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.

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.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Camera calibration method of binocular stereo vision based on OpenCV

NASA Astrophysics Data System (ADS)

Zhong, Wanzhen; Dong, Xiaona

2015-10-01

Camera calibration, an important part of the binocular stereo vision research, is the essential foundation of 3D reconstruction of the spatial object. In this paper, the camera calibration method based on OpenCV (open source computer vision library) is submitted to make the process better as a result of obtaining higher precision and efficiency. First, the camera model in OpenCV and an algorithm of camera calibration are presented, especially considering the influence of camera lens radial distortion and decentering distortion. Then, camera calibration procedure is designed to compute those parameters of camera and calculate calibration errors. High-accurate profile extraction algorithm and a checkboard with 48 corners have also been used in this part. Finally, results of calibration program are presented, demonstrating the high efficiency and accuracy of the proposed approach. The results can reach the requirement of robot binocular stereo vision.

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.

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.

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.

From Image Analysis to Computer Vision: Motives, Methods, and Milestones.

DTIC Science & Technology

1998-07-01

images. Initially, work on digital image analysis dealt with specific classes of images such as text, photomicrographs, nuclear particle tracks, and aerial...photographs; but by the 1960’s, general algorithms and paradigms for image analysis began to be formulated. When the artificial intelligence...scene, but eventually from image sequences obtained by a moving camera; at this stage, image analysis had become scene analysis or computer vision

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.

Computational gestalts and perception thresholds.

PubMed

Desolneux, Agnès; Moisan, Lionel; Morel, Jean-Michel

2003-01-01

In 1923, Max Wertheimer proposed a research programme and method in visual perception. He conjectured the existence of a small set of geometric grouping laws governing the perceptual synthesis of phenomenal objects, or "gestalt" from the atomic retina input. In this paper, we review this set of geometric grouping laws, using the works of Metzger, Kanizsa and their schools. In continuation, we explain why the Gestalt theory research programme can be translated into a Computer Vision programme. This translation is not straightforward, since Gestalt theory never addressed two fundamental matters: image sampling and image information measurements. Using these advances, we shall show that gestalt grouping laws can be translated into quantitative laws allowing the automatic computation of gestalts in digital images. From the psychophysical viewpoint, a main issue is raised: the computer vision gestalt detection methods deliver predictable perception thresholds. Thus, we are set in a position where we can build artificial images and check whether some kind of agreement can be found between the computationally predicted thresholds and the psychophysical ones. We describe and discuss two preliminary sets of experiments, where we compared the gestalt detection performance of several subjects with the predictable detection curve. In our opinion, the results of this experimental comparison support the idea of a much more systematic interaction between computational predictions in Computer Vision and psychophysical experiments.

Computational approaches to vision

NASA Technical Reports Server (NTRS)

Barrow, H. G.; Tenenbaum, J. M.

1986-01-01

Vision is examined in terms of a computational process, and the competence, structure, and control of computer vision systems are analyzed. Theoretical and experimental data on the formation of a computer vision system are discussed. Consideration is given to early vision, the recovery of intrinsic surface characteristics, higher levels of interpretation, and system integration and control. A computational visual processing model is proposed and its architecture and operation are described. Examples of state-of-the-art vision systems, which include some of the levels of representation and processing mechanisms, are presented.

A method of non-contact reading code based on computer vision

NASA Astrophysics Data System (ADS)

Zhang, Chunsen; Zong, Xiaoyu; Guo, Bingxuan

2018-03-01

With the purpose of guarantee the computer information exchange security between internal and external network (trusted network and un-trusted network), A non-contact Reading code method based on machine vision has been proposed. Which is different from the existing network physical isolation method. By using the computer monitors, camera and other equipment. Deal with the information which will be on exchanged, Include image coding ,Generate the standard image , Display and get the actual image , Calculate homography matrix, Image distort correction and decoding in calibration, To achieve the computer information security, Non-contact, One-way transmission between the internal and external network , The effectiveness of the proposed method is verified by experiments on real computer text data, The speed of data transfer can be achieved 24kb/s. The experiment shows that this algorithm has the characteristics of high security, fast velocity and less loss of information. Which can meet the daily needs of the confidentiality department to update the data effectively and reliably, Solved the difficulty of computer information exchange between Secret network and non-secret network, With distinctive originality, practicability, and practical research value.

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.

The research of edge extraction and target recognition based on inherent feature of objects

NASA Astrophysics Data System (ADS)

Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

2008-03-01

Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots fields. The results of simulation experiments and theory analyzing demonstrate that the proposed method could suppress noise effectively, extracted target edges robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

Recent advances in the development and transfer of machine vision technologies for space

NASA Technical Reports Server (NTRS)

Defigueiredo, Rui J. P.; Pendleton, Thomas

1991-01-01

Recent work concerned with real-time machine vision is briefly reviewed. This work includes methodologies and techniques for optimal illumination, shape-from-shading of general (non-Lambertian) 3D surfaces, laser vision devices and technology, high level vision, sensor fusion, real-time computing, artificial neural network design and use, and motion estimation. Two new methods that are currently being developed for object recognition in clutter and for 3D attitude tracking based on line correspondence are discussed.

The Event Detection and the Apparent Velocity Estimation Based on Computer Vision

NASA Astrophysics Data System (ADS)

Shimojo, M.

2012-08-01

The high spatial and time resolution data obtained by the telescopes aboard Hinode revealed the new interesting dynamics in solar atmosphere. In order to detect such events and estimate the velocity of dynamics automatically, we examined the estimation methods of the optical flow based on the OpenCV that is the computer vision library. We applied the methods to the prominence eruption observed by NoRH, and the polar X-ray jet observed by XRT. As a result, it is clear that the methods work well for solar images if the images are optimized for the methods. It indicates that the optical flow estimation methods in the OpenCV library are very useful to analyze the solar phenomena.

Computer vision uncovers predictors of physical urban change.

PubMed

Naik, Nikhil; Kominers, Scott Duke; Raskar, Ramesh; Glaeser, Edward L; Hidalgo, César A

2017-07-18

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements-an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements-an observation that is consistent with "tipping" theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods-an observation that is consistent with the "invasion" theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities.

Computer vision uncovers predictors of physical urban change

PubMed Central

Naik, Nikhil; Kominers, Scott Duke; Raskar, Ramesh; Glaeser, Edward L.; Hidalgo, César A.

2017-01-01

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements—an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements—an observation that is consistent with “tipping” theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods—an observation that is consistent with the “invasion” theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities. PMID:28684401

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.

Illumination-based synchronization of high-speed vision sensors.

PubMed

Hou, Lei; Kagami, Shingo; Hashimoto, Koichi

2010-01-01

To acquire images of dynamic scenes from multiple points of view simultaneously, the acquisition time of vision sensors should be synchronized. This paper describes an illumination-based synchronization method derived from the phase-locked loop (PLL) algorithm. Incident light to a vision sensor from an intensity-modulated illumination source serves as the reference signal for synchronization. Analog and digital computation within the vision sensor forms a PLL to regulate the output signal, which corresponds to the vision frame timing, to be synchronized with the reference. Simulated and experimental results show that a 1,000 Hz frame rate vision sensor was successfully synchronized with 32 μs jitters.

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.

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

Quality Parameters of Six Cultivars of Blueberry Using Computer Vision

PubMed Central

Celis Cofré, Daniela; Silva, Patricia; Enrione, Javier; Osorio, Fernando

2013-01-01

Background. Blueberries are considered an important source of health benefits. This work studied six blueberry cultivars: “Duke,” “Brigitta”, “Elliott”, “Centurion”, “Star,” and “Jewel”, measuring quality parameters such as °Brix, pH, moisture content using standard techniques and shape, color, and fungal presence obtained by computer vision. The storage conditions were time (0–21 days), temperature (4 and 15°C), and relative humidity (75 and 90%). Results. Significant differences (P < 0.05) were detected between fresh cultivars in pH, °Brix, shape, and color. However, the main parameters which changed depending on storage conditions, increasing at higher temperature, were color (from blue to red) and fungal presence (from 0 to 15%), both detected using computer vision, which is important to determine a shelf life of 14 days for all cultivars. Similar behavior during storage was obtained for all cultivars. Conclusion. Computer vision proved to be a reliable and simple method to objectively determine blueberry decay during storage that can be used as an alternative approach to currently used subjective measurements. PMID:26904598

Perceptual organization in computer vision - A review and a proposal for a classificatory structure

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1993-01-01

The evolution of perceptual organization in biological vision, and its necessity in advanced computer vision systems, arises from the characteristic that perception, the extraction of meaning from sensory input, is an intelligent process. This is particularly so for high order organisms and, analogically, for more sophisticated computational models. The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. First, a brief history of perceptual organization research in both humans and computer vision is offered. Next, a classificatory structure in which to cast perceptual organization research to clarify both the nomenclature and the relationships among the many contributions is proposed. Thirdly, the perceptual organization work in computer vision in the context of this classificatory structure is reviewed. Finally, the array of computational techniques applied to perceptual organization problems in computer vision is surveyed.

