suzuki, T; Shimura, D; Yamashita, M; Nishio, S

1994-07-01

The telescience testbed experiments were carried out to test and investigate the tele-manipulation techniques in the intracellular potential recording of amphibian eggs. Implementation of telescience testbed was set up in the two separated laboratories of the Tsukuba Space center of NASDA, which were connected by tele-communication links. Manipulators respective for a microelectrode and a sample stage of microscope were moved by computers, of which command signals were transmitted from a computer in a remote control room. The computer in the control room was operated by an investigator (PI) who controlled the movement of each manipulator remotely. A stereoscopic vision of the microscope image were prepared by using a head mounted display (HMD) and were indispensable to the intracellular single cell recording. The fertilization potential of amphibian eggs was successfully obtained through the remote operating system.

Navy CALS Vision. Draft 2.0. Volume 25

DOT National Transportation Integrated Search

1990-10-01

Computer-aided Acquisition and Logistic Support (CALS) is a joint initiative between industry and the Department of Defense (DoD) that is targeted at: (1) Improving designs for weapon systems; (2) Reducing both acquisition and logistic support costs ...

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

PubMed Central

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-01-01

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms. PMID:27240382

Computer programming for generating visual stimuli.

PubMed

Bukhari, Farhan; Kurylo, Daniel D

2008-02-01

Critical to vision research is the generation of visual displays with precise control over stimulus metrics. Generating stimuli often requires adapting commercial software or developing specialized software for specific research applications. In order to facilitate this process, we give here an overview that allows nonexpert users to generate and customize stimuli for vision research. We first give a review of relevant hardware and software considerations, to allow the selection of display hardware, operating system, programming language, and graphics packages most appropriate for specific research applications. We then describe the framework of a generic computer program that can be adapted for use with a broad range of experimental applications. Stimuli are generated in the context of trial events, allowing the display of text messages, the monitoring of subject responses and reaction times, and the inclusion of contingency algorithms. This approach allows direct control and management of computer-generated visual stimuli while utilizing the full capabilities of modern hardware and software systems. The flowchart and source code for the stimulus-generating program may be downloaded from www.psychonomic.org/archive.

Galaxy morphology - An unsupervised machine learning approach

NASA Astrophysics Data System (ADS)

Schutter, A.; Shamir, L.

2015-09-01

Structural properties poses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a network of similarities between galaxy morphological types, and automatically deduce a morphological sequence of galaxies. Application of the method to the EFIGI catalog show that the morphological scheme produced by the algorithm is largely in agreement with the De Vaucouleurs system, demonstrating the ability of computer vision and machine learning methods to automatically profile galaxy morphological sequences. The unsupervised analysis method is based on comprehensive computer vision techniques that compute the visual similarities between the different morphological types. Rather than relying on human cognition, the proposed system deduces the similarities between sets of galaxy images in an automatic manner, and is therefore not limited by the number of galaxies being analyzed. The source code of the method is publicly available, and the protocol of the experiment is included in the paper so that the experiment can be replicated, and the method can be used to analyze user-defined datasets of galaxy images.

Adaptive control for eye-gaze input system

NASA Astrophysics Data System (ADS)

Zhao, Qijie; Tu, Dawei; Yin, Hairong

2004-01-01

The characteristics of the vision-based human-computer interaction system have been analyzed, and the practical application and its limited factors at present time have also been mentioned. The information process methods have been put forward. In order to make the communication flexible and spontaneous, the algorithms to adaptive control of user"s head movement has been designed, and the events-based methods and object-oriented computer language is used to develop the system software, by experiment testing, we found that under given condition, these methods and algorithms can meet the need of the HCI.

3D-model building of the jaw impression

NASA Astrophysics Data System (ADS)

Ahmed, Moumen T.; Yamany, Sameh M.; Hemayed, Elsayed E.; Farag, Aly A.

1997-03-01

A novel approach is proposed to obtain a record of the patient's occlusion using computer vision. Data acquisition is obtained using intra-oral video cameras. The technique utilizes shape from shading to extract 3D information from 2D views of the jaw, and a novel technique for 3D data registration using genetic algorithms. The resulting 3D model can be used for diagnosis, treatment planning, and implant purposes. The overall purpose of this research is to develop a model-based vision system for orthodontics to replace traditional approaches. This system will be flexible, accurate, and will reduce the cost of orthodontic treatments.

The Mark 3 Haploscope

NASA Technical Reports Server (NTRS)

Decker, T. A.; Williams, R. E.; Kuether, C. L.; Logar, N. D.; Wyman-Cornsweet, D.

1975-01-01

A computer-operated binocular vision testing device was developed as one part of a system designed for NASA to evaluate the visual function of astronauts during spaceflight. This particular device, called the Mark 3 Haploscope, employs semi-automated psychophysical test procedures to measure visual acuity, stereopsis, phoria, fixation disparity, refractive state and accommodation/convergence relationships. Test procedures are self-administered and can be used repeatedly without subject memorization. The Haploscope was designed as one module of the complete NASA Vision Testing System. However, it is capable of stand-alone operation. Moreover, the compactness and portability of the Haploscope make possible its use in a broad variety of testing environments.

A fast 3-D object recognition algorithm for the vision system of a special-purpose dexterous manipulator

NASA Technical Reports Server (NTRS)

Hung, Stephen H. Y.

1989-01-01

A fast 3-D object recognition algorithm that can be used as a quick-look subsystem to the vision system for the Special-Purpose Dexterous Manipulator (SPDM) is described. Global features that can be easily computed from range data are used to characterize the images of a viewer-centered model of an object. This algorithm will speed up the processing by eliminating the low level processing whenever possible. It may identify the object, reject a set of bad data in the early stage, or create a better environment for a more powerful algorithm to carry the work further.

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

NASA Technical Reports Server (NTRS)

Williams, D. S.

1977-01-01

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

Comparative randomised active drug controlled clinical trial of a herbal eye drop in computer vision syndrome.

PubMed

Chatterjee, Pranab Kr; Bairagi, Debasis; Roy, Sudipta; Majumder, Nilay Kr; Paul, Ratish Ch; Bagchi, Sunil Ch

2005-07-01

A comparative double-blind placebo-controlled clinical trial of a herbal eye drop (itone) was conducted to find out its efficacy and safety in 120 patients with computer vision syndrome. Patients using computers for more than 3 hours continuously per day having symptoms of watering, redness, asthenia, irritation, foreign body sensation and signs of conjunctival hyperaemia, corneal filaments and mucus were studied. One hundred and twenty patients were randomly given either placebo, tears substitute (tears plus) or itone in identical vials with specific code number and were instructed to put one drop four times daily for 6 weeks. Subjective and objective assessments were done at bi-weekly intervals. In computer vision syndrome both subjective and objective improvements were noticed with itone drops. Itone drop was found significantly better than placebo (p<0.01) and almost identical results were observed with tears plus (difference was not statistically significant). Itone is considered to be a useful drug in computer vision syndrome.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia.

PubMed

Diamond, James; Anderson, Neil H; Bartels, Peter H; Montironi, Rodolfo; Hamilton, Peter W

2004-09-01

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at x 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 x 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

A cognitive approach to vision for a mobile robot

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Funk, Christopher; Lyons, Damian

2013-05-01

We describe a cognitive vision system for a mobile robot. This system works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion. These 3D models are embedded within an overall 3D model of the robot's environment. This approach turns the computer vision problem into a search problem, with the goal of constructing a physically realistic model of the entire environment. At each step, the vision system selects a point in the visual input to focus on. The distance, shape, texture and motion information are computed in a small region and used to build a mesh in a 3D virtual world. Background knowledge is used to extend this structure as appropriate, e.g. if a patch of wall is seen, it is hypothesized to be part of a large wall and the entire wall is created in the virtual world, or if part of an object is recognized, the whole object's mesh is retrieved from the library of objects and placed into the virtual world. The difference between the input from the real camera and from the virtual camera is compared using local Gaussians, creating an error mask that indicates the main differences between them. This is then used to select the next points to focus on. This approach permits us to use very expensive algorithms on small localities, thus generating very accurate models. It also is task-oriented, permitting the robot to use its knowledge about its task and goals to decide which parts of the environment need to be examined. The software components of this architecture include PhysX for the 3D virtual world, OpenCV and the Point Cloud Library for visual processing, and the Soar cognitive architecture, which controls the perceptual processing and robot planning. The hardware is a custom-built pan-tilt stereo color camera. We describe experiments using both static and moving objects.

Human performance models for computer-aided engineering

NASA Technical Reports Server (NTRS)

Elkind, Jerome I. (Editor); Card, Stuart K. (Editor); Hochberg, Julian (Editor); Huey, Beverly Messick (Editor)

1989-01-01

This report discusses a topic important to the field of computational human factors: models of human performance and their use in computer-based engineering facilities for the design of complex systems. It focuses on a particular human factors design problem -- the design of cockpit systems for advanced helicopters -- and on a particular aspect of human performance -- vision and related cognitive functions. By focusing in this way, the authors were able to address the selected topics in some depth and develop findings and recommendations that they believe have application to many other aspects of human performance and to other design domains.

Integrating Mobile Robotics and Vision with Undergraduate Computer Science

ERIC Educational Resources Information Center

Cielniak, G.; Bellotto, N.; Duckett, T.

2013-01-01

This paper describes the integration of robotics education into an undergraduate Computer Science curriculum. The proposed approach delivers mobile robotics as well as covering the closely related field of Computer Vision and is directly linked to the research conducted at the authors' institution. The paper describes the most relevant details of…

Computer Vision Assisted Virtual Reality Calibration

NASA Technical Reports Server (NTRS)

Kim, W.

1999-01-01

A computer vision assisted semi-automatic virtual reality (VR) calibration technology has been developed that can accurately match a virtual environment of graphically simulated three-dimensional (3-D) models to the video images of the real task environment.

Challenges and insights for situated language processing: Comment on "Towards a computational comparative neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

NASA Astrophysics Data System (ADS)

Knoeferle, Pia

2016-03-01

In his review article [19], Arbib outlines an ambitious research agenda: to accommodate within a unified framework the evolution, the development, and the processing of language in natural settings (implicating other systems such as vision). He does so with neuro-computationally explicit modeling in mind [1,2] and inspired by research on the mirror neuron system in primates. Similar research questions have received substantial attention also among other scientists [3,4,12].

Computer vision for driver assistance systems

NASA Astrophysics Data System (ADS)

Handmann, Uwe; Kalinke, Thomas; Tzomakas, Christos; Werner, Martin; von Seelen, Werner

1998-07-01

Systems for automated image analysis are useful for a variety of tasks and their importance is still increasing due to technological advances and an increase of social acceptance. Especially in the field of driver assistance systems the progress in science has reached a level of high performance. Fully or partly autonomously guided vehicles, particularly for road-based traffic, pose high demands on the development of reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We introduce a system which extracts the important information from an image taken by a CCD camera installed at the rear view mirror in a car. The approach consists of a sequential and a parallel sensor and information processing. Three main tasks namely the initial segmentation (object detection), the object tracking and the object classification are realized by integration in the sequential branch and by fusion in the parallel branch. The main gain of this approach is given by the integrative coupling of different algorithms providing partly redundant information.

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Portable real-time color night vision

NASA Astrophysics Data System (ADS)

Toet, Alexander; Hogervorst, Maarten A.

2008-03-01

We developed a simple and fast lookup-table based method to derive and apply natural daylight colors to multi-band night-time images. The method deploys an optimal color transformation derived from a set of samples taken from a daytime color reference image. The colors in the resulting colorized multiband night-time images closely resemble the colors in the daytime color reference image. Also, object colors remain invariant under panning operations and are independent of the scene content. Here we describe the implementation of this method in two prototype portable dual band realtime night vision systems. One system provides co-aligned visual and near-infrared bands of two image intensifiers, the other provides co-aligned images from a digital image intensifier and an uncooled longwave infrared microbolometer. The co-aligned images from both systems are further processed by a notebook computer. The color mapping is implemented as a realtime lookup table transform. The resulting colorised video streams can be displayed in realtime on head mounted displays and stored on the hard disk of the notebook computer. Preliminary field trials demonstrate the potential of these systems for applications like surveillance, navigation and target detection.

An egocentric vision based assistive co-robot.

PubMed

Zhang, Jingzhe; Zhuang, Lishuo; Wang, Yang; Zhou, Yameng; Meng, Yan; Hua, Gang

2013-06-01

We present the prototype of an egocentric vision based assistive co-robot system. In this co-robot system, the user is wearing a pair of glasses with a forward looking camera, and is actively engaged in the control loop of the robot in navigational tasks. The egocentric vision glasses serve for two purposes. First, it serves as a source of visual input to request the robot to find a certain object in the environment. Second, the motion patterns computed from the egocentric video associated with a specific set of head movements are exploited to guide the robot to find the object. These are especially helpful for quadriplegic individuals who do not have needed hand functionality for interaction and control with other modalities (e.g., joystick). In our co-robot system, when the robot does not fulfill the object finding task in a pre-specified time window, it would actively solicit user controls for guidance. Then the users can use the egocentric vision based gesture interface to orient the robot towards the direction of the object. After that the robot will automatically navigate towards the object until it finds it. Our experiments validated the efficacy of the closed-loop design to engage the human in the loop.

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

PubMed Central

Zhang, Xiang; Chen, Zhangwei

2013-01-01

This paper, proposes a novel solution for a stereo vision machine based on the System-on-Programmable-Chip (SoPC) architecture. The SOPC technology provides great convenience for accessing many hardware devices such as DDRII, SSRAM, Flash, etc., by IP reuse. The system hardware is implemented in a single FPGA chip involving a 32-bit Nios II microprocessor, which is a configurable soft IP core in charge of managing the image buffer and users' configuration data. The Sum of Absolute Differences (SAD) algorithm is used for dense disparity map computation. The circuits of the algorithmic module are modeled by the Matlab-based DSP Builder. With a set of configuration interfaces, the machine can process many different sizes of stereo pair images. The maximum image size is up to 512 K pixels. This machine is designed to focus on real time stereo vision applications. The stereo vision machine offers good performance and high efficiency in real time. Considering a hardware FPGA clock of 90 MHz, 23 frames of 640 × 480 disparity maps can be obtained in one second with 5 × 5 matching window and maximum 64 disparity pixels. PMID:23459385

High accuracy position method based on computer vision and error analysis

NASA Astrophysics Data System (ADS)

Chen, Shihao; Shi, Zhongke

2003-09-01

The study of high accuracy position system is becoming the hotspot in the field of autocontrol. And positioning is one of the most researched tasks in vision system. So we decide to solve the object locating by using the image processing method. This paper describes a new method of high accuracy positioning method through vision system. In the proposed method, an edge-detection filter is designed for a certain running condition. Here, the filter contains two mainly parts: one is image-processing module, this module is to implement edge detection, it contains of multi-level threshold self-adapting segmentation, edge-detection and edge filter; the other one is object-locating module, it is to point out the location of each object in high accurate, and it is made up of medium-filtering and curve-fitting. This paper gives some analysis error for the method to prove the feasibility of vision in position detecting. Finally, to verify the availability of the method, an example of positioning worktable, which is using the proposed method, is given at the end of the paper. Results show that the method can accurately detect the position of measured object and identify object attitude.

Optogenetics and computer vision for Caenorhabditis elegans neuroscience and other biophysical applications

NASA Astrophysics Data System (ADS)

Leifer, Andrew Michael

2011-07-01

This work presents optogenetics and real-time computer vision techniques to non-invasively manipulate and monitor neural activity with high spatiotemporal resolution in awake behaving Caenorhabditis elegans. These methods were employed to dissect the nematode's mechanosensory and motor circuits and to elucidate the neural control of wave propagation during forward locomotion. Additionally, similar computer vision methods were used to automatically detect and decode fluorescing DNA origami nanobarcodes, a new class of fluorescent reporter constructs. An optogenetic instrument capable of real-time light delivery with high spatiotemporal resolution to specified targets in freely moving C. elegans, the first such instrument of its kind, was developed. The instrument was used to probe the nematode's mechanosensory circuit, demonstrating that stimulation of a single mechanosensory neuron suffices to induce reversals. The instrument was also used to probe the motor circuit, demonstrating that inhibition of regions of cholinergic motor neurons blocks undulatory wave propagation and that muscle contractions can persist even without inputs from the motor neurons. The motor circuit was further probed using optogenetics and microfluidic techniques. Undulatory wave propagation during forward locomotion was observed to depend on stretch-sensitive signaling mediated by cholinergic motor neurons. Specifically, posterior body segments are compelled, through stretch-sensitive feedback, to bend in the same direction as anterior segments. This is the first explicit demonstration of such feedback and serves as a foundation for understanding motor circuits in other organisms. A real-time tracking system was developed to record intracellular calcium transients in single neurons while simultaneously monitoring macroscopic behavior of freely moving C. elegans. This was used to study the worm's stereotyped reversal behavior, the omega turn. Calcium transients corresponding to temporal features of the omega turn were observed in interneurons AVA and AVB. Optics and computer vision techniques similar to those developed for the C. elegans experiments were also used to detect DNA origami nanorod barcodes. An optimal Bayesian multiple hypothesis test was deployed to unambiguously classify each barcode as a member of one of 216 distinct barcode species. Overall, this set of experiments demonstrates the powerful role that optogenetics and computer vision can play in behavioral neuroscience and quantitative biophysics.

Stereo Image Ranging For An Autonomous Robot Vision System

NASA Astrophysics Data System (ADS)

Holten, James R.; Rogers, Steven K.; Kabrisky, Matthew; Cross, Steven

1985-12-01

The principles of stereo vision for three-dimensional data acquisition are well-known and can be applied to the problem of an autonomous robot vehicle. Coincidental points in the two images are located and then the location of that point in a three-dimensional space can be calculated using the offset of the points and knowledge of the camera positions and geometry. This research investigates the application of artificial intelligence knowledge representation techniques as a means to apply heuristics to relieve the computational intensity of the low level image processing tasks. Specifically a new technique for image feature extraction is presented. This technique, the Queen Victoria Algorithm, uses formal language productions to process the image and characterize its features. These characterized features are then used for stereo image feature registration to obtain the required ranging information. The results can be used by an autonomous robot vision system for environmental modeling and path finding.

PRoViScout: a planetary scouting rover demonstrator

NASA Astrophysics Data System (ADS)

Paar, Gerhard; Woods, Mark; Gimkiewicz, Christiane; Labrosse, Frédéric; Medina, Alberto; Tyler, Laurence; Barnes, David P.; Fritz, Gerald; Kapellos, Konstantinos

2012-01-01

Mobile systems exploring Planetary surfaces in future will require more autonomy than today. The EU FP7-SPACE Project ProViScout (2010-2012) establishes the building blocks of such autonomous exploration systems in terms of robotics vision by a decision-based combination of navigation and scientific target selection, and integrates them into a framework ready for and exposed to field demonstration. The PRoViScout on-board system consists of mission management components such as an Executive, a Mars Mission On-Board Planner and Scheduler, a Science Assessment Module, and Navigation & Vision Processing modules. The platform hardware consists of the rover with the sensors and pointing devices. We report on the major building blocks and their functions & interfaces, emphasizing on the computer vision parts such as image acquisition (using a novel zoomed 3D-Time-of-Flight & RGB camera), mapping from 3D-TOF data, panoramic image & stereo reconstruction, hazard and slope maps, visual odometry and the recognition of potential scientifically interesting targets.

Real-time tracking using stereo and motion: Visual perception for space robotics

NASA Technical Reports Server (NTRS)

Nishihara, H. Keith; Thomas, Hans; Huber, Eric; Reid, C. Ann

1994-01-01

The state-of-the-art in computing technology is rapidly attaining the performance necessary to implement many early vision algorithms at real-time rates. This new capability is helping to accelerate progress in vision research by improving our ability to evaluate the performance of algorithms in dynamic environments. In particular, we are becoming much more aware of the relative stability of various visual measurements in the presence of camera motion and system noise. This new processing speed is also allowing us to raise our sights toward accomplishing much higher-level processing tasks, such as figure-ground separation and active object tracking, in real-time. This paper describes a methodology for using early visual measurements to accomplish higher-level tasks; it then presents an overview of the high-speed accelerators developed at Teleos to support early visual measurements. The final section describes the successful deployment of a real-time vision system to provide visual perception for the Extravehicular Activity Helper/Retriever robotic system in tests aboard NASA's KC135 reduced gravity aircraft.

Toothguide Trainer tests with color vision deficiency simulation monitor.

PubMed

Borbély, Judit; Varsányi, Balázs; Fejérdy, Pál; Hermann, Péter; Jakstat, Holger A

2010-01-01

The aim of this study was to evaluate whether simulated severe red and green color vision deficiency (CVD) influenced color matching results and to investigate whether training with Toothguide Trainer (TT) computer program enabled better color matching results. A total of 31 color normal dental students participated in the study. Every participant had to pass the Ishihara Test. Participants with a red/green color vision deficiency were excluded. A lecture on tooth color matching was given, and individual training with TT was performed. To measure the individual tooth color matching results in normal and color deficient display modes, the TT final exam was displayed on a calibrated monitor that served as a hardware-based method of simulating protanopy and deuteranopy. Data from the TT final exams were collected in normal and in severe red and green CVD-simulating monitor display modes. Color difference values for each participant in each display mode were computed (∑ΔE(ab)(*)), and the respective means and standard deviations were calculated. The Student's t-test was used in statistical evaluation. Participants made larger ΔE(ab)(*) errors in severe color vision deficient display modes than in the normal monitor mode. TT tests showed significant (p<0.05) difference in the tooth color matching results of severe green color vision deficiency simulation mode compared to normal vision mode. Students' shade matching results were significantly better after training (p=0.009). Computer-simulated severe color vision deficiency mode resulted in significantly worse color matching quality compared to normal color vision mode. Toothguide Trainer computer program improved color matching results. Copyright © 2010 Elsevier Ltd. All rights reserved.

Technology Support for Discussion Based Learning: From Computer Supported Collaborative Learning to the Future of Massive Open Online Courses

ERIC Educational Resources Information Center

Rosé, Carolyn Penstein; Ferschke, Oliver

2016-01-01

This article offers a vision for technology supported collaborative and discussion-based learning at scale. It begins with historical work in the area of tutorial dialogue systems. It traces the history of that area of the field of Artificial Intelligence in Education as it has made an impact on the field of Computer-Supported Collaborative…

A Computer Vision System forLocating and Identifying Internal Log Defects Using CT Imagery

Treesearch

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

1991-01-01

A number of researchers have shown the ability of magnetic resonance imaging (MRI) and computer tomography (CT) imaging to detect internal defects in logs. However, if these devices are ever to play a role in the forest products industry, automatic methods for analyzing data from these devices must be developed. This paper reports research aimed at developing a...