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.

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.

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.

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.

[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.

Modern Approaches to the Computation of the Probability of Target Detection in Cluttered Environments

NASA Astrophysics Data System (ADS)

Meitzler, Thomas J.

The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.

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.

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.

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.

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.

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.

Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

NASA Technical Reports Server (NTRS)

Smith, Phillip N.

1990-01-01

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

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

Global Methods for Image Motion Analysis

DTIC Science & Technology

1992-10-01

a variant of the same error function as in Adiv [2]. Another related approach was presented by Maybank [46,45]. Nearly all researchers in motion...with an application to stereo vision. In Proc. 7th Intern. Joint Conference on AI, pages 674{679, Vancouver, 1981. [45] S. J. Maybank . Algorithm for...analysing optical ow based on the least-squares method. Image and Vision Computing, 4:38{42, 1986. [46] S. J. Maybank . A Theoretical Study of Optical

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.

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.

(Computer) Vision without Sight

PubMed Central

Manduchi, Roberto; Coughlan, James

2012-01-01

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs of the VI population and which of these needs might be addressed by computer vision. This article reviews the types of assistive technology application areas that have already been developed for VI, and the possible roles that computer vision can play in facilitating these applications. We discuss how appropriate user interfaces are designed to translate the output of computer vision algorithms into information that the user can quickly and safely act upon, and how system-level characteristics affect the overall usability of an assistive technology. Finally, we conclude by highlighting a few novel and intriguing areas of application of computer vision to assistive technology. PMID:22815563

Microscope self-calibration based on micro laser line imaging and soft computing algorithms

NASA Astrophysics Data System (ADS)

Apolinar Muñoz Rodríguez, J.

2018-06-01

A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.

Fuzzy classification for strawberry diseases-infection using machine vision and soft-computing techniques

NASA Astrophysics Data System (ADS)

Altıparmak, Hamit; Al Shahadat, Mohamad; Kiani, Ehsan; Dimililer, Kamil

2018-04-01

Robotic agriculture requires smart and doable techniques to substitute the human intelligence with machine intelligence. Strawberry is one of the important Mediterranean product and its productivity enhancement requires modern and machine-based methods. Whereas a human identifies the disease infected leaves by his eye, the machine should also be capable of vision-based disease identification. The objective of this paper is to practically verify the applicability of a new computer-vision method for discrimination between the healthy and disease infected strawberry leaves which does not require neural network or time consuming trainings. The proposed method was tested under outdoor lighting condition using a regular DLSR camera without any particular lens. Since the type and infection degree of disease is approximated a human brain a fuzzy decision maker classifies the leaves over the images captured on-site having the same properties of human vision. Optimizing the fuzzy parameters for a typical strawberry production area at a summer mid-day in Cyprus produced 96% accuracy for segmented iron deficiency and 93% accuracy for segmented using a typical human instant classification approximation as the benchmark holding higher accuracy than a human eye identifier. The fuzzy-base classifier provides approximate result for decision making on the leaf status as if it is healthy or not.

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.

A method of detection to the grinding wheel layer thickness based on computer vision

NASA Astrophysics Data System (ADS)

Ji, Yuchen; Fu, Luhua; Yang, Dujuan; Wang, Lei; Liu, Changjie; Wang, Zhong

2018-01-01

This paper proposed a method of detection to the grinding wheel layer thickness based on computer vision. A camera is used to capture images of grinding wheel layer on the whole circle. Forward lighting and back lighting are used to enables a clear image to be acquired. Image processing is then executed on the images captured, which consists of image preprocessing, binarization and subpixel subdivision. The aim of binarization is to help the location of a chord and the corresponding ring width. After subpixel subdivision, the thickness of the grinding layer can be calculated finally. Compared with methods usually used to detect grinding wheel wear, method in this paper can directly and quickly get the information of thickness. Also, the eccentric error and the error of pixel equivalent are discussed in this paper.

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.

Computer Vision Techniques for Transcatheter Intervention

PubMed Central

Zhao, Feng; Roach, Matthew

2015-01-01

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and the treatment of cardiovascular diseases. For example, transcatheter aortic valve implantation is an alternative to aortic valve replacement for the treatment of severe aortic stenosis, and transcatheter atrial fibrillation ablation is widely used for the treatment and the cure of atrial fibrillation. In addition, catheter-based intravascular ultrasound and optical coherence tomography imaging of coronary arteries provides important information about the coronary lumen, wall, and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial to the evaluation and the treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation and motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods. We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence, it is important to understand the application domain, clinical background, and imaging modality, so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on the background information of the transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area. PMID:27170893

People with Hemianopia Report Difficulty with TV, Computer, Cinema Use, and Photography.

PubMed

Costela, Francisco M; Sheldon, Sarah S; Walker, Bethany; Woods, Russell L

2018-05-01

Our survey found that participants with hemianopia report more difficulties watching video in various formats, including television (TV), on computers, and in a movie theater, compared with participants with normal vision (NV). These reported difficulties were not as marked as those reported by people with central vision loss. The aim of this study was to survey the viewing experience (e.g., frequency, difficulty) of viewing video on TV, computers and portable visual display devices, and at the cinema of people with hemianopia and NV. This information may guide vision rehabilitation. We administered a cross-sectional survey to investigate the viewing habits of people with hemianopia (n = 91) or NV (n = 192). The survey, consisting of 22 items, was administered either in person or in a telephone interview. Descriptive statistics are reported. There were five major differences between the hemianopia and NV groups. Many participants with hemianopia reported (1) at least "some" difficulty watching TV (39/82); (2) at least "some" difficulty watching video on a computer (16/62); (3) never attending the cinema (30/87); (4) at least some difficulty watching movies in the cinema (20/56), among those who did attend the cinema; and (5) never taking photographs (24/80). Some people with hemianopia reported methods that they used to help them watch video, including video playback and head turn. Although people with hemianopia report more difficulty with viewing video on TV and at the cinema, we are not aware of any rehabilitation methods specifically designed to assist people with hemianopia to watch video. The results of this survey may guide future vision rehabilitation.

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.

A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

NASA Astrophysics Data System (ADS)

Hannachi, Ammar; Kohler, Sophie; Lallement, Alex; Hirsch, Ernest

2015-04-01

3D modeling of scene contents takes an increasing importance for many computer vision based applications. In particular, industrial applications of computer vision require efficient tools for the computation of this 3D information. Routinely, stereo-vision is a powerful technique to obtain the 3D outline of imaged objects from the corresponding 2D images. As a consequence, this approach provides only a poor and partial description of the scene contents. On another hand, for structured light based reconstruction techniques, 3D surfaces of imaged objects can often be computed with high accuracy. However, the resulting active range data in this case lacks to provide data enabling to characterize the object edges. Thus, in order to benefit from the positive points of various acquisition techniques, we introduce in this paper promising approaches, enabling to compute complete 3D reconstruction based on the cooperation of two complementary acquisition and processing techniques, in our case stereoscopic and structured light based methods, providing two 3D data sets describing respectively the outlines and surfaces of the imaged objects. We present, accordingly, the principles of three fusion techniques and their comparison based on evaluation criterions related to the nature of the workpiece and also the type of the tackled application. The proposed fusion methods are relying on geometric characteristics of the workpiece, which favour the quality of the registration. Further, the results obtained demonstrate that the developed approaches are well adapted for 3D modeling of manufactured parts including free-form surfaces and, consequently quality control applications using these 3D reconstructions.

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.

Landmark-aided localization for air vehicles using learned object detectors

NASA Astrophysics Data System (ADS)

DeAngelo, Mark Patrick

This research presents two methods to localize an aircraft without GPS using fixed landmarks observed from an optical sensor. Onboard absolute localization is useful for vehicle navigation free from an external network. The objective is to achieve practical navigation performance using available autopilot hardware and a downward pointing camera. The first method uses computer vision cascade object detectors, which are trained to detect predetermined, distinct landmarks prior to a flight. The first method also concurrently explores aircraft localization using roads between landmark updates. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement updates when landmarks are detected. The sensor measurements and landmark coordinates extracted from the aircraft's camera images are combined into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities. The second method uses computer vision object detectors to detect abundant generic landmarks referred as buildings, fields, trees, and road intersections from aerial perspectives. Various landmark attributes and spatial relationships to other landmarks are used to help associate observed landmarks with reference landmarks. The computer vision algorithms automatically extract reference landmarks from maps, which are processed offline before a flight. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement corrections by processing aerial photos with similar generic landmark detection techniques. The method also combines sensor measurements and landmark coordinates into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities.

Pyramidal neurovision architecture for vision machines

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1993-08-01

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

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...

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.

[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.

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

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.

Vision-based calibration of parallax barrier displays

NASA Astrophysics Data System (ADS)

Ranieri, Nicola; Gross, Markus

2014-03-01

Static and dynamic parallax barrier displays became very popular over the past years. Especially for single viewer applications like tablets, phones and other hand-held devices, parallax barriers provide a convenient solution to render stereoscopic content. In our work we present a computer vision based calibration approach to relate image layer and barrier layer of parallax barrier displays with unknown display geometry for static or dynamic viewer positions using homographies. We provide the math and methods to compose the required homographies on the fly and present a way to compute the barrier without the need of any iteration. Our GPU implementation is stable and general and can be used to reduce latency and increase refresh rate of existing and upcoming barrier methods.

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.

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.

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

Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

NASA Astrophysics Data System (ADS)

Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

1989-03-01

The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

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

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi

1989-01-01

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

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.

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.

Iris features-based heart disease diagnosis by computer vision

NASA Astrophysics Data System (ADS)

Nguchu, Benedictor A.; Li, Li

2017-07-01

The study takes advantage of several new breakthroughs in computer vision technology to develop a new mid-irisbiomedical platform that processes iris image for early detection of heart-disease. Guaranteeing early detection of heart disease provides a possibility of having non-surgical treatment as suggested by biomedical researchers and associated institutions. However, our observation discovered that, a clinical practicable solution which could be both sensible and specific for early detection is still lacking. Due to this, the rate of majority vulnerable to death is highly increasing. The delayed diagnostic procedures, inefficiency, and complications of available methods are the other reasons for this catastrophe. Therefore, this research proposes the novel IFB (Iris Features Based) method for diagnosis of premature, and early stage heart disease. The method incorporates computer vision and iridology to obtain a robust, non-contact, nonradioactive, and cost-effective diagnostic tool. The method analyzes abnormal inherent weakness in tissues, change in color and patterns, of a specific region of iris that responds to impulses of heart organ as per Bernard Jensen-iris Chart. The changes in iris infer the presence of degenerative abnormalities in heart organ. These changes are precisely detected and analyzed by IFB method that includes, tensor-based-gradient(TBG), multi orientations gabor filters(GF), textural oriented features(TOF), and speed-up robust features(SURF). Kernel and Multi class oriented support vector machines classifiers are used for classifying normal and pathological iris features. Experimental results demonstrated that the proposed method, not only has better diagnostic performance, but also provides an insight for early detection of other diseases.

Computer vision for foreign body detection and removal in the food industry

USDA-ARS?s Scientific Manuscript database

Computer vision inspection systems are often used for quality control, product grading, defect detection and other product evaluation issues. This chapter focuses on the use of computer vision inspection systems that detect foreign bodies and remove them from the product stream. Specifically, we wi...

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 ...

Laser speckle imaging for lesion detection on tooth

NASA Astrophysics Data System (ADS)

Gavinho, Luciano G.; Silva, João. V. P.; Damazio, João. H.; Sfalcin, Ravana A.; Araujo, Sidnei A.; Pinto, Marcelo M.; Olivan, Silvia R. G.; Prates, Renato A.; Bussadori, Sandra K.; Deana, Alessandro M.

2018-02-01

Computer vision technologies for diagnostic imaging applied to oral lesions, specifically, carious lesions of the teeth, are in their early years of development. The relevance of this public problem, dental caries, worries countries around the world, as it affects almost the entire population, at least once in the life of each individual. The present work demonstrates current techniques for obtaining information about lesions on teeth by segmentation laser speckle imagens (LSI). Laser speckle image results from laser light reflection on a rough surface, and it was considered a noise but has important features that carry information about the illuminated surface. Even though these are basic images, only a few works have analyzed it by application of computer vision methods. In this article, we present the latest results of our group, in which Computer vision techniques were adapted to segment laser speckle images for diagnostic purposes. These methods are applied to the segmentation of images between healthy and lesioned regions of the tooth. These methods have proven to be effective in the diagnosis of early-stage lesions, often imperceptible in traditional diagnostic methods in the clinical practice. The first method uses first-order statistical models, segmenting the image by comparing the mean and standard deviation of the intensity of the pixels. The second method is based on the distance of the chi-square (χ2 ) between the histograms of the image, bringing a significant improvement in the precision of the diagnosis, while a third method introduces the use of fractal geometry, exposing, through of the fractal dimension, more precisely the difference between lesioned areas and healthy areas of a tooth compared to other methods of segmentation. So far, we can observe efficiency in the segmentation of the carious regions. A software was developed for the execution and demonstration of the applicability of the models

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.

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

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.

Hyperbolic Harmonic Mapping for Surface Registration

PubMed Central

Shi, Rui; Zeng, Wei; Su, Zhengyu; Jiang, Jian; Damasio, Hanna; Lu, Zhonglin; Wang, Yalin; Yau, Shing-Tung; Gu, Xianfeng

2016-01-01

Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture inducstries. Although numerous studies have been devoted to harmonic map research, limited progress has been made to compute a diffeomorphic harmonic map on general topology surfaces with landmark constraints. This work conquers this problem by changing the Riemannian metric on the target surface to a hyperbolic metric so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints. The computational algorithms are based on Ricci flow and nonlinear heat diffusion methods. The approach is general and robust. We employ our algorithm to study the constrained surface registration problem which applies to both computer vision and medical imaging applications. Experimental results demonstrate that, by changing the Riemannian metric, the registrations are always diffeomorphic and achieve relatively high performance when evaluated with some popular surface registration evaluation standards. PMID:27187948

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.

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.

VibroCV: a computer vision-based vibroarthrography platform with possible application to Juvenile Idiopathic Arthritis.

PubMed

Wiens, Andrew D; Prahalad, Sampath; Inan, Omer T

2016-08-01

Vibroarthrography, a method for interpreting the sounds emitted by a knee during movement, has been studied for several joint disorders since 1902. However, to our knowledge, the usefulness of this method for management of Juvenile Idiopathic Arthritis (JIA) has not been investigated. To study joint sounds as a possible new biomarker for pediatric cases of JIA we designed and built VibroCV, a platform to capture vibroarthrograms from four accelerometers; electromyograms (EMG) and inertial measurements from four wireless EMG modules; and joint angles from two Sony Eye cameras and six light-emitting diodes with commercially-available off-the-shelf parts and computer vision via OpenCV. This article explains the design of this turn-key platform in detail, and provides a sample recording captured from a pediatric subject.

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.

Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision

PubMed Central

Zupanc, Jernej; Drašler, Barbara; Boljte, Sabina; Kralj-Iglič, Veronika; Iglič, Aleš; Erdogmus, Deniz; Drobne, Damjana

2014-01-01

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscopy and enables non-destructive analysis of vesicles from suspensions containing up to several thousands of lipid vesicles (1–50 µm in diameter). For each sample, image analysis was employed to extract data on vesicle quantity and size distributions of their projected diameters and isoperimetric quotients (measure of contour roundness). This process enables a comparison of samples from the same population over time, or the comparison of a treated population to a control. Although vesicles in suspensions are heterogeneous in sizes and shapes and have distinctively non-homogeneous distribution throughout the suspension, this method allows for the capture and analysis of repeatable vesicle samples that are representative of the population inspected. PMID:25426933

Computer Vision Syndrome and Associated Factors Among Medical and Engineering Students in Chennai

PubMed Central

Logaraj, M; Madhupriya, V; Hegde, SK

2014-01-01

Background: Almost all institutions, colleges, universities and homes today were using computer regularly. Very little research has been carried out on Indian users especially among college students the effects of computer use on the eye and vision related problems. Aim: The aim of this study was to assess the prevalence of computer vision syndrome (CVS) among medical and engineering students and the factors associated with the same. Subjects and Methods: A cross-sectional study was conducted among medical and engineering college students of a University situated in the suburban area of Chennai. Students who used computer in the month preceding the date of study were included in the study. The participants were surveyed using pre-tested structured questionnaire. Results: Among engineering students, the prevalence of CVS was found to be 81.9% (176/215) while among medical students; it was found to be 78.6% (158/201). A significantly higher proportion of engineering students 40.9% (88/215) used computers for 4-6 h/day as compared to medical students 10% (20/201) (P < 0.001). The reported symptoms of CVS were higher among engineering students compared with medical students. Students who used computer for 4-6 h were at significantly higher risk of developing redness (OR = 1.2, 95% CI = 1.0-3.1,P = 0.04), burning sensation (OR = 2.1,95% CI = 1.3-3.1, P < 0.01) and dry eyes (OR = 1.8, 95% CI = 1.1-2.9, P = 0.02) compared to those who used computer for less than 4 h. Significant correlation was found between increased hours of computer use and the symptoms redness, burning sensation, blurred vision and dry eyes. Conclusion: The present study revealed that more than three-fourth of the students complained of any one of the symptoms of CVS while working on the computer. PMID:24761234

Deep Learning: A Primer for Radiologists.