Computer vision-based technologies and commercial best practices for the advancement of the motion imagery tradecraft

NASA Astrophysics Data System (ADS)

Phipps, Marja; Capel, David; Srinivasan, James

2014-06-01

Motion imagery capabilities within the Department of Defense/Intelligence Community (DoD/IC) have advanced significantly over the last decade, attempting to meet continuously growing data collection, video processing and analytical demands in operationally challenging environments. The motion imagery tradecraft has evolved accordingly, enabling teams of analysts to effectively exploit data and generate intelligence reports across multiple phases in structured Full Motion Video (FMV) Processing Exploitation and Dissemination (PED) cells. Yet now the operational requirements are drastically changing. The exponential growth in motion imagery data continues, but to this the community adds multi-INT data, interoperability with existing and emerging systems, expanded data access, nontraditional users, collaboration, automation, and support for ad hoc configurations beyond the current FMV PED cells. To break from the legacy system lifecycle, we look towards a technology application and commercial adoption model course which will meet these future Intelligence, Surveillance and Reconnaissance (ISR) challenges. In this paper, we explore the application of cutting edge computer vision technology to meet existing FMV PED shortfalls and address future capability gaps. For example, real-time georegistration services developed from computer-vision-based feature tracking, multiple-view geometry, and statistical methods allow the fusion of motion imagery with other georeferenced information sources - providing unparalleled situational awareness. We then describe how these motion imagery capabilities may be readily deployed in a dynamically integrated analytical environment; employing an extensible framework, leveraging scalable enterprise-wide infrastructure and following commercial best practices.

[Meibomian gland disfunction in computer vision syndrome].

PubMed

Pimenidi, M K; Polunin, G S; Safonova, T N

2010-01-01

This article reviews ethiology and pathogenesis of dry eye syndrome due to meibomian gland disfunction (MDG). It is showed that blink rate influences meibomian gland functioning and computer vision syndrome development. Current diagnosis and treatment options of MDG are presented.

A computer vision-based approach for structural displacement measurement

NASA Astrophysics Data System (ADS)

Ji, Yunfeng

2010-04-01

Along with the incessant advancement in optics, electronics and computer technologies during the last three decades, commercial digital video cameras have experienced a remarkable evolution, and can now be employed to measure complex motions of objects with sufficient accuracy, which render great assistance to structural displacement measurement in civil engineering. This paper proposes a computer vision-based approach for dynamic measurement of structures. One digital camera is used to capture image sequences of planar targets mounted on vibrating structures. The mathematical relationship between image plane and real space is established based on computer vision theory. Then, the structural dynamic displacement at the target locations can be quantified using point reconstruction rules. Compared with other tradition displacement measurement methods using sensors, such as accelerometers, linear-variable-differential-transducers (LVDTs) and global position system (GPS), the proposed approach gives the main advantages of great flexibility, a non-contact working mode and ease of increasing measurement points. To validate, four tests of sinusoidal motion of a point, free vibration of a cantilever beam, wind tunnel test of a cross-section bridge model, and field test of bridge displacement measurement, are performed. Results show that the proposed approach can attain excellent accuracy compared with the analytical ones or the measurements using conventional transducers, and proves to deliver an innovative and low cost solution to structural displacement measurement.

The Light Plane Calibration Method of the Laser Welding Vision Monitoring System

NASA Astrophysics Data System (ADS)

Wang, B. G.; Wu, M. H.; Jia, W. P.

2018-03-01

According to the aerospace and automobile industry, the sheet steels are the very important parts. In the recent years, laser welding technique had been used to weld the sheet steel part. The seam width between the two parts is usually less than 0.1mm. Because the error of the fixture fixed can’t be eliminated, the welding parts quality can be greatly affected. In order to improve the welding quality, the line structured light is employed in the vision monitoring system to plan the welding path before welding. In order to improve the weld precision, the vision system is located on Z axis of the computer numerical control (CNC) tool. The planar pattern is placed on the X-Y plane of the CNC tool, and the structured light is projected on the planar pattern. The vision system stay at three different positions along the Z axis of the CNC tool, and the camera shoot the image of the planar pattern at every position. Using the calculated the sub-pixel center line of the structure light, the world coordinate of the center light line can be calculated. Thus, the structured light plane can be calculated by fitting the structured light line. Experiment result shows the effective of the proposed method.

An on-line calibration algorithm for external parameters of visual system based on binocular stereo cameras

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Liu, Zhen; Zhang, Zhonghua

2014-11-01

Stereo vision is the key in the visual measurement, robot vision, and autonomous navigation. Before performing the system of stereo vision, it needs to calibrate the intrinsic parameters for each camera and the external parameters of the system. In engineering, the intrinsic parameters remain unchanged after calibrating cameras, and the positional relationship between the cameras could be changed because of vibration, knocks and pressures in the vicinity of the railway or motor workshops. Especially for large baselines, even minute changes in translation or rotation can affect the epipolar geometry and scene triangulation to such a degree that visual system becomes disabled. A technology including both real-time examination and on-line recalibration for the external parameters of stereo system becomes particularly important. This paper presents an on-line method for checking and recalibrating the positional relationship between stereo cameras. In epipolar geometry, the external parameters of cameras can be obtained by factorization of the fundamental matrix. Thus, it offers a method to calculate the external camera parameters without any special targets. If the intrinsic camera parameters are known, the external parameters of system can be calculated via a number of random matched points. The process is: (i) estimating the fundamental matrix via the feature point correspondences; (ii) computing the essential matrix from the fundamental matrix; (iii) obtaining the external parameters by decomposition of the essential matrix. In the step of computing the fundamental matrix, the traditional methods are sensitive to noise and cannot ensure the estimation accuracy. We consider the feature distribution situation in the actual scene images and introduce a regional weighted normalization algorithm to improve accuracy of the fundamental matrix estimation. In contrast to traditional algorithms, experiments on simulated data prove that the method improves estimation robustness and accuracy of the fundamental matrix. Finally, we take an experiment for computing the relationship of a pair of stereo cameras to demonstrate accurate performance of the algorithm.

An analog VLSI chip emulating polarization vision of Octopus retina.

PubMed

Momeni, Massoud; Titus, Albert H

2006-01-01

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

Integrated 3-D vision system for autonomous vehicles

NASA Astrophysics Data System (ADS)

Hou, Kun M.; Shawky, Mohamed; Tu, Xiaowei

1992-03-01

Nowadays, autonomous vehicles have become a multidiscipline field. Its evolution is taking advantage of the recent technological progress in computer architectures. As the development tools became more sophisticated, the trend is being more specialized, or even dedicated architectures. In this paper, we will focus our interest on a parallel vision subsystem integrated in the overall system architecture. The system modules work in parallel, communicating through a hierarchical blackboard, an extension of the 'tuple space' from LINDA concepts, where they may exchange data or synchronization messages. The general purpose processing elements are of different skills, built around 40 MHz i860 Intel RISC processors for high level processing and pipelined systolic array processors based on PLAs or FPGAs for low-level processing.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Optoelectronic instrumentation enhancement using data mining feedback for a 3D measurement system

NASA Astrophysics Data System (ADS)

Flores-Fuentes, Wendy; Sergiyenko, Oleg; Gonzalez-Navarro, Félix F.; Rivas-López, Moisés; Hernandez-Balbuena, Daniel; Rodríguez-Quiñonez, Julio C.; Tyrsa, Vera; Lindner, Lars

2016-12-01

3D measurement by a cyber-physical system based on optoelectronic scanning instrumentation has been enhanced by outliers and regression data mining feedback. The prototype has applications in (1) industrial manufacturing systems that include: robotic machinery, embedded vision, and motion control, (2) health care systems for measurement scanning, and (3) infrastructure by providing structural health monitoring. This paper presents new research performed in data processing of a 3D measurement vision sensing database. Outliers from multivariate data have been detected and removal to improve artificial intelligence regression algorithm results. Physical measurement error regression data has been used for 3D measurements error correction. Concluding, that the joint of physical phenomena, measurement and computation is an effectiveness action for feedback loops in the control of industrial, medical and civil tasks.

High-fidelity video and still-image communication based on spectral information: natural vision system and its applications

NASA Astrophysics Data System (ADS)

Yamaguchi, Masahiro; Haneishi, Hideaki; Fukuda, Hiroyuki; Kishimoto, Junko; Kanazawa, Hiroshi; Tsuchida, Masaru; Iwama, Ryo; Ohyama, Nagaaki

2006-01-01

In addition to the great advancement of high-resolution and large-screen imaging technology, the issue of color is now receiving considerable attention as another aspect than the image resolution. It is difficult to reproduce the original color of subject in conventional imaging systems, and that obstructs the applications of visual communication systems in telemedicine, electronic commerce, and digital museum. To breakthrough the limitation of conventional RGB 3-primary systems, "Natural Vision" project aims at an innovative video and still-image communication technology with high-fidelity color reproduction capability, based on spectral information. This paper summarizes the results of NV project including the development of multispectral and multiprimary imaging technologies and the experimental investigations on the applications to medicine, digital archives, electronic commerce, and computer graphics.

Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

PubMed

Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

2016-09-01

We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

Taming Crowded Visual Scenes

DTIC Science & Technology

2014-08-12

Nolan Warner, Mubarak Shah. Tracking in Dense Crowds Using Prominenceand Neighborhood Motion Concurrence, IEEE Transactions on Pattern Analysis...of  computer  vision,   computer   graphics  and  evacuation  dynamics  by  providing  a  common  platform,  and  provides...areas  that  includes  Computer  Vision,  Computer   Graphics ,  and  Pedestrian   Evacuation  Dynamics.  Despite  the

Computer vision syndrome: a review of ocular causes and potential treatments.

PubMed

Rosenfield, Mark

2011-09-01

Computer vision syndrome (CVS) is the combination of eye and vision problems associated with the use of computers. In modern western society the use of computers for both vocational and avocational activities is almost universal. However, CVS may have a significant impact not only on visual comfort but also occupational productivity since between 64% and 90% of computer users experience visual symptoms which may include eyestrain, headaches, ocular discomfort, dry eye, diplopia and blurred vision either at near or when looking into the distance after prolonged computer use. This paper reviews the principal ocular causes for this condition, namely oculomotor anomalies and dry eye. Accommodation and vergence responses to electronic screens appear to be similar to those found when viewing printed materials, whereas the prevalence of dry eye symptoms is greater during computer operation. The latter is probably due to a decrease in blink rate and blink amplitude, as well as increased corneal exposure resulting from the monitor frequently being positioned in primary gaze. However, the efficacy of proposed treatments to reduce symptoms of CVS is unproven. A better understanding of the physiology underlying CVS is critical to allow more accurate diagnosis and treatment. This will enable practitioners to optimize visual comfort and efficiency during computer operation. Ophthalmic & Physiological Optics © 2011 The College of Optometrists.

Effects of cortical damage on binocular depth perception.

PubMed

Bridge, Holly

2016-06-19

Stereoscopic depth perception requires considerable neural computation, including the initial correspondence of the two retinal images, comparison across the local regions of the visual field and integration with other cues to depth. The most common cause for loss of stereoscopic vision is amblyopia, in which one eye has failed to form an adequate input to the visual cortex, usually due to strabismus (deviating eye) or anisometropia. However, the significant cortical processing required to produce the percept of depth means that, even when the retinal input is intact from both eyes, brain damage or dysfunction can interfere with stereoscopic vision. In this review, I examine the evidence for impairment of binocular vision and depth perception that can result from insults to the brain, including both discrete damage, temporal lobectomy and more systemic diseases such as posterior cortical atrophy.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Authors.

Effects of cortical damage on binocular depth perception

PubMed Central

2016-01-01

Stereoscopic depth perception requires considerable neural computation, including the initial correspondence of the two retinal images, comparison across the local regions of the visual field and integration with other cues to depth. The most common cause for loss of stereoscopic vision is amblyopia, in which one eye has failed to form an adequate input to the visual cortex, usually due to strabismus (deviating eye) or anisometropia. However, the significant cortical processing required to produce the percept of depth means that, even when the retinal input is intact from both eyes, brain damage or dysfunction can interfere with stereoscopic vision. In this review, I examine the evidence for impairment of binocular vision and depth perception that can result from insults to the brain, including both discrete damage, temporal lobectomy and more systemic diseases such as posterior cortical atrophy. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269597

Colour, vision and coevolution in avian brood parasitism.

PubMed

Stoddard, Mary Caswell; Hauber, Mark E

2017-07-05

The coevolutionary interactions between avian brood parasites and their hosts provide a powerful system for investigating the diversity of animal coloration. Specifically, reciprocal selection pressure applied by hosts and brood parasites can give rise to novel forms and functions of animal coloration, which largely differ from those that arise when selection is imposed by predators or mates. In the study of animal colours, avian brood parasite-host dynamics therefore invite special consideration. Rapid advances across disciplines have paved the way for an integrative study of colour and vision in brood parasite-host systems. We now know that visually driven host defences and host life history have selected for a suite of phenotypic adaptations in parasites, including mimicry, crypsis and supernormal stimuli. This sometimes leads to vision-based host counter-adaptations and increased parasite trickery. Here, we review vision-based adaptations that arise in parasite-host interactions, emphasizing that these adaptations can be visual/sensory, cognitive or phenotypic in nature. We highlight recent breakthroughs in chemistry, genomics, neuroscience and computer vision, and we conclude by identifying important future directions. Moving forward, it will be essential to identify the genetic and neural bases of adaptation and to compare vision-based adaptations to those arising in other sensory modalities.This article is part of the themed issue 'Animal coloration: production, perception, function and application'. © 2017 The Author(s).

An Enduring Dialogue between Computational and Empirical Vision.

PubMed

Martinez-Conde, Susana; Macknik, Stephen L; Heeger, David J

2018-04-01

In the late 1970s, key discoveries in neurophysiology, psychophysics, computer vision, and image processing had reached a tipping point that would shape visual science for decades to come. David Marr and Ellen Hildreth's 'Theory of edge detection', published in 1980, set out to integrate the newly available wealth of data from behavioral, physiological, and computational approaches in a unifying theory. Although their work had wide and enduring ramifications, their most important contribution may have been to consolidate the foundations of the ongoing dialogue between theoretical and empirical vision science. Copyright © 2018 Elsevier Ltd. All rights reserved.

Towards an Autonomic Cluster Management System (ACMS) with Reflex Autonomicity

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Hinchey, Mike; Sterritt, Roy

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of providing a fault-tolerant environment and achieving significant computational capabilities for high-performance computing applications. However, the task of manually managing and configuring a cluster quickly becomes daunting as the cluster grows in size. Autonomic computing, with its vision to provide self-management, can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Autonomic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management and its evolution to include reflex reactions via pulse monitoring.

Neo-Symbiosis: The Next Stage in the Evolution of Human Information Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Griffith, Douglas; Greitzer, Frank L.

Abstract--The purpose of this paper is to re-address the vision of human-computer symbiosis as originally expressed by J.C.R. Licklider nearly a half-century ago. We describe this vision, place it in some historical context relating to the evolution of human factors research, and we observe that the field is now in the process of re-invigorating Licklider’s vision. We briefly assess the state of the technology within the context of contemporary theory and practice, and we describe what we regard as this emerging field of neo-symbiosis. We offer some initial thoughts on requirements to define functionality of neo-symbiotic systems and discuss researchmore » challenges associated with their development and evaluation.« less

Computational models of human vision with applications

NASA Technical Reports Server (NTRS)

Wandell, B. A.

1985-01-01

Perceptual problems in aeronautics were studied. The mechanism by which color constancy is achieved in human vision was examined. A computable algorithm was developed to model the arrangement of retinal cones in spatial vision. The spatial frequency spectra are similar to the spectra of actual cone mosaics. The Hartley transform as a tool of image processing was evaluated and it is suggested that it could be used in signal processing applications, GR image processing.

Artificial Intelligence.

ERIC Educational Resources Information Center

Wash, Darrel Patrick

1989-01-01

Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

Artificial Intelligence: Underlying Assumptions and Basic Objectives.

ERIC Educational Resources Information Center

Cercone, Nick; McCalla, Gordon

1984-01-01

Presents perspectives on methodological assumptions underlying research efforts in artificial intelligence (AI) and charts activities, motivations, methods, and current status of research in each of the major AI subareas: natural language understanding; computer vision; expert systems; search, problem solving, planning; theorem proving and logic…

Automatic recognition of lactating sow behaviors through depth image processing

USDA-ARS?s Scientific Manuscript database

Manual observation and classification of animal behaviors is laborious, time-consuming, and of limited ability to process large amount of data. A computer vision-based system was developed that automatically recognizes sow behaviors (lying, sitting, standing, kneeling, feeding, drinking, and shiftin...

Precision of computer-assisted core decompression drilling of the femoral head.

PubMed

Beckmann, J; Goetz, J; Baethis, H; Kalteis, T; Grifka, J; Perlick, L

2006-08-01

Osteonecrosis of the femoral head is a local destructive disease with progression into devastating stages. Left untreated it mostly leads to severe secondary osteoarthrosis and early endoprosthetic joint replacement. Core decompression by exact drilling into the ischemic areas can be performed in early stages according to Ficat or ARCO. Computer-aided surgery might enhance the precision of the drilling and lower the radiation exposure time of both staff and patients. The aim of this study was to evaluate the precision of the fluoroscopically based VectorVision navigation system in an in vitro model. Thirty sawbones were prepared with a defect filled up with a radiopaque gypsum sphere mimicking the osteonecrosis. Twenty sawbones were drilled by guidance of an intraoperative navigation system VectorVision (BrainLAB, Munich, Germany) and 10 sawbones by fluoroscopic control only. No gypsum sphere was missed. There was a statistically significant difference regarding the three-dimensional deviation (Euclidian norm) as well as maximum deviation in x-, y- or z-direction (maximum norm) to the desired mid-point of the lesion, with a mean of 0.51 and 0.4 mm in the navigated group and 1.1 and 0.88 mm in the control group, respectively. Furthermore, significant difference was found in the number of drilling corrections as well as the radiation time needed: no second drilling or correction of drilling direction was necessary in the navigated group compared to 1.4 in the control group. The radiation time needed was less than 1 s compared to 3.1 s, respectively. The fluoroscopy-based VectorVision navigation system shows a high feasibility of computer-guided drilling with a clear reduction of radiation exposure time and can therefore be integrated into clinical routine. The additional time needed is acceptable regarding the simultaneous reduction of radiation time.

Compact Microscope Imaging System with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The figure presents selected views of a compact microscope imaging system (CMIS) that includes a miniature video microscope, a Cartesian robot (a computer- controlled three-dimensional translation stage), and machine-vision and control subsystems. The CMIS was built from commercial off-the-shelf instrumentation, computer hardware and software, and custom machine-vision software. The machine-vision and control subsystems include adaptive neural networks that afford a measure of artificial intelligence. The CMIS can perform several automated tasks with accuracy and repeatability . tasks that, heretofore, have required the full attention of human technicians using relatively bulky conventional microscopes. In addition, the automation and control capabilities of the system inherently include a capability for remote control. Unlike human technicians, the CMIS is not at risk of becoming fatigued or distracted: theoretically, it can perform continuously at the level of the best human technicians. In its capabilities for remote control and for relieving human technicians of tedious routine tasks, the CMIS is expected to be especially useful in biomedical research, materials science, inspection of parts on industrial production lines, and space science. The CMIS can automatically focus on and scan a microscope sample, find areas of interest, record the resulting images, and analyze images from multiple samples simultaneously. Automatic focusing is an iterative process: The translation stage is used to move the microscope along its optical axis in a succession of coarse, medium, and fine steps. A fast Fourier transform (FFT) of the image is computed at each step, and the FFT is analyzed for its spatial-frequency content. The microscope position that results in the greatest dispersal of FFT content toward high spatial frequencies (indicating that the image shows the greatest amount of detail) is deemed to be the focal position.

Automatic vision system for analysis of microscopic behavior of flow and transport in porous media

NASA Astrophysics Data System (ADS)

Rashidi, Mehdi; Dehmeshki, Jamshid; Dickenson, Eric; Daemi, M. Farhang

1997-10-01

This paper describes the development of a novel automated and efficient vision system to obtain velocity and concentration measurement within a porous medium. An aqueous fluid lace with a fluorescent dye to microspheres flows through a transparent, refractive-index-matched column packed with transparent crystals. For illumination purposes, a planar sheet of laser passes through the column as a CCD camera records all the laser illuminated planes. Detailed microscopic velocity and concentration fields have been computed within a 3D volume of the column. For measuring velocities, while the aqueous fluid, laced with fluorescent microspheres, flows through the transparent medium, a CCD camera records the motions of the fluorescing particles by a video cassette recorder. The recorded images are acquired automatically frame by frame and transferred to the computer for processing, by using a frame grabber an written relevant algorithms through an RS-232 interface. Since the grabbed image is poor in this stage, some preprocessings are used to enhance particles within images. Finally, these enhanced particles are monitored to calculate velocity vectors in the plane of the beam. For concentration measurements, while the aqueous fluid, laced with a fluorescent organic dye, flows through the transparent medium, a CCD camera sweeps back and forth across the column and records concentration slices on the planes illuminated by the laser beam traveling simultaneously with the camera. Subsequently, these recorded images are transferred to the computer for processing in similar fashion to the velocity measurement. In order to have a fully automatic vision system, several detailed image processing techniques are developed to match exact images that have different intensities values but the same topological characteristics. This results in normalized interstitial chemical concentrations as a function of time within the porous column.

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

PubMed

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

2012-01-01

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

Computer vision syndrome-A common cause of unexplained visual symptoms in the modern era.

PubMed

Munshi, Sunil; Varghese, Ashley; Dhar-Munshi, Sushma

2017-07-01

The aim of this study was to assess the evidence and available literature on the clinical, pathogenetic, prognostic and therapeutic aspects of Computer vision syndrome. Information was collected from Medline, Embase & National Library of Medicine over the last 30 years up to March 2016. The bibliographies of relevant articles were searched for additional references. Patients with Computer vision syndrome present to a variety of different specialists, including General Practitioners, Neurologists, Stroke physicians and Ophthalmologists. While the condition is common, there is a poor awareness in the public and among health professionals. Recognising this condition in the clinic or in emergency situations like the TIA clinic is crucial. The implications are potentially huge in view of the extensive and widespread use of computers and visual display units. Greater public awareness of Computer vision syndrome and education of health professionals is vital. Preventive strategies should form part of work place ergonomics routinely. Prompt and correct recognition is important to allow management and avoid unnecessary treatments. © 2017 John Wiley & Sons Ltd.

Comparative randomised controlled clinical trial of a herbal eye drop with artificial tear and placebo in computer vision syndrome.

PubMed

Biswas, N R; Nainiwal, S K; Das, G K; Langan, U; Dadeya, S C; Mongre, P K; Ravi, A K; Baidya, P

2003-03-01

A comparative randomised double masked multicentric clinical trial has been conducted to find out the efficacy and safety of a herbal eye drop preparation, itone eye drops with artificial tear and placebo in 120 patients with computer vision syndrome. Patients using computer for at least 2 hours continuosly per day having symptoms of irritation, foreign body sensation, watering, redness, headache, eyeache and signs of conjunctival congestion, mucous/debris, corneal filaments, corneal staining or lacrimal lake were included in this study. Every patient was instructed to put two drops of either herbal drugs or placebo or artificial tear in the eyes regularly four times for 6 weeks. Objective and subjective findings were recorded at bi-weekly intervals up to six weeks. Side-effects, if any, were also noted. In computer vision syndrome the herbal eye drop preparation was found significantly better than artificial tear (p < 0.01). No side-effects were noted by any of the drugs. Both subjective and objective improvements were observed in itone treated cases. So, itone can be considered as a useful drug in computer vision syndrome.