PubMed

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

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.

3-D Signal Processing in a Computer Vision System

Treesearch

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

1991-01-01

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

An overview of computer vision

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An overview of computer vision is provided. Image understanding and scene analysis are emphasized, and pertinent aspects of pattern recognition are treated. The basic approach to computer vision systems, the techniques utilized, applications, the current existing systems and state-of-the-art issues and research requirements, who is doing it and who is funding it, and future trends and expectations are reviewed.

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…

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Detecting Motion from a Moving Platform; Phase 3: Unification of Control and Sensing for More Advanced Situational Awareness

DTIC Science & Technology

2011-11-01

RX-TY-TR-2011-0096-01) develops a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica...01 summarizes the development of a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica

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

A Review on Making Things See: Augmented Reality for Futuristic Virtual Educator

ERIC Educational Resources Information Center

Iqbal, Javid; Sidhu, Manjit Singh

2017-01-01

In the past few years many choreographers have focused upon implementation of computer technology to enhance their artistic skills. Computer vision technology presents new methods for learning, instructing, developing, and assessing physical movements as well as provides scope to expand dance resources and rediscover the learning process. This…

Geometric Variational Methods for Controlled Active Vision

DTIC Science & Technology

2006-08-01

Haker , L. Zhu, and A. Tannenbaum, ``Optimal mass transport for registration and warping’’ Int. Journal Computer Vision, volume 60, 2004, pp. 225-240. G...pp. 119-142. A. Angenent, S. Haker , and A. Tannenbaum, ``Minimizing flows for the Monge-Kantorovich problem,’’ SIAM J. Math. Analysis, volume 35...Shape analysis of structures using spherical wavelets’’ (with S. Haker and D. Nain), Proceeedings of MICCAI, 2005. ``Affine surface evolution for 3D

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.

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

Wide baseline stereo matching based on double topological relationship consistency

NASA Astrophysics Data System (ADS)

Zou, Xiaohong; Liu, Bin; Song, Xiaoxue; Liu, Yang

2009-07-01

Stereo matching is one of the most important branches in computer vision. In this paper, an algorithm is proposed for wide-baseline stereo vision matching. Here, a novel scheme is presented called double topological relationship consistency (DCTR). The combination of double topological configuration includes the consistency of first topological relationship (CFTR) and the consistency of second topological relationship (CSTR). It not only sets up a more advanced model on matching, but discards mismatches by iteratively computing the fitness of the feature matches and overcomes many problems of traditional methods depending on the powerful invariance to changes in the scale, rotation or illumination across large view changes and even occlusions. Experimental examples are shown where the two cameras have been located in very different orientations. Also, epipolar geometry can be recovered using RANSAC by far the most widely method adopted possibly. By the method, we can obtain correspondences with high precision on wide baseline matching problems. Finally, the effectiveness and reliability of this method are demonstrated in wide-baseline experiments on the image pairs.

Computational Analysis of Behavior.

PubMed

Egnor, S E Roian; Branson, Kristin

2016-07-08

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

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.

Computer vision based nacre thickness measurement of Tahitian pearls

NASA Astrophysics Data System (ADS)

Loesdau, Martin; Chabrier, Sébastien; Gabillon, Alban

2017-03-01

The Tahitian Pearl is the most valuable export product of French Polynesia contributing with over 61 million Euros to more than 50% of the total export income. To maintain its excellent reputation on the international market, an obligatory quality control for every pearl deemed for exportation has been established by the local government. One of the controlled quality parameters is the pearls nacre thickness. The evaluation is currently done manually by experts that are visually analyzing X-ray images of the pearls. In this article, a computer vision based approach to automate this procedure is presented. Even though computer vision based approaches for pearl nacre thickness measurement exist in the literature, the very specific features of the Tahitian pearl, namely the large shape variety and the occurrence of cavities, have so far not been considered. The presented work closes the. Our method consists of segmenting the pearl from X-ray images with a model-based approach, segmenting the pearls nucleus with an own developed heuristic circle detection and segmenting possible cavities with region growing. Out of the obtained boundaries, the 2-dimensional nacre thickness profile can be calculated. A certainty measurement to consider imaging and segmentation imprecisions is included in the procedure. The proposed algorithms are tested on 298 manually evaluated Tahitian pearls, showing that it is generally possible to automatically evaluate the nacre thickness of Tahitian pearls with computer vision. Furthermore the results show that the automatic measurement is more precise and faster than the manual one.

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Progress in computer vision.

NASA Astrophysics Data System (ADS)

Jain, A. K.; Dorai, C.

Computer vision has emerged as a challenging and important area of research, both as an engineering and a scientific discipline. The growing importance of computer vision is evident from the fact that it was identified as one of the "Grand Challenges" and also from its prominent role in the National Information Infrastructure. While the design of a general-purpose vision system continues to be elusive machine vision systems are being used successfully in specific application elusive, machine vision systems are being used successfully in specific application domains. Building a practical vision system requires a careful selection of appropriate sensors, extraction and integration of information from available cues in the sensed data, and evaluation of system robustness and performance. The authors discuss and demonstrate advantages of (1) multi-sensor fusion, (2) combination of features and classifiers, (3) integration of visual modules, and (IV) admissibility and goal-directed evaluation of vision algorithms. The requirements of several prominent real world applications such as biometry, document image analysis, image and video database retrieval, and automatic object model construction offer exciting problems and new opportunities to design and evaluate vision algorithms.

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

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.

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.

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.

Supercomputers Of The Future

NASA Technical Reports Server (NTRS)

Peterson, Victor L.; Kim, John; Holst, Terry L.; Deiwert, George S.; Cooper, David M.; Watson, Andrew B.; Bailey, F. Ron

1992-01-01

Report evaluates supercomputer needs of five key disciplines: turbulence physics, aerodynamics, aerothermodynamics, chemistry, and mathematical modeling of human vision. Predicts these fields will require computer speed greater than 10(Sup 18) floating-point operations per second (FLOP's) and memory capacity greater than 10(Sup 15) words. Also, new parallel computer architectures and new structured numerical methods will make necessary speed and capacity available.

Evaluation of the Effectiveness of a Tablet Computer Application (App) in Helping Students with Visual Impairments Solve Mathematics Problems

ERIC Educational Resources Information Center

Beal, Carole R.; Rosenblum, L. Penny

2018-01-01

Introduction: The authors examined a tablet computer application (iPad app) for its effectiveness in helping students studying prealgebra to solve mathematical word problems. Methods: Forty-three visually impaired students (that is, those who are blind or have low vision) completed eight alternating mathematics units presented using their…

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.

Reconfigurable vision system for real-time applications

NASA Astrophysics Data System (ADS)

Torres-Huitzil, Cesar; Arias-Estrada, Miguel

2002-03-01

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

Computer-Aided Evaluation of Blood Vessel Geometry From Acoustic Images.

PubMed

Lindström, Stefan B; Uhlin, Fredrik; Bjarnegård, Niclas; Gylling, Micael; Nilsson, Kamilla; Svensson, Christina; Yngman-Uhlin, Pia; Länne, Toste

2018-04-01

A method for computer-aided assessment of blood vessel geometries based on shape-fitting algorithms from metric vision was evaluated. Acoustic images of cross sections of the radial artery and cephalic vein were acquired, and medical practitioners used a computer application to measure the wall thickness and nominal diameter of these blood vessels with a caliper method and the shape-fitting method. The methods performed equally well for wall thickness measurements. The shape-fitting method was preferable for measuring the diameter, since it reduced systematic errors by up to 63% in the case of the cephalic vein because of its eccentricity. © 2017 by the American Institute of Ultrasound in Medicine.