Computer vision syndrome in presbyopia and beginning presbyopia: effects of spectacle lens type.

PubMed

Jaschinski, Wolfgang; König, Mirjam; Mekontso, Tiofil M; Ohlendorf, Arne; Welscher, Monique

2015-05-01

This office field study investigated the effects of different types of spectacle lenses habitually worn by computer users with presbyopia and in the beginning stages of presbyopia. Computer vision syndrome was assessed through reported complaints and ergonomic conditions. A questionnaire regarding the type of habitually worn near-vision lenses at the workplace, visual conditions and the levels of different types of complaints was administered to 175 participants aged 35 years and older (mean ± SD: 52.0 ± 6.7 years). Statistical factor analysis identified five specific aspects of the complaints. Workplace conditions were analysed based on photographs taken in typical working conditions. In the subgroup of 25 users between the ages of 36 and 57 years (mean 44 ± 5 years), who wore distance-vision lenses and performed more demanding occupational tasks, the reported extents of 'ocular strain', 'musculoskeletal strain' and 'headache' increased with the daily duration of computer work and explained up to 44 per cent of the variance (rs = 0.66). In the other subgroups, this effect was smaller, while in the complete sample (n = 175), this correlation was approximately rs = 0.2. The subgroup of 85 general-purpose progressive lens users (mean age 54 years) adopted head inclinations that were approximately seven degrees more elevated than those of the subgroups with single vision lenses. The present questionnaire was able to assess the complaints of computer users depending on the type of spectacle lenses worn. A missing near-vision addition among participants in the early stages of presbyopia was identified as a risk factor for complaints among those with longer daily durations of demanding computer work. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Automatic decoding of facial movements reveals deceptive pain expressions

PubMed Central

Bartlett, Marian Stewart; Littlewort, Gwen C.; Frank, Mark G.; Lee, Kang

2014-01-01

Summary In highly social species such as humans, faces have evolved to convey rich information for social interaction, including expressions of emotions and pain [1–3]. Two motor pathways control facial movement [4–7]. A subcortical extrapyramidal motor system drives spontaneous facial expressions of felt emotions. A cortical pyramidal motor system controls voluntary facial expressions. The pyramidal system enables humans to simulate facial expressions of emotions not actually experienced. Their simulation is so successful that they can deceive most observers [8–11]. Machine vision may, however, be able to distinguish deceptive from genuine facial signals by identifying the subtle differences between pyramidally and extrapyramidally driven movements. Here we show that human observers could not discriminate real from faked expressions of pain better than chance, and after training, improved accuracy to a modest 55%. However a computer vision system that automatically measures facial movements and performs pattern recognition on those movements attained 85% accuracy. The machine system’s superiority is attributable to its ability to differentiate the dynamics of genuine from faked expressions. Thus by revealing the dynamics of facial action through machine vision systems, our approach has the potential to elucidate behavioral fingerprints of neural control systems involved in emotional signaling. PMID:24656830

A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

PubMed

Linder, Nina; Turkki, Riku; Walliander, Margarita; Mårtensson, Andreas; Diwan, Vinod; Rahtu, Esa; Pietikäinen, Matti; Lundin, Mikael; Lundin, Johan

2014-01-01

Microscopy is the gold standard for diagnosis of malaria, however, manual evaluation of blood films is highly dependent on skilled personnel in a time-consuming, error-prone and repetitive process. In this study we propose a method using computer vision detection and visualization of only the diagnostically most relevant sample regions in digitized blood smears. Giemsa-stained thin blood films with P. falciparum ring-stage trophozoites (n = 27) and uninfected controls (n = 20) were digitally scanned with an oil immersion objective (0.1 µm/pixel) to capture approximately 50,000 erythrocytes per sample. Parasite candidate regions were identified based on color and object size, followed by extraction of image features (local binary patterns, local contrast and Scale-invariant feature transform descriptors) used as input to a support vector machine classifier. The classifier was trained on digital slides from ten patients and validated on six samples. The diagnostic accuracy was tested on 31 samples (19 infected and 12 controls). From each digitized area of a blood smear, a panel with the 128 most probable parasite candidate regions was generated. Two expert microscopists were asked to visually inspect the panel on a tablet computer and to judge whether the patient was infected with P. falciparum. The method achieved a diagnostic sensitivity and specificity of 95% and 100% as well as 90% and 100% for the two readers respectively using the diagnostic tool. Parasitemia was separately calculated by the automated system and the correlation coefficient between manual and automated parasitemia counts was 0.97. We developed a decision support system for detecting malaria parasites using a computer vision algorithm combined with visualization of sample areas with the highest probability of malaria infection. The system provides a novel method for blood smear screening with a significantly reduced need for visual examination and has a potential to increase the throughput in malaria diagnostics.

Computer vision syndrome (CVS) - Thermographic Analysis

NASA Astrophysics Data System (ADS)

Llamosa-Rincón, L. E.; Jaime-Díaz, J. M.; Ruiz-Cardona, D. F.

2017-01-01

The use of computers has reported an exponential growth in the last decades, the possibility of carrying out several tasks for both professional and leisure purposes has contributed to the great acceptance by the users. The consequences and impact of uninterrupted tasks with computers screens or displays on the visual health, have grabbed researcher’s attention. When spending long periods of time in front of a computer screen, human eyes are subjected to great efforts, which in turn triggers a set of symptoms known as Computer Vision Syndrome (CVS). Most common of them are: blurred vision, visual fatigue and Dry Eye Syndrome (DES) due to unappropriate lubrication of ocular surface when blinking decreases. An experimental protocol was de-signed and implemented to perform thermographic studies on healthy human eyes during exposure to dis-plays of computers, with the main purpose of comparing the existing differences in temperature variations of healthy ocular surfaces.

Automated design of image operators that detect interest points.

PubMed

Trujillo, Leonardo; Olague, Gustavo

2008-01-01

This work describes how evolutionary computation can be used to synthesize low-level image operators that detect interesting points on digital images. Interest point detection is an essential part of many modern computer vision systems that solve tasks such as object recognition, stereo correspondence, and image indexing, to name but a few. The design of the specialized operators is posed as an optimization/search problem that is solved with genetic programming (GP), a strategy still mostly unexplored by the computer vision community. The proposed approach automatically synthesizes operators that are competitive with state-of-the-art designs, taking into account an operator's geometric stability and the global separability of detected points during fitness evaluation. The GP search space is defined using simple primitive operations that are commonly found in point detectors proposed by the vision community. The experiments described in this paper extend previous results (Trujillo and Olague, 2006a,b) by presenting 15 new operators that were synthesized through the GP-based search. Some of the synthesized operators can be regarded as improved manmade designs because they employ well-known image processing techniques and achieve highly competitive performance. On the other hand, since the GP search also generates what can be considered as unconventional operators for point detection, these results provide a new perspective to feature extraction research.

Machine vision system for measuring conifer seedling morphology

NASA Astrophysics Data System (ADS)

Rigney, Michael P.; Kranzler, Glenn A.

1995-01-01

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

A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

NASA Astrophysics Data System (ADS)

Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

Automated measurement of human body shape and curvature using computer vision

NASA Astrophysics Data System (ADS)

Pearson, Jeremy D.; Hobson, Clifford A.; Dangerfield, Peter H.

1993-06-01

A system to measure the surface shape of the human body has been constructed. The system uses a fringe pattern generated by projection of multi-stripe structured light. The optical methodology used is fully described and the algorithms used to process acquired digital images are outlined. The system has been applied to the measurement of the shape of the human back in scoliosis.

Milestones on the road to independence for the blind

NASA Astrophysics Data System (ADS)

Reed, Kenneth

1997-02-01

Ken will talk about his experiences as an end user of technology. Even moderate technological progress in the field of pattern recognition and artificial intelligence can be, often surprisingly, of great help to the blind. An example is the providing of portable bar code scanners so that a blind person knows what he is buying and what color it is. In this age of microprocessors controlling everything, how can a blind person find out what his VCR is doing? Is there some technique that will allow a blind musician to convert print music into midi files to drive a synthesizer? Can computer vision help the blind cross a road including predictions of where oncoming traffic will be located? Can computer vision technology provide spoken description of scenes so a blind person can figure out where doors and entrances are located, and what the signage on the building says? He asks 'can computer vision help me flip a pancake?' His challenge to those in the computer vision field is 'where can we go from here?'

A large-scale solar dynamics observatory image dataset for computer vision applications.

PubMed

Kucuk, Ahmet; Banda, Juan M; Angryk, Rafal A

2017-01-01

The National Aeronautics Space Agency (NASA) Solar Dynamics Observatory (SDO) mission has given us unprecedented insight into the Sun's activity. By capturing approximately 70,000 images a day, this mission has created one of the richest and biggest repositories of solar image data available to mankind. With such massive amounts of information, researchers have been able to produce great advances in detecting solar events. In this resource, we compile SDO solar data into a single repository in order to provide the computer vision community with a standardized and curated large-scale dataset of several hundred thousand solar events found on high resolution solar images. This publicly available resource, along with the generation source code, will accelerate computer vision research on NASA's solar image data by reducing the amount of time spent performing data acquisition and curation from the multiple sources we have compiled. By improving the quality of the data with thorough curation, we anticipate a wider adoption and interest from the computer vision to the solar physics community.

The Ilac-Project Supporting Ancient Coin Classification by Means of Image Analysis

NASA Astrophysics Data System (ADS)

Kavelar, A.; Zambanini, S.; Kampel, M.; Vondrovec, K.; Siegl, K.

2013-07-01

This paper presents the ILAC project, which aims at the development of an automated image-based classification system for ancient Roman Republican coins. The benefits of such a system are manifold: operating at the suture between computer vision and numismatics, ILAC can reduce the day-to-day workload of numismatists by assisting them in classification tasks and providing a preselection of suitable coin classes. This is especially helpful for large coin hoard findings comprising several thousands of coins. Furthermore, this system could be implemented in an online platform for hobby numismatists, allowing them to access background information about their coin collection by simply uploading a photo of obverse and reverse for the coin of interest. ILAC explores different computer vision techniques and their combinations for the use of image-based coin recognition. Some of these methods, such as image matching, use the entire coin image in the classification process, while symbol or legend recognition exploit certain characteristics of the coin imagery. An overview of the methods explored so far and the respective experiments is given as well as an outlook on the next steps of the project.

Recent developments in computer vision-based analytical chemistry: A tutorial review.

PubMed

Capitán-Vallvey, Luis Fermín; López-Ruiz, Nuria; Martínez-Olmos, Antonio; Erenas, Miguel M; Palma, Alberto J

2015-10-29

Chemical analysis based on colour changes recorded with imaging devices is gaining increasing interest. This is due to its several significant advantages, such as simplicity of use, and the fact that it is easily combinable with portable and widely distributed imaging devices, resulting in friendly analytical procedures in many areas that demand out-of-lab applications for in situ and real-time monitoring. This tutorial review covers computer vision-based analytical (CVAC) procedures and systems from 2005 to 2015, a period of time when 87.5% of the papers on this topic were published. The background regarding colour spaces and recent analytical system architectures of interest in analytical chemistry is presented in the form of a tutorial. Moreover, issues regarding images, such as the influence of illuminants, and the most relevant techniques for processing and analysing digital images are addressed. Some of the most relevant applications are then detailed, highlighting their main characteristics. Finally, our opinion about future perspectives is discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Computer Vision Malaria Diagnostic Systems-Progress and Prospects.

PubMed

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

2017-01-01

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

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

PubMed

Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

2018-06-01

The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Computer eyeglasses--aspects of a confusing topic].