Feasibility Study of a Vision-Based Landing System for Unmanned Fixed-Wing Aircraft

DTIC Science & Technology

2017-06-01

International Journal of Computer Science and Network Security 7 no. 3: 112–117. Accessed April 7, 2017. http://www.sciencedirect.com/science/ article /pii...the feasibility of applying computer vision techniques and visual feedback in the control loop for an autonomous system. This thesis examines the...integration into an autonomous aircraft control system. 14. SUBJECT TERMS autonomous systems, auto-land, computer vision, image processing

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.

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

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

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.

Infrared Cephalic-Vein to Assist Blood Extraction Tasks: Automatic Projection and Recognition

NASA Astrophysics Data System (ADS)

Lagüela, S.; Gesto, M.; Riveiro, B.; González-Aguilera, D.

2017-05-01

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms. This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

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.

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.

Fast Markerless Tracking for Augmented Reality in Planar Environment

NASA Astrophysics Data System (ADS)

Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim

2015-12-01

Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.

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.

Strategic Vision for Adopting 21st Century Science Methodologies

EPA Pesticide Factsheets

To better protect human health and the environment, EPA’s OPP is developing and evaluating new technologies in molecular, cellular, computational sciences to supplement or replace more traditional methods of toxicity testing and risk assessment.

Computer vision research with new imaging technology

NASA Astrophysics Data System (ADS)

Hou, Guangqi; Liu, Fei; Sun, Zhenan

2015-12-01

Light field imaging is capable of capturing dense multi-view 2D images in one snapshot, which record both intensity values and directions of rays simultaneously. As an emerging 3D device, the light field camera has been widely used in digital refocusing, depth estimation, stereoscopic display, etc. Traditional multi-view stereo (MVS) methods only perform well on strongly texture surfaces, but the depth map contains numerous holes and large ambiguities on textureless or low-textured regions. In this paper, we exploit the light field imaging technology on 3D face modeling in computer vision. Based on a 3D morphable model, we estimate the pose parameters from facial feature points. Then the depth map is estimated through the epipolar plane images (EPIs) method. At last, the high quality 3D face model is exactly recovered via the fusing strategy. We evaluate the effectiveness and robustness on face images captured by a light field camera with different poses.

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.

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.

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.

Stereo-vision-based cooperative-vehicle positioning using OCC and neural networks

NASA Astrophysics Data System (ADS)

Ifthekhar, Md. Shareef; Saha, Nirzhar; Jang, Yeong Min

2015-10-01

Vehicle positioning has been subjected to extensive research regarding driving safety measures and assistance as well as autonomous navigation. The most common positioning technique used in automotive positioning is the global positioning system (GPS). However, GPS is not reliably accurate because of signal blockage caused by high-rise buildings. In addition, GPS is error prone when a vehicle is inside a tunnel. Moreover, GPS and other radio-frequency-based approaches cannot provide orientation information or the position of neighboring vehicles. In this study, we propose a cooperative-vehicle positioning (CVP) technique by using the newly developed optical camera communications (OCC). The OCC technique utilizes image sensors and cameras to receive and decode light-modulated information from light-emitting diodes (LEDs). A vehicle equipped with an OCC transceiver can receive positioning and other information such as speed, lane change, driver's condition, etc., through optical wireless links of neighboring vehicles. Thus, the target vehicle position that is too far away to establish an OCC link can be determined by a computer-vision-based technique combined with the cooperation of neighboring vehicles. In addition, we have devised a back-propagation (BP) neural-network learning method for positioning and range estimation for CVP. The proposed neural-network-based technique can estimate target vehicle position from only two image points of target vehicles using stereo vision. For this, we use rear LEDs on target vehicles as image points. We show from simulation results that our neural-network-based method achieves better accuracy than that of the computer-vision method.

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

Treesearch

Philip A. Araman

1990-01-01

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

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms.

PubMed

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-06-06

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms

PubMed Central

Hu, Qijun; He, Songsheng; Wang, Shilong; Liu, Yugang; Zhang, Zutao; He, Leping; Wang, Fubin; Cai, Qijie; Shi, Rendan; Yang, Yuan

2017-01-01

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable. PMID:28587275

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

Bonior, Jason D; Hu, Zhen; Guo, Terry N.

This letter presents an experimental demonstration of software-defined-radio-based wireless tomography using computer-hosted radio devices called Universal Software Radio Peripheral (USRP). This experimental brief follows our vision and previous theoretical study of wireless tomography that combines wireless communication and RF tomography to provide a novel approach to remote sensing. Automatic data acquisition is performed inside an RF anechoic chamber. Semidefinite relaxation is used for phase retrieval, and the Born iterative method is utilized for imaging the target. Experimental results are presented, validating our vision of wireless tomography.

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.

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).

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.

A variational approach to multi-phase motion of gas, liquid and solid based on the level set method

NASA Astrophysics Data System (ADS)

Yokoi, Kensuke

2009-07-01

We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.

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

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.

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.

Multi-resolution information mining and a computer vision approach to pavement condition distress analysis.

DOT National Transportation Integrated Search

2014-07-01

Pavement Condition surveys are carried out periodically to gather information on pavement distresses that will guide decision-making for maintenance and preservation. Traditional methods involve manual pavement inspections which are time-consuming : ...

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.

Bag-of-visual-ngrams for histopathology image classification

NASA Astrophysics Data System (ADS)

López-Monroy, A. Pastor; Montes-y-Gómez, Manuel; Escalante, Hugo Jair; Cruz-Roa, Angel; González, Fabio A.

2013-11-01

This paper describes an extension of the Bag-of-Visual-Words (BoVW) representation for image categorization (IC) of histophatology images. This representation is one of the most used approaches in several high-level computer vision tasks. However, the BoVW representation has an important limitation: the disregarding of spatial information among visual words. This information may be useful to capture discriminative visual-patterns in specific computer vision tasks. In order to overcome this problem we propose the use of visual n-grams. N-grams based-representations are very popular in the field of natural language processing (NLP), in particular within text mining and information retrieval. We propose building a codebook of n-grams and then representing images by histograms of visual n-grams. We evaluate our proposal in the challenging task of classifying histopathology images. The novelty of our proposal lies in the fact that we use n-grams as attributes for a classification model (together with visual-words, i.e., 1-grams). This is common practice within NLP, although, to the best of our knowledge, this idea has not been explored yet within computer vision. We report experimental results in a database of histopathology images where our proposed method outperforms the traditional BoVWs formulation.

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.

A computer-vision-based rotating speed estimation method for motor bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Wang, Xiaoxian; Guo, Jie; Lu, Siliang; Shen, Changqing; He, Qingbo

2017-06-01

Diagnosis of motor bearing faults under variable speed is a problem. In this study, a new computer-vision-based order tracking method is proposed to address this problem. First, a video recorded by a high-speed camera is analyzed with the speeded-up robust feature extraction and matching algorithm to obtain the instantaneous rotating speed (IRS) of the motor. Subsequently, an audio signal recorded by a microphone is equi-angle resampled for order tracking in accordance with the IRS curve, through which the frequency-domain signal is transferred to an angular-domain one. The envelope order spectrum is then calculated to determine the fault characteristic order, and finally the bearing fault pattern is determined. The effectiveness and robustness of the proposed method are verified with two brushless direct-current motor test rigs, in which two defective bearings and a healthy bearing are tested separately. This study provides a new noninvasive measurement approach that simultaneously avoids the installation of a tachometer and overcomes the disadvantages of tacholess order tracking methods for motor bearing fault diagnosis under variable speed.

Parametric Representation of the Speaker's Lips for Multimodal Sign Language and Speech Recognition

NASA Astrophysics Data System (ADS)

Ryumin, D.; Karpov, A. A.

2017-05-01

In this article, we propose a new method for parametric representation of human's lips region. The functional diagram of the method is described and implementation details with the explanation of its key stages and features are given. The results of automatic detection of the regions of interest are illustrated. A speed of the method work using several computers with different performances is reported. This universal method allows applying parametrical representation of the speaker's lipsfor the tasks of biometrics, computer vision, machine learning, and automatic recognition of face, elements of sign languages, and audio-visual speech, including lip-reading.

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.

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.

Automatic tracking of red blood cells in micro channels using OpenCV

NASA Astrophysics Data System (ADS)

Rodrigues, Vânia; Rodrigues, Pedro J.; Pereira, Ana I.; Lima, Rui

2013-10-01

The present study aims to developan automatic method able to track red blood cells (RBCs) trajectories flowing through a microchannel using the Open Source Computer Vision (OpenCV). The developed method is based on optical flux calculation assisted by the maximization of the template-matching product. The experimental results show a good functional performance of this method.