PubMed

Huber-Spitzy, V; Janeba, E

1997-01-01

With the coming into force of the new Austrian Employee Protection Act the issue of the so called "computer glasses" will also gain added importance in our country. Such glasses have been defined as vision aids to be exclusively used for the work on computer monitors and include single-vision glasses solely intended for reading computer screen, glasses with bifocal lenses for reading computer screen and hard-copy documents as well as those with varifocal lenses featuring a thickened central section. There is still a considerable controversy among those concerned as to who will bear the costs for such glasses--most likely it will be the employer. Prescription of such vision aids will be exclusively restricted to ophthalmologists, based on a thorough ophthalmological examination under adequate consideration of the specific working environment and the workplace requirements of the individual employee concerned.

TOXICITY TESTING IN THE 21ST CENTURY: A VISION AND A STRATEGY

PubMed Central

Krewski, Daniel; Acosta, Daniel; Andersen, Melvin; Anderson, Henry; Bailar, John C.; Boekelheide, Kim; Brent, Robert; Charnley, Gail; Cheung, Vivian G.; Green, Sidney; Kelsey, Karl T.; Kerkvliet, Nancy I.; Li, Abby A.; McCray, Lawrence; Meyer, Otto; Patterson, Reid D.; Pennie, William; Scala, Robert A.; Solomon, Gina M.; Stephens, Martin; Yager, James; Zeise, Lauren

2015-01-01

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology. PMID:20574894

Development of yarn breakage detection software system based on machine vision

NASA Astrophysics Data System (ADS)

Wang, Wenyuan; Zhou, Ping; Lin, Xiangyu

2017-10-01

For questions spinning mills and yarn breakage cannot be detected in a timely manner, and save the cost of textile enterprises. This paper presents a software system based on computer vision for real-time detection of yarn breakage. The system and Windows8.1 system Tablet PC, cloud server to complete the yarn breakage detection and management. Running on the Tablet PC software system is designed to collect yarn and location information for analysis and processing. And will be processed after the information through the Wi-Fi and http protocol sent to the cloud server to store in the Microsoft SQL2008 database. In order to follow up on the yarn break information query and management. Finally sent to the local display on time display, and remind the operator to deal with broken yarn. The experimental results show that the system of missed test rate not more than 5%o, and no error detection.

Embedded Systems and TensorFlow Frameworks as Assistive Technology Solutions.

PubMed

Mulfari, Davide; Palla, Alessandro; Fanucci, Luca

2017-01-01

In the field of deep learning, this paper presents the design of a wearable computer vision system for visually impaired users. The Assistive Technology solution exploits a powerful single board computer and smart glasses with a camera in order to allow its user to explore the objects within his surrounding environment, while it employs Google TensorFlow machine learning framework in order to real time classify the acquired stills. Therefore the proposed aid can increase the awareness of the explored environment and it interacts with its user by means of audio messages.

Mars Rover imaging systems and directional filtering

NASA Technical Reports Server (NTRS)

Wang, Paul P.

1989-01-01

Computer literature searches were carried out at Duke University and NASA Langley Research Center. The purpose is to enhance personal knowledge based on the technical problems of pattern recognition and image understanding which must be solved for the Mars Rover and Sample Return Mission. Intensive study effort of a large collection of relevant literature resulted in a compilation of all important documents in one place. Furthermore, the documents are being classified into: Mars Rover; computer vision (theory); imaging systems; pattern recognition methodologies; and other smart techniques (AI, neural networks, fuzzy logic, etc).

Algorithms in nature: the convergence of systems biology and computational thinking

PubMed Central

Navlakha, Saket; Bar-Joseph, Ziv

2011-01-01

Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Recently, these two directions have been converging. In this review, we argue that thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. We discuss the similar mechanisms and requirements shared by computational and biological processes and then present several recent studies that apply this joint analysis strategy to problems related to coordination, network analysis, and tracking and vision. We also discuss additional biological processes that can be studied in a similar manner and link them to potential computational problems. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future. PMID:22068329

77 FR 16890 - Eighteenth Meeting: RTCA Special Committee 213, Enhanced Flight Visions Systems/Synthetic Vision...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-22

... Committee 213, Enhanced Flight Visions Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY: Federal Aviation... 213, Enhanced Flight Visions Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing... Flight Visions Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held April 17-19...

78 FR 5557 - Twenty-First Meeting: RTCA Special Committee 213, Enhanced Flight Vision Systems/Synthetic Vision...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-25

... Committee 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY: Federal Aviation... 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing..., Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held...

77 FR 56254 - Twentieth Meeting: RTCA Special Committee 213, Enhanced Flight Vision Systems/Synthetic Vision...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-12

... Committee 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY: Federal Aviation... 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing... Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held October 2-4...

Brain-computer interaction research at the Computer Vision and Multimedia Laboratory, University of Geneva.

PubMed

Pun, Thierry; Alecu, Teodor Iulian; Chanel, Guillaume; Kronegg, Julien; Voloshynovskiy, Sviatoslav

2006-06-01

This paper describes the work being conducted in the domain of brain-computer interaction (BCI) at the Multimodal Interaction Group, Computer Vision and Multimedia Laboratory, University of Geneva, Geneva, Switzerland. The application focus of this work is on multimodal interaction rather than on rehabilitation, that is how to augment classical interaction by means of physiological measurements. Three main research topics are addressed. The first one concerns the more general problem of brain source activity recognition from EEGs. In contrast with classical deterministic approaches, we studied iterative robust stochastic based reconstruction procedures modeling source and noise statistics, to overcome known limitations of current techniques. We also developed procedures for optimal electroencephalogram (EEG) sensor system design in terms of placement and number of electrodes. The second topic is the study of BCI protocols and performance from an information-theoretic point of view. Various information rate measurements have been compared for assessing BCI abilities. The third research topic concerns the use of EEG and other physiological signals for assessing a user's emotional status.

Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.

PubMed

Marchetti, Michael A; Codella, Noel C F; Dusza, Stephen W; Gutman, David A; Helba, Brian; Kalloo, Aadi; Mishra, Nabin; Carrera, Cristina; Celebi, M Emre; DeFazio, Jennifer L; Jaimes, Natalia; Marghoob, Ashfaq A; Quigley, Elizabeth; Scope, Alon; Yélamos, Oriol; Halpern, Allan C

2018-02-01

Computer vision may aid in melanoma detection. We sought to compare melanoma diagnostic accuracy of computer algorithms to dermatologists using dermoscopic images. We conducted a cross-sectional study using 100 randomly selected dermoscopic images (50 melanomas, 44 nevi, and 6 lentigines) from an international computer vision melanoma challenge dataset (n = 379), along with individual algorithm results from 25 teams. We used 5 methods (nonlearned and machine learning) to combine individual automated predictions into "fusion" algorithms. In a companion study, 8 dermatologists classified the lesions in the 100 images as either benign or malignant. The average sensitivity and specificity of dermatologists in classification was 82% and 59%. At 82% sensitivity, dermatologist specificity was similar to the top challenge algorithm (59% vs. 62%, P = .68) but lower than the best-performing fusion algorithm (59% vs. 76%, P = .02). Receiver operating characteristic area of the top fusion algorithm was greater than the mean receiver operating characteristic area of dermatologists (0.86 vs. 0.71, P = .001). The dataset lacked the full spectrum of skin lesions encountered in clinical practice, particularly banal lesions. Readers and algorithms were not provided clinical data (eg, age or lesion history/symptoms). Results obtained using our study design cannot be extrapolated to clinical practice. Deep learning computer vision systems classified melanoma dermoscopy images with accuracy that exceeded some but not all dermatologists. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Computer Vision Photogrammetry for Underwater Archaeological Site Recording in a Low-Visibility Environment

NASA Astrophysics Data System (ADS)

Van Damme, T.

2015-04-01

Computer Vision Photogrammetry allows archaeologists to accurately record underwater sites in three dimensions using simple twodimensional picture or video sequences, automatically processed in dedicated software. In this article, I share my experience in working with one such software package, namely PhotoScan, to record a Dutch shipwreck site. In order to demonstrate the method's reliability and flexibility, the site in question is reconstructed from simple GoPro footage, captured in low-visibility conditions. Based on the results of this case study, Computer Vision Photogrammetry compares very favourably to manual recording methods both in recording efficiency, and in the quality of the final results. In a final section, the significance of Computer Vision Photogrammetry is then assessed from a historical perspective, by placing the current research in the wider context of about half a century of successful use of Analytical and later Digital photogrammetry in the field of underwater archaeology. I conclude that while photogrammetry has been used in our discipline for several decades now, for various reasons the method was only ever used by a relatively small percentage of projects. This is likely to change in the near future since, compared to the `traditional' photogrammetry approaches employed in the past, today Computer Vision Photogrammetry is easier to use, more reliable and more affordable than ever before, while at the same time producing more accurate and more detailed three-dimensional results.

Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis

NASA Astrophysics Data System (ADS)

Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

2015-12-01

Objective. Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. Approach. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. Main results. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. Significance. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis.

PubMed

Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

2015-12-01

Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

Issues central to a useful image understanding environment

NASA Astrophysics Data System (ADS)

Beveridge, J. Ross; Draper, Bruce A.; Hanson, Allen R.; Riseman, Edward M.

1992-04-01

A recent DARPA initiative has sparked interested in software environments for computer vision. The goal is a single environment to support both basic research and technology transfer. This paper lays out six fundamental attributes such a system must possess: (1) support for both C and Lisp, (2) extensibility, (3) data sharing, (4) data query facilities tailored to vision, (5) graphics, and (6) code sharing. The first three attributes fundamentally constrain the system design. Support for both C and Lisp demands some form of database or data-store for passing data between languages. Extensibility demands that system support facilities, such as spatial retrieval of data, be readily extended to new user-defined datatypes. Finally, data sharing demands that data saved by one user, including data of a user-defined type, must be readable by another user.

Computational Vision: A Critical Review

DTIC Science & Technology

1989-10-01

Optic News, 15:9-25, 1989. [8] H. B . Barlow and R. W. Levick . The mechanism of directional selectivity in the rabbit’s retina. J. Physiol., 173:477...comparison, other formulations, e.g., [64], used 16 @V A \\E(t=t2) (a) \\ E(t-tl) ( b ) Figure 7: An illustration of the aperture problem. Left: a bar E is...Ballard and C. M. Brown. Computer Vision. Prentice-Hall, Englewood Cliffs, NJ, 1982. [7] D. H. Ballard, R. C. Nelson, and B . Yamauchi. Animate vision

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress

PubMed Central

Fu, Longwen; Liu, Zuoyi

2018-01-01

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented. PMID:29849612

PlantCV v2: Image analysis software for high-throughput plant phenotyping

PubMed Central

Abbasi, Arash; Berry, Jeffrey C.; Callen, Steven T.; Chavez, Leonardo; Doust, Andrew N.; Feldman, Max J.; Gilbert, Kerrigan B.; Hodge, John G.; Hoyer, J. Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning. PMID:29209576

PlantCV v2: Image analysis software for high-throughput plant phenotyping.

PubMed

Gehan, Malia A; Fahlgren, Noah; Abbasi, Arash; Berry, Jeffrey C; Callen, Steven T; Chavez, Leonardo; Doust, Andrew N; Feldman, Max J; Gilbert, Kerrigan B; Hodge, John G; Hoyer, J Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

PlantCV v2: Image analysis software for high-throughput plant phenotyping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

PlantCV v2: Image analysis software for high-throughput plant phenotyping

DOE PAGES

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash; ...