[A study of biomechanical method for urine test based on color difference estimation].

PubMed

Wang, Chunhong; Zhou, Yue; Zhao, Hongxia; Zhou, Fengkun

2008-02-01

The biochemical analysis of urine is an important inspection and diagnosis method in hospitals. The conventional method of urine analysis covers mainly colorimetric visual appraisement and automation detection, in which the colorimetric visual appraisement technique has been superseded basically, and the automation detection method is adopted in hospital; moreover, the price of urine biochemical analyzer on market is around twenty thousand RMB yuan (Y), which is hard to enter into ordinary families. It is known that computer vision system is not subject to the physiological and psychological influence of person, its appraisement standard is objective and steady. Therefore, according to the color theory, we have established a computer vision system, which can carry through collection, management, display, and appraisement of color difference between the color of standard threshold value and the color of urine test paper after reaction with urine liquid, and then the level of an illness can be judged accurately. In this paper, we introduce the Urine Test Biochemical Analysis method, which is new and can be popularized in families. Experimental result shows that this test method is easy-to-use and cost-effective. It can realize the monitoring of a whole course and can find extensive applications.

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.

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...

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

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

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

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.

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.

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.

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

Objective definition of rosette shape variation using a combined computer vision and data mining approach.

PubMed

Camargo, Anyela; Papadopoulou, Dimitra; Spyropoulou, Zoi; Vlachonasios, Konstantinos; Doonan, John H; Gay, Alan P

2014-01-01

Computer-vision based measurements of phenotypic variation have implications for crop improvement and food security because they are intrinsically objective. It should be possible therefore to use such approaches to select robust genotypes. However, plants are morphologically complex and identification of meaningful traits from automatically acquired image data is not straightforward. Bespoke algorithms can be designed to capture and/or quantitate specific features but this approach is inflexible and is not generally applicable to a wide range of traits. In this paper, we have used industry-standard computer vision techniques to extract a wide range of features from images of genetically diverse Arabidopsis rosettes growing under non-stimulated conditions, and then used statistical analysis to identify those features that provide good discrimination between ecotypes. This analysis indicates that almost all the observed shape variation can be described by 5 principal components. We describe an easily implemented pipeline including image segmentation, feature extraction and statistical analysis. This pipeline provides a cost-effective and inherently scalable method to parameterise and analyse variation in rosette shape. The acquisition of images does not require any specialised equipment and the computer routines for image processing and data analysis have been implemented using open source software. Source code for data analysis is written using the R package. The equations to calculate image descriptors have been also provided.

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.

Fusion of monocular cues to detect man-made structures in aerial imagery

NASA Technical Reports Server (NTRS)

Shufelt, Jefferey; Mckeown, David M.

1991-01-01

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

Image Classification for Web Genre Identification

DTIC Science & Technology

2012-01-01

recognition and landscape detection using the computer vision toolkit OpenCV1. For facial recognition , we researched the possibilities of using the...method for connecting these names with a face/personal photo and logo respectively. [2] METHODOLOGY For this project, we focused primarily on facial

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…

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.

Evaluation of Deep Learning Based Stereo Matching Methods: from Ground to Aerial Images

NASA Astrophysics Data System (ADS)

Liu, J.; Ji, S.; Zhang, C.; Qin, Z.

2018-05-01

Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.

Present status and trends of image fusion

NASA Astrophysics Data System (ADS)

Xiang, Dachao; Fu, Sheng; Cai, Yiheng

2009-10-01

Image fusion information extracted from multiple images which is more accurate and reliable than that from just a single image. Since various images contain different information aspects of the measured parts, and comprehensive information can be obtained by integrating them together. Image fusion is a main branch of the application of data fusion technology. At present, it was widely used in computer vision technology, remote sensing, robot vision, medical image processing and military field. This paper mainly presents image fusion's contents, research methods, and the status quo at home and abroad, and analyzes the development trend.

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

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.

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.

Visualizing stressful aspects of repetitive motion tasks and opportunities for ergonomic improvements using computer vision.

PubMed

Greene, Runyu L; Azari, David P; Hu, Yu Hen; Radwin, Robert G

2017-11-01

Patterns of physical stress exposure are often difficult to measure, and the metrics of variation and techniques for identifying them is underdeveloped in the practice of occupational ergonomics. Computer vision has previously been used for evaluating repetitive motion tasks for hand activity level (HAL) utilizing conventional 2D videos. The approach was made practical by relaxing the need for high precision, and by adopting a semi-automatic approach for measuring spatiotemporal characteristics of the repetitive task. In this paper, a new method for visualizing task factors, using this computer vision approach, is demonstrated. After videos are made, the analyst selects a region of interest on the hand to track and the hand location and its associated kinematics are measured for every frame. The visualization method spatially deconstructs and displays the frequency, speed and duty cycle components of tasks that are part of the threshold limit value for hand activity for the purpose of identifying patterns of exposure associated with the specific job factors, as well as for suggesting task improvements. The localized variables are plotted as a heat map superimposed over the video, and displayed in the context of the task being performed. Based on the intensity of the specific variables used to calculate HAL, we can determine which task factors most contribute to HAL, and readily identify those work elements in the task that contribute more to increased risk for an injury. Work simulations and actual industrial examples are described. This method should help practitioners more readily measure and interpret temporal exposure patterns and identify potential task improvements. Copyright © 2017. Published by Elsevier Ltd.

Threshold-adaptive canny operator based on cross-zero points

NASA Astrophysics Data System (ADS)

Liu, Boqi; Zhang, Xiuhua; Hong, Hanyu

2018-03-01

Canny edge detection[1] is a technique to extract useful structural information from different vision objects and dramatically reduce the amount of data to be processed. It has been widely applied in various computer vision systems. There are two thresholds have to be settled before the edge is segregated from background. Usually, by the experience of developers, two static values are set as the thresholds[2]. In this paper, a novel automatic thresholding method is proposed. The relation between the thresholds and Cross-zero Points is analyzed, and an interpolation function is deduced to determine the thresholds. Comprehensive experimental results demonstrate the effectiveness of proposed method and advantageous for stable edge detection at changing illumination.

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…

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…

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.

Computer vision syndrome prevalence, knowledge and associated factors among Saudi Arabia University Students: Is it a serious problem?

PubMed Central

Al Rashidi, Sultan H.; Alhumaidan, H.

2017-01-01

Objectives: Computers and other visual display devices are now an essential part of our daily life. With the increased use, a very large population is experiencing sundry ocular symptoms globally such as dry eyes, eye strain, irritation, and redness of the eyes to name a few. Collectively, all such computer related symptoms are usually referred to as computer vision syndrome (CVS). The current study aims to define the prevalence, knowledge in community, pathophysiology, factors associated, and prevention of CVS. Methods: This is a cross-sectional study conducted in Qassim University College of Medicine during a period of 1 year from January 2015 to January 2016 using a questionnaire to collect relevant data including demographics and various variables to be studied. 634 students were inducted from a public sector University of Qassim, Saudi Arabia, regardless of their age and gender. The data were then statistically analyzed on SPSS version 22, and the descriptive data were expressed as percentages, mode, and median using graphs where needed. Results: A total of 634 students with a mean age of 21. 40, Std 1.997 and Range 7 (18-25) were included as study subjects with a male predominance (77.28%). Of the total patients, majority (459, 72%) presented with acute symptoms while remaining had chronic problems. A clear-cut majority was carrying the symptoms for <5 days and >1 month. The statistical analysis revealed serious symptoms in the majority of study subjects especially those who are permanent users of a computer for long hours. Conclusion: Continuous use of computers for long hours is found to have severe problems of vision especially in those who are using computers and similar devices for a long duration. PMID:29114189

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.

Tracking by Identification Using Computer Vision and Radio

PubMed Central

Mandeljc, Rok; Kovačič, Stanislav; Kristan, Matej; Perš, Janez

2013-01-01

We present a novel system for detection, localization and tracking of multiple people, which fuses a multi-view computer vision approach with a radio-based localization system. The proposed fusion combines the best of both worlds, excellent computer-vision-based localization, and strong identity information provided by the radio system, and is therefore able to perform tracking by identification, which makes it impervious to propagated identity switches. We present comprehensive methodology for evaluation of systems that perform person localization in world coordinate system and use it to evaluate the proposed system as well as its components. Experimental results on a challenging indoor dataset, which involves multiple people walking around a realistically cluttered room, confirm that proposed fusion of both systems significantly outperforms its individual components. Compared to the radio-based system, it achieves better localization results, while at the same time it successfully prevents propagation of identity switches that occur in pure computer-vision-based tracking. PMID:23262485

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.