2017-12-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

Data-driven ranch management: A vision for sustainable ranching

USDA-ARS?s Scientific Manuscript database

Introduction The 21st century has ushered in an era of tiny, inexpensive electronics with impressive capabilities for sensing the environment. Also emerging are new technologies for communicating data to computer systems where new analytical tools can process the data. Many of these technologies w...

How the Air Force Should Stay Engaged in Computer Vision Technology Development

DTIC Science & Technology

2007-04-01

present individuals. The survey 29 Paddy Comyn, "Sensing Forward to a Driverless Future," The Irish...34 Military Embedded Systems (2006). Comyn, Paddy. "Sensing Forward to a Driverless Future." The Irish Times 21 February 2007. Dakley, Norman C. The

A multimodal 3D framework for fire characteristics estimation

NASA Astrophysics Data System (ADS)

Toulouse, T.; Rossi, L.; Akhloufi, M. A.; Pieri, A.; Maldague, X.

2018-02-01

In the last decade we have witnessed an increasing interest in using computer vision and image processing in forest fire research. Image processing techniques have been successfully used in different fire analysis areas such as early detection, monitoring, modeling and fire front characteristics estimation. While the majority of the work deals with the use of 2D visible spectrum images, recent work has introduced the use of 3D vision in this field. This work proposes a new multimodal vision framework permitting the extraction of the three-dimensional geometrical characteristics of fires captured by multiple 3D vision systems. The 3D system is a multispectral stereo system operating in both the visible and near-infrared (NIR) spectral bands. The framework supports the use of multiple stereo pairs positioned so as to capture complementary views of the fire front during its propagation. Multimodal registration is conducted using the captured views in order to build a complete 3D model of the fire front. The registration process is achieved using multisensory fusion based on visual data (2D and NIR images), GPS positions and IMU inertial data. Experiments were conducted outdoors in order to show the performance of the proposed framework. The obtained results are promising and show the potential of using the proposed framework in operational scenarios for wildland fire research and as a decision management system in fighting.

AstroCV: Astronomy computer vision library

NASA Astrophysics Data System (ADS)

González, Roberto E.; Muñoz, Roberto P.; Hernández, Cristian A.

2018-04-01

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

Projector-Camera Systems for Immersive Training

DTIC Science & Technology

2006-01-01

average to a sequence of 100 captured distortion corrected images. The OpenCV library [ OpenCV ] was used for camera calibration. To correct for...rendering application [Treskunov, Pair, and Swartout, 2004]. It was transposed to take into account different matrix conventions between OpenCV and...Screen Imperfections. Proc. Workshop on Projector-Camera Systems (PROCAMS), Nice, France, IEEE. OpenCV : Open Source Computer Vision. [Available

Economics of cutting hardwood dimension parts with an automated system

Treesearch

Henry A. Huber; Steve Ruddell; Kalinath Mukherjee; Charles W. McMillin

1989-01-01

A financial analysis using discounted cash-flow decision methods was completed to determine the economic feasibility of replacing a conventional roughmill crosscut and rip operation with a proposed automated computer vision and laser cutting system. Red oak and soft maple lumber were cut at production levels of 30 thousand board feet (MBF)/day and 5 MBF/day to produce...

Remote hardware-reconfigurable robotic camera

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar; Maya-Rueda, Selene E.

2001-10-01

In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software functionalities that can be exchanged during run time. The system has been validated with an edge detection and a motion processing architecture, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.

Reducing the Time and Cost of Testing Engines

NASA Technical Reports Server (NTRS)

2004-01-01

Producing a new aircraft engine currently costs approximately $1 billion, with 3 years of development time for a commercial engine and 10 years for a military engine. The high development time and cost make it extremely difficult to transition advanced technologies for cleaner, quieter, and more efficient new engines. To reduce this time and cost, NASA created a vision for the future where designers would use high-fidelity computer simulations early in the design process in order to resolve critical design issues before building the expensive engine hardware. To accomplish this vision, NASA's Glenn Research Center initiated a collaborative effort with the aerospace industry and academia to develop its Numerical Propulsion System Simulation (NPSS), an advanced engineering environment for the analysis and design of aerospace propulsion systems and components. Partners estimate that using NPSS has the potential to dramatically reduce the time, effort, and expense necessary to design and test jet engines by generating sophisticated computer simulations of an aerospace object or system. These simulations will permit an engineer to test various design options without having to conduct costly and time-consuming real-life tests. By accelerating and streamlining the engine system design analysis and test phases, NPSS facilitates bringing the final product to market faster. NASA's NPSS Version (V)1.X effort was a task within the Agency s Computational Aerospace Sciences project of the High Performance Computing and Communication program, which had a mission to accelerate the availability of high-performance computing hardware and software to the U.S. aerospace community for its use in design processes. The technology brings value back to NASA by improving methods of analyzing and testing space transportation components.

Identifying the Computational Requirements of an Integrated Top-Down-Bottom-Up Model for Overt Visual Attention within an Active Vision System

PubMed Central

McBride, Sebastian; Huelse, Martin; Lee, Mark

2013-01-01

Computational visual attention systems have been constructed in order for robots and other devices to detect and locate regions of interest in their visual world. Such systems often attempt to take account of what is known of the human visual system and employ concepts, such as ‘active vision’, to gain various perceived advantages. However, despite the potential for gaining insights from such experiments, the computational requirements for visual attention processing are often not clearly presented from a biological perspective. This was the primary objective of this study, attained through two specific phases of investigation: 1) conceptual modeling of a top-down-bottom-up framework through critical analysis of the psychophysical and neurophysiological literature, 2) implementation and validation of the model into robotic hardware (as a representative of an active vision system). Seven computational requirements were identified: 1) transformation of retinotopic to egocentric mappings, 2) spatial memory for the purposes of medium-term inhibition of return, 3) synchronization of ‘where’ and ‘what’ information from the two visual streams, 4) convergence of top-down and bottom-up information to a centralized point of information processing, 5) a threshold function to elicit saccade action, 6) a function to represent task relevance as a ratio of excitation and inhibition, and 7) derivation of excitation and inhibition values from object-associated feature classes. The model provides further insight into the nature of data representation and transfer between brain regions associated with the vertebrate ‘active’ visual attention system. In particular, the model lends strong support to the functional role of the lateral intraparietal region of the brain as a primary area of information consolidation that directs putative action through the use of a ‘priority map’. PMID:23437044

State-Estimation Algorithm Based on Computer Vision

NASA Technical Reports Server (NTRS)

Bayard, David; Brugarolas, Paul

2007-01-01

An algorithm and software to implement the algorithm are being developed as means to estimate the state (that is, the position and velocity) of an autonomous vehicle, relative to a visible nearby target object, to provide guidance for maneuvering the vehicle. In the original intended application, the autonomous vehicle would be a spacecraft and the nearby object would be a small astronomical body (typically, a comet or asteroid) to be explored by the spacecraft. The algorithm could also be used on Earth in analogous applications -- for example, for guiding underwater robots near such objects of interest as sunken ships, mineral deposits, or submerged mines. It is assumed that the robot would be equipped with a vision system that would include one or more electronic cameras, image-digitizing circuitry, and an imagedata- processing computer that would generate feature-recognition data products.

Computer vision techniques for rotorcraft low-altitude flight

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Cheng, Victor H. L.

1988-01-01

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning

PubMed Central

Wang, Shuihua; Yang, Ming; Du, Sidan; Yang, Jiquan; Liu, Bin; Gorriz, Juan M.; Ramírez, Javier; Yuan, Ti-Fei; Zhang, Yudong

2016-01-01

Highlights We develop computer-aided diagnosis system for unilateral hearing loss detection in structural magnetic resonance imaging.Wavelet entropy is introduced to extract image global features from brain images. Directed acyclic graph is employed to endow support vector machine an ability to handle multi-class problems.The developed computer-aided diagnosis system achieves an overall accuracy of 95.1% for this three-class problem of differentiating left-sided and right-sided hearing loss from healthy controls. Aim: Sensorineural hearing loss (SNHL) is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. Materials: We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany). The subjects contain 14 patients with right-sided hearing loss (RHL), 15 patients with left-sided hearing loss (LHL), and 20 healthy controls (HC). Method: We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE) was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM). Results: The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. Conclusions: This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss. PMID:27807415

Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning.

PubMed

Wang, Shuihua; Yang, Ming; Du, Sidan; Yang, Jiquan; Liu, Bin; Gorriz, Juan M; Ramírez, Javier; Yuan, Ti-Fei; Zhang, Yudong

2016-01-01

Highlights We develop computer-aided diagnosis system for unilateral hearing loss detection in structural magnetic resonance imaging.Wavelet entropy is introduced to extract image global features from brain images. Directed acyclic graph is employed to endow support vector machine an ability to handle multi-class problems.The developed computer-aided diagnosis system achieves an overall accuracy of 95.1% for this three-class problem of differentiating left-sided and right-sided hearing loss from healthy controls. Aim: Sensorineural hearing loss (SNHL) is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. Materials: We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany). The subjects contain 14 patients with right-sided hearing loss (RHL), 15 patients with left-sided hearing loss (LHL), and 20 healthy controls (HC). Method: We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE) was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM). Results: The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. Conclusions: This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss.

Sparse Representation of Multimodality Sensing Databases for Data Mining and Retrieval

DTIC Science & Technology

2015-04-09

Savarese. Estimating the Aspect Layout of Object Categories, EEE Conference on Computer Vision and Pattern Recognition (CVPR). 19-JUN-12...Time Equivalent (FTE) support provided by this agreement, and total for each category): (a) Graduate Students Liang Mei, 50% FTE, EE : systems...PhD candidate Min Sun, 50% FTE, EE : systems, PhD candidate Yu Xiang, 50% FTE, EE : systems, PhD candidate Dae Yon Jung, 50% FTE, EE : systems, PhD

Topographic Mapping of Residual Vision by Computer

ERIC Educational Resources Information Center

MacKeben, Manfred

2008-01-01

Many persons with low vision have diseases that damage the retina only in selected areas, which can lead to scotomas (blind spots) in perception. The most frequent of these diseases is age-related macular degeneration (AMD), in which foveal vision is often impaired by a central scotoma that impairs vision of fine detail and causes problems with…

HALO: a reconfigurable image enhancement and multisensor fusion system

NASA Astrophysics Data System (ADS)

Wu, F.; Hickman, D. L.; Parker, Steve J.

2014-06-01

Contemporary high definition (HD) cameras and affordable infrared (IR) imagers are set to dramatically improve the effectiveness of security, surveillance and military vision systems. However, the quality of imagery is often compromised by camera shake, or poor scene visibility due to inadequate illumination or bad atmospheric conditions. A versatile vision processing system called HALO™ is presented that can address these issues, by providing flexible image processing functionality on a low size, weight and power (SWaP) platform. Example processing functions include video distortion correction, stabilisation, multi-sensor fusion and image contrast enhancement (ICE). The system is based around an all-programmable system-on-a-chip (SoC), which combines the computational power of a field-programmable gate array (FPGA) with the flexibility of a CPU. The FPGA accelerates computationally intensive real-time processes, whereas the CPU provides management and decision making functions that can automatically reconfigure the platform based on user input and scene content. These capabilities enable a HALO™ equipped reconnaissance or surveillance system to operate in poor visibility, providing potentially critical operational advantages in visually complex and challenging usage scenarios. The choice of an FPGA based SoC is discussed, and the HALO™ architecture and its implementation are described. The capabilities of image distortion correction, stabilisation, fusion and ICE are illustrated using laboratory and trials data.

78 FR 16756 - Twenty-Second Meeting: RTCA Special Committee 213, Enhanced Flight Vision Systems/Synthetic...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-18

... Committee 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY: Federal Aviation... 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing..., Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held April...