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.

Computer Vision Research and Its Applications to Automated Cartography

DTIC Science & Technology

1984-09-01

reflecting from scene surfaces, and the film and digitization processes that result in the computer representation of the image. These models, when...alone. Specifically, intepretations that are in some sense "orthogonal" are preferred. A method for finding such interpretations for right-angle...saturated colors are not precisely representable and the colors recorded with different films or cameras may differ, but the tricomponent representation is t

Automatic image orientation detection via confidence-based integration of low-level and semantic cues.

PubMed

Luo, Jiebo; Boutell, Matthew

2005-05-01

Automatic image orientation detection for natural images is a useful, yet challenging research topic. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is difficult for a computer to perform the task in the same way because current object recognition algorithms are extremely limited in their scope and robustness. As a result, existing orientation detection methods were built upon low-level vision features such as spatial distributions of color and texture. Discrepant detection rates have been reported for these methods in the literature. We have developed a probabilistic approach to image orientation detection via confidence-based integration of low-level and semantic cues within a Bayesian framework. Our current accuracy is 90 percent for unconstrained consumer photos, impressive given the findings of a psychophysical study conducted recently. The proposed framework is an attempt to bridge the gap between computer and human vision systems and is applicable to other problems involving semantic scene content understanding.

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.

[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 comparison of algorithms for inference and learning in probabilistic graphical models.

PubMed

Frey, Brendan J; Jojic, Nebojsa

2005-09-01

Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.

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

Classification of breast tissue in mammograms using efficient coding.

PubMed

Costa, Daniel D; Campos, Lúcio F; Barros, Allan K

2011-06-24

Female breast cancer is the major cause of death by cancer in western countries. Efforts in Computer Vision have been made in order to improve the diagnostic accuracy by radiologists. Some methods of lesion diagnosis in mammogram images were developed based in the technique of principal component analysis which has been used in efficient coding of signals and 2D Gabor wavelets used for computer vision applications and modeling biological vision. In this work, we present a methodology that uses efficient coding along with linear discriminant analysis to distinguish between mass and non-mass from 5090 region of interest from mammograms. The results show that the best rates of success reached with Gabor wavelets and principal component analysis were 85.28% and 87.28%, respectively. In comparison, the model of efficient coding presented here reached up to 90.07%. Altogether, the results presented demonstrate that independent component analysis performed successfully the efficient coding in order to discriminate mass from non-mass tissues. In addition, we have observed that LDA with ICA bases showed high predictive performance for some datasets and thus provide significant support for a more detailed clinical investigation.

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

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.

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.

Virtual viewpoint synthesis in multi-view video system

NASA Astrophysics Data System (ADS)

Li, Fang; Yang, Shiqiang

2005-07-01

In this paper, we present a virtual viewpoint video synthesis algorithm to satisfy the following three aims: low computing consuming; real time interpolation and acceptable video quality. In contrast with previous technologies, this method obtain incompletely 3D structure using neighbor video sources instead of getting total 3D information with all video sources, so that the computation is reduced greatly. So we demonstrate our interactive multi-view video synthesis algorithm in a personal computer. Furthermore, adopting the method of choosing feature points to build the correspondence between the frames captured by neighbor cameras, we need not require camera calibration. Finally, our method can be used when the angle between neighbor cameras is 25-30 degrees that it is much larger than common computer vision experiments. In this way, our method can be applied into many applications such as sports live, video conference, etc.

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.

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.

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

Computer vision and soft computing for automatic skull-face overlay in craniofacial superimposition.

PubMed

Campomanes-Álvarez, B Rosario; Ibáñez, O; Navarro, F; Alemán, I; Botella, M; Damas, S; Cordón, O

2014-12-01

Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

Risk factors for computer visual syndrome (CVS) among operators of two call centers in São Paulo, Brazil.

PubMed

Sa, Eduardo Costa; Ferreira Junior, Mario; Rocha, Lys Esther

2012-01-01

The aims of this study were to investigate work conditions, to estimate the prevalence and to describe risk factors associated with Computer Vision Syndrome among two call centers' operators in São Paulo (n = 476). The methods include a quantitative cross-sectional observational study and an ergonomic work analysis, using work observation, interviews and questionnaires. The case definition was the presence of one or more specific ocular symptoms answered as always, often or sometimes. The multiple logistic regression model, were created using the stepwise forward likelihood method and remained the variables with levels below 5% (p < 0.05). The operators were mainly female and young (from 15 to 24 years old). The call center was opened 24 hours and the operators weekly hours were 36 hours with break time from 21 to 35 minutes per day. The symptoms reported were eye fatigue (73.9%), "weight" in the eyes (68.2%), "burning" eyes (54.6%), tearing (43.9%) and weakening of vision (43.5%). The prevalence of Computer Vision Syndrome was 54.6%. Associations verified were: being female (OR 2.6, 95% CI 1.6 to 4.1), lack of recognition at work (OR 1.4, 95% CI 1.1 to 1.8), organization of work in call center (OR 1.4, 95% CI 1.1 to 1.7) and high demand at work (OR 1.1, 95% CI 1.0 to 1.3). The organization and psychosocial factors at work should be included in prevention programs of visual syndrome among call centers' operators.

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.

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.

Neurally and Ocularly Informed Graph-Based Models for Searching 3D Environments

DTIC Science & Technology

2014-06-03

hBCI = hybrid brain–computer interface, TAG = transductive annotation by graph, CV = computer vision, TSP = traveling salesman problem . are navigated...environment that are most likely to contain objects that the subject would like to visit. 2.9. Route planning A traveling salesman problem (TSP) solver...fixations in a visual search task using fixation-related potentials J. Vis. 13 Croes G 1958 A method for solving traveling - salesman problems Oper. Res

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.

Tablet computers versus optical aids to support education and learning in children and young people with low vision: protocol for a pilot randomised controlled trial, CREATE (Children Reading with Electronic Assistance To Educate)

PubMed Central

Crossland, Michael D; Thomas, Rachel; Unwin, Hilary; Bharani, Seelam; Gothwal, Vijaya K; Quartilho, Ana; Bunce, Catey

2017-01-01

Introduction Low vision and blindness adversely affect education and independence of children and young people. New ‘assistive’ technologies such as tablet computers can display text in enlarged font, read text out to the user, allow speech input and conversion into typed text, offer document and spreadsheet processing and give access to wide sources of information such as the internet. Research on these devices in low vision has been limited to case series. Methods and analysis We will carry out a pilot randomised controlled trial (RCT) to assess the feasibility of a full RCT of assistive technologies for children/young people with low vision. We will recruit 40 students age 10–18 years in India and the UK, whom we will randomise 1:1 into two parallel groups. The active intervention will be Apple iPads; the control arm will be the local standard low-vision aid care. Primary outcomes will be acceptance/usage, accessibility of the device and trial feasibility measures (time to recruit children, lost to follow-up). Exploratory outcomes will be validated measures of vision-related quality of life for children/young people as well as validated measures of reading and educational outcomes. In addition, we will carry out semistructured interviews with the participants and their teachers. Ethics and dissemination NRES reference 15/NS/0068; dissemination is planned via healthcare and education sector conferences and publications, as well as via patient support organisations. Trial registration number NCT02798848; IRAS ID 179658, UCL reference 15/0570. PMID:28637740

Tactile and bone-conduction auditory brain computer interface for vision and hearing impaired users.

PubMed

Rutkowski, Tomasz M; Mori, Hiromu

2015-04-15

The paper presents a report on the recently developed BCI alternative for users suffering from impaired vision (lack of focus or eye-movements) or from the so-called "ear-blocking-syndrome" (limited hearing). We report on our recent studies of the extents to which vibrotactile stimuli delivered to the head of a user can serve as a platform for a brain computer interface (BCI) paradigm. In the proposed tactile and bone-conduction auditory BCI novel multiple head positions are used to evoke combined somatosensory and auditory (via the bone conduction effect) P300 brain responses, in order to define a multimodal tactile and bone-conduction auditory brain computer interface (tbcaBCI). In order to further remove EEG interferences and to improve P300 response classification synchrosqueezing transform (SST) is applied. SST outperforms the classical time-frequency analysis methods of the non-linear and non-stationary signals such as EEG. The proposed method is also computationally more effective comparing to the empirical mode decomposition. The SST filtering allows for online EEG preprocessing application which is essential in the case of BCI. Experimental results with healthy BCI-naive users performing online tbcaBCI, validate the paradigm, while the feasibility of the concept is illuminated through information transfer rate case studies. We present a comparison of the proposed SST-based preprocessing method, combined with a logistic regression (LR) classifier, together with classical preprocessing and LDA-based classification BCI techniques. The proposed tbcaBCI paradigm together with data-driven preprocessing methods are a step forward in robust BCI applications research. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

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.

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.

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.

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.

Unification and Enhancement of Planetary Robotic Vision Ground Processing: The EC FP7 Project PRoVisG

NASA Astrophysics Data System (ADS)

Paar, G.

2009-04-01

At present, mainly the US have realized planetary space missions with essential robotics background. Joining institutions, companies and universities from different established groups in Europe and two relevant players from the US, the EC FP7 Project PRoVisG started in autumn 2008 to demonstrate the European ability of realizing high-level processing of robotic vision image products from the surface of planetary bodies. PRoVisG will build a unified European framework for Robotic Vision Ground Processing. State-of-art computer vision technology will be collected inside and outside Europe to better exploit the image data gathered during past, present and future robotic space missions to the Moon and the Planets. This will lead to a significant enhancement of the scientific, technologic and educational outcome of such missions. We report on the main PRoVisG objectives and the development status: - Past, present and future planetary robotic mission profiles are analysed in terms of existing solutions and requirements for vision processing - The generic processing chain is based on unified vision sensor descriptions and processing interfaces. Processing components available at the PRoVisG Consortium Partners will be completed by and combined with modules collected within the international computer vision community in the form of Announcements of Opportunity (AOs). - A Web GIS is developed to integrate the processing results obtained with data from planetary surfaces into the global planetary context. - Towards the end of the 39 month project period, PRoVisG will address the public by means of a final robotic field test in representative terrain. The European tax payers will be able to monitor the imaging and vision processing in a Mars - similar environment, thus getting an insight into the complexity and methods of processing, the potential and decision making of scientific exploitation of such data and not least the elegancy and beauty of the resulting image products and their visualization. - The educational aspect is addressed by two summer schools towards the end of the project, presenting robotic vision to the students who are future providers of European science and technology, inside and outside the space domain.

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.

A Review on Human Activity Recognition Using Vision-Based Method.

PubMed

Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.

A Review on Human Activity Recognition Using Vision-Based Method

PubMed Central

Nie, Jie

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research. PMID:29065585

A Monocular SLAM Method to Estimate Relative Pose During Satellite Proximity Operations

DTIC Science & Technology

2015-03-26

localization and mapping with efficient outlier handling. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2013. 5. Herbert Bay...S.H. Spencer . Next generation advanced video guidance sensor. In Aerospace Conference, 2008 IEEE, pages 1–8, March 2008. 12. Michael Calonder, Vincent

Coordinated Autonomy for Persistent Presence in Harbor and Riverine Environments

DTIC Science & Technology

2007-09-30

estimators, and methods designed to deal with real-world problems such as video transmission noise; • OpenCV for basic computer vision functionality as...awareness and forward surveillance of Rocky’s intended path. Aerial video was transmitted to the UAV ground station, where an operator using GIS

A conceptual framework to support exposure science research and complete the source-to-outcome continuum for risk assessment

EPA Science Inventory

While knowledge of exposure is fundamental to assessing and mitigating risks, exposure information has been costly and difficult to generate. Driven by major scientific advances in analytical methods, biomonitoring, computational tools, and a newly articulated vision for a great...

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…

Reexamination of color vision standards, part II. a computational method to assess the effect of color deficiencies in using ATC displays : final report.

DOT National Transportation Integrated Search

2006-03-01

The previous study showed that many colors were used in air traffic control displays. We also found that colors were used mainly for three purposes: capturing controllers immediate attention, identifying targets, and segmenting information. This r...

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.

[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.

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.

Saliency detection by conditional generative adversarial network

NASA Astrophysics Data System (ADS)

Cai, Xiaoxu; Yu, Hui

2018-04-01

Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

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.

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.

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.

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

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

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.

Computational materials science and engineering education: A survey of trends and needs

NASA Astrophysics Data System (ADS)

Thornton, K.; Nola, Samanthule; Edwin Garcia, R.; Asta, Mark; Olson, G. B.

2009-10-01

Results from a recent reassessment of the state of computational materials science and engineering (CMSE) education are reported. Surveys were distributed to the chairs and heads of materials programs, faculty members engaged in computational research, and employers of materials scientists and engineers, mainly in the United States. The data was compiled to assess current course offerings related to CMSE, the general climate for introducing computational methods in MSE curricula, and the requirements from the employers’ viewpoint. Furthermore, the available educational resources and their utilization by the community are examined. The surveys show a general support for integrating computational content into MSE education. However, they also reflect remaining issues with implementation, as well as a gap between the tools being taught in courses and those that are used by employers. Overall, the results suggest the necessity for a comprehensively developed vision and plans to further the integration of computational methods into MSE curricula.

Change Detection of Mobile LIDAR Data Using Cloud Computing

NASA Astrophysics Data System (ADS)

Liu, Kun; Boehm, Jan; Alis, Christian

2016-06-01

Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

Optical performance of multifocal soft contact lenses via a single-pass method.

PubMed

Bakaraju, Ravi C; Ehrmann, Klaus; Falk, Darrin; Ho, Arthur; Papas, Eric

2012-08-01

A physical model eye capable of carrying soft contact lenses (CLs) was used as a platform to evaluate optical performance of several commercial multifocals (MFCLs) with high- and low-add powers and a single-vision control. Optical performance was evaluated at three pupil sizes, six target vergences, and five CL-correcting positions using a spatially filtered monochromatic (632.8 nm) light source. The various target vergences were achieved by using negative trial lenses. A photosensor in the retinal plane recorded the image point-spread that enabled the computation of visual Strehl ratios. The centration of CLs was monitored by an additional integrated en face camera. Hydration of the correcting lens was maintained using a humidity chamber and repeated instillations of rewetting saline drops. All the MFCLs reduced performance for distance but considerably improved performance along the range of distance to near target vergences, relative to the single-vision CL. Performance was dependent on add power, design, pupil, and centration of the correcting CLs. Proclear (D) design produced good performance for intermediate vision, whereas Proclear (N) design performed well at near vision (p < 0.05). AirOptix design exhibited good performance for distance and intermediate vision. PureVision design showed improved performance across the test vergences, but only for pupils ≥4 mm in diameter. Performance of Acuvue bifocal was comparable with other MFCLs, but only for pupils >4 mm in diameter. Acuvue Oasys bifocal produced performance comparable with single-vision CL for most vergences. Direct measurement of single-pass images at the retinal plane of a physical model eye used in conjunction with various MFCLs is demonstrated. This method may have utility in evaluating the relative effectiveness of commercial and prototype designs.

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.

Design of an optimum computer vision-based automatic abalone (Haliotis discus hannai) grading algorithm.

PubMed

Lee, Donggil; Lee, Kyounghoon; Kim, Seonghun; Yang, Yongsu

2015-04-01

An automatic abalone grading algorithm that estimates abalone weights on the basis of computer vision using 2D images is developed and tested. The algorithm overcomes the problems experienced by conventional abalone grading methods that utilize manual sorting and mechanical automatic grading. To design an optimal algorithm, a regression formula and R(2) value were investigated by performing a regression analysis for each of total length, body width, thickness, view area, and actual volume against abalone weights. The R(2) value between the actual volume and abalone weight was 0.999, showing a relatively high correlation. As a result, to easily estimate the actual volumes of abalones based on computer vision, the volumes were calculated under the assumption that abalone shapes are half-oblate ellipsoids, and a regression formula was derived to estimate the volumes of abalones through linear regression analysis between the calculated and actual volumes. The final automatic abalone grading algorithm is designed using the abalone volume estimation regression formula derived from test results, and the actual volumes and abalone weights regression formula. In the range of abalones weighting from 16.51 to 128.01 g, the results of evaluation of the performance of algorithm via cross-validation indicate root mean square and worst-case prediction errors of are 2.8 and ±8 g, respectively. © 2015 Institute of Food Technologists®

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…

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.

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.

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

Report: Unsupervised identification of malaria parasites using computer vision.

PubMed

Khan, Najeed Ahmed; Pervaz, Hassan; Latif, Arsalan; Musharaff, Ayesha

2017-01-01

Malaria in human is a serious and fatal tropical disease. This