78 FR 55774 - Twenty Fourth Meeting: RTCA Special Committee 213, Enhanced Flight Vision Systems/Synthetic...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-11

... Committee 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY: Federal Aviation... 213, Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing..., Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held October...

75 FR 17202 - Eighth Meeting: Joint RTCA Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-05

... Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY...-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY: The FAA is issuing...: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will be held April...

75 FR 44306 - Eleventh Meeting: Joint RTCA Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-28

... Committee 213: EUROCAE WG- 79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY... Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS... 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The...

75 FR 71183 - Twelfth Meeting: Joint RTCA Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-22

... Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS) AGENCY... Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). SUMMARY...: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS). DATES: The meeting will...

The Effect of the Usage of Computer-Based Assistive Devices on the Functioning and Quality of Life of Individuals Who Are Blind or Have Low Vision

ERIC Educational Resources Information Center

Rosner, Yotam; Perlman, Amotz

2018-01-01

Introduction: The Israel Ministry of Social Affairs and Social Services subsidizes computer-based assistive devices for individuals with visual impairments (that is, those who are blind or have low vision) to assist these individuals in their interactions with computers and thus to enhance their independence and quality of life. The aim of this…

Software for Real-Time Analysis of Subsonic Test Shot Accuracy

DTIC Science & Technology

2014-03-01

used the C++ programming language, the Open Source Computer Vision ( OpenCV ®) software library, and Microsoft Windows® Application Programming...video for comparison through OpenCV image analysis tools. Based on the comparison, the software then computed the coordinates of each shot relative to...DWB researchers wanted to use the Open Source Computer Vision ( OpenCV ) software library for capturing and analyzing frames of video. OpenCV contains

Intelligent surgical laser system configuration and software implementation

NASA Astrophysics Data System (ADS)

Hsueh, Chi-Fu T.; Bille, Josef F.

1992-06-01

An intelligent surgical laser system, which can help the ophthalmologist to achieve higher precision and control during their procedures, has been developed by ISL as model CLS 4001. In addition to the laser and laser delivery system, the system is also equipped with a vision system (IPU), robotics motion control (MCU), and a tracking closed loop system (ETS) that tracks the eye in three dimensions (X, Y and Z). The initial patient setup is computer controlled with guidance from the vision system. The tracking system is automatically engaged when the target is in position. A multi-level tracking system is developed by integrating our vision and tracking systems which have been able to maintain our laser beam precisely on target. The capabilities of the automatic eye setup and the tracking in three dimensions provides for improved accuracy and measurement repeatability. The system is operated through the Surgical Control Unit (SCU). The SCU communicates with the IPU and the MCU through both ethernet and RS232. Various scanning pattern (i.e., line, curve, circle, spiral, etc.) can be selected with given parameters. When a warning is activated, a voice message is played that will normally require a panel touch acknowledgement. The reliability of the system is ensured in three levels: (1) hardware, (2) software real time monitoring, and (3) user. The system is currently under clinical validation.

[Ophthalmologist and "computer vision syndrome"].

PubMed

Barar, A; Apatachioaie, Ioana Daniela; Apatachioaie, C; Marceanu-Brasov, L

2007-01-01

The authors had tried to collect the data available on the Internet about a subject that we consider as being totally ignored in the Romanian scientific literature and unexpectedly insufficiently treated in the specialized ophthalmologic literature. Known in the specialty literature under the generic name of "Computer vision syndrome", it is defined by the American Optometric Association as a complex of eye and vision problems related to the activities which stress the near vision and which are experienced in relation, or during, the use of the computer. During the consultations we hear frequent complaints of eye-strain - asthenopia, headaches, blurred distance and/or near vision, dry and irritated eyes, slow refocusing, neck and backache, photophobia, sensation of diplopia, light sensitivity, and double vision, but because of the lack of information, we overlooked them too easily, without going thoroughly into the real motives. In most of the developed countries, there are recommendations issued by renowned medical associations with regard to the definition, the diagnosis, and the methods for the prevention, treatment and periodical control of the symptoms found in computer users, in conjunction with an extremely detailed ergonomic legislation. We found out that these problems incite a much too low interest in our country. We would like to rouse the interest of our ophthalmologist colleagues in the understanding and the recognition of these symptoms and in their treatment, or at least their improvement, through specialized measures or through the cooperation with our specialist occupational medicine colleagues.

Metal surface corrosion grade estimation from single image

NASA Astrophysics Data System (ADS)

Chen, Yijun; Qi, Lin; Sun, Huyuan; Fan, Hao; Dong, Junyu

2018-04-01

Metal corrosion can cause many problems, how to quickly and effectively assess the grade of metal corrosion and timely remediation is a very important issue. Typically, this is done by trained surveyors at great cost. Assisting them in the inspection process by computer vision and artificial intelligence would decrease the inspection cost. In this paper, we propose a dataset of metal surface correction used for computer vision detection and present a comparison between standard computer vision techniques by using OpenCV and deep learning method for automatic metal surface corrosion grade estimation from single image on this dataset. The test has been performed by classifying images and calculating the accuracy for the two different approaches.

Apple flower detection using deep convolutional networks

USDA-ARS?s Scientific Manuscript database

In order to optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems...

Technology for Work, Home, and Leisure. Tech Use Guide: Using Computer Technology.

ERIC Educational Resources Information Center

Williams, John M.

This guide provides a brief introduction to several types of technological devices useful to individuals with disabilities and illustrates how some individuals are applying technology in the workplace and at home. Devices described include communication aids, low-vision products, voice-activated systems, environmental controls, and aids for…

Urban Terrain Modeling for Augmented Reality Applications

DTIC Science & Technology

2001-01-01

pointing ( Maybank -92). Almost all such systems are designed to extract the geometry of buildings and to texture these to provide models that can be... Maybank , S. and Faugeras, O. (1992). A Theory of Self-Calibration of a Moving Camera, International Journal of Computer Vision, 8(2):123-151

Digital Libraries--Methods and Applications

ERIC Educational Resources Information Center

Huang, Kuo Hung, Ed.

2011-01-01

Digital library is commonly seen as a type of information retrieval system which stores and accesses digital content remotely via computer networks. However, the vision of digital libraries is not limited to technology or management, but user experience. This book is an attempt to share the practical experiences of solutions to the operation of…

Smart Camera System for Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Delgado, Frank; White, Janis; Abernathy, Michael F.

2003-01-01

This paper describes a new approach to situation awareness that combines video sensor technology and synthetic vision technology in a unique fashion to create a hybrid vision system. Our implementation of the technology, called "SmartCam3D" (SC3D) has been flight tested by both NASA and the Department of Defense with excellent results. This paper details its development and flight test results. Windshields and windows add considerable weight and risk to vehicle design, and because of this, many future vehicles will employ a windowless cockpit design. This windowless cockpit design philosophy prompted us to look at what would be required to develop a system that provides crewmembers and awareness. The system created to date provides a real-time operations personnel an appropriate level of situation 3D perspective display that can be used during all-weather and visibility conditions. While the advantages of a synthetic vision only system are considerable, the major disadvantage of such a system is that it displays the synthetic scene created using "static" data acquired by an aircraft or satellite at some point in the past. The SC3D system we are presenting in this paper is a hybrid synthetic vision system that fuses live video stream information with a computer generated synthetic scene. This hybrid system can display a dynamic, real-time scene of a region of interest, enriched by information from a synthetic environment system, see figure 1. The SC3D system has been flight tested on several X-38 flight tests performed over the last several years and on an ARMY Unmanned Aerial Vehicle (UAV) ground control station earlier this year. Additional testing using an assortment of UAV ground control stations and UAV simulators from the Army and Air Force will be conducted later this year.

Optimizing virtual reality for all users through gaze-contingent and adaptive focus displays.

PubMed

Padmanaban, Nitish; Konrad, Robert; Stramer, Tal; Cooper, Emily A; Wetzstein, Gordon

2017-02-28

From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics. Current displays cannot reproduce the changes in focus that accompany natural vision, and they cannot support users with uncorrected refractive errors. With two prototype near-eye displays, we show how these issues can be overcome using display modes that adapt to the user via computational optics. By using focus-tunable lenses, mechanically actuated displays, and mobile gaze-tracking technology, these displays can be tailored to correct common refractive errors and provide natural focus cues by dynamically updating the system based on where a user looks in a virtual scene. Indeed, the opportunities afforded by recent advances in computational optics open up the possibility of creating a computing platform in which some users may experience better quality vision in the virtual world than in the real one.

Optimizing virtual reality for all users through gaze-contingent and adaptive focus displays

NASA Astrophysics Data System (ADS)

Padmanaban, Nitish; Konrad, Robert; Stramer, Tal; Cooper, Emily A.; Wetzstein, Gordon

2017-02-01

From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics. Current displays cannot reproduce the changes in focus that accompany natural vision, and they cannot support users with uncorrected refractive errors. With two prototype near-eye displays, we show how these issues can be overcome using display modes that adapt to the user via computational optics. By using focus-tunable lenses, mechanically actuated displays, and mobile gaze-tracking technology, these displays can be tailored to correct common refractive errors and provide natural focus cues by dynamically updating the system based on where a user looks in a virtual scene. Indeed, the opportunities afforded by recent advances in computational optics open up the possibility of creating a computing platform in which some users may experience better quality vision in the virtual world than in the real one.

Vision-based augmented reality system

NASA Astrophysics Data System (ADS)

Chen, Jing; Wang, Yongtian; Shi, Qi; Yan, Dayuan

2003-04-01

The most promising aspect of augmented reality lies in its ability to integrate the virtual world of the computer with the real world of the user. Namely, users can interact with the real world subjects and objects directly. This paper presents an experimental augmented reality system with a video see-through head-mounted device to display visual objects, as if they were lying on the table together with real objects. In order to overlay virtual objects on the real world at the right position and orientation, the accurate calibration and registration are most important. A vision-based method is used to estimate CCD external parameters by tracking 4 known points with different colors. It achieves sufficient accuracy for non-critical applications such as gaming, annotation and so on.

A comparison of symptoms after viewing text on a computer screen and hardcopy.

PubMed

Chu, Christina; Rosenfield, Mark; Portello, Joan K; Benzoni, Jaclyn A; Collier, Juanita D

2011-01-01

Computer vision syndrome (CVS) is a complex of eye and vision problems experienced during or related to computer use. Ocular symptoms may include asthenopia, accommodative and vergence difficulties and dry eye. CVS occurs in up to 90% of computer workers, and given the almost universal use of these devices, it is important to identify whether these symptoms are specific to computer operation, or are simply a manifestation of performing a sustained near-vision task. This study compared ocular symptoms immediately following a sustained near task. 30 young, visually-normal subjects read text aloud either from a desktop computer screen or a printed hardcopy page at a viewing distance of 50 cm for a continuous 20 min period. Identical text was used in the two sessions, which was matched for size and contrast. Target viewing angle and luminance were similar for the two conditions. Immediately following completion of the reading task, subjects completed a written questionnaire asking about their level of ocular discomfort during the task. When comparing the computer and hardcopy conditions, significant differences in median symptom scores were reported with regard to blurred vision during the task (t = 147.0; p = 0.03) and the mean symptom score (t = 102.5; p = 0.04). In both cases, symptoms were higher during computer use. Symptoms following sustained computer use were significantly worse than those reported after hard copy fixation under similar viewing conditions. A better understanding of the physiology underlying CVS is critical to allow more accurate diagnosis and treatment. This will allow practitioners to optimize visual comfort and efficiency during computer operation.

76 FR 11847 - Thirteenth Meeting: Joint RTCA Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-03

... Special Committee 213: EUROCAE WG- 79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS... Joint RTCA Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems... Special Committee 213: EUROCAE WG-79: Enhanced Flight Vision Systems/Synthetic Vision Systems (EFVS/SVS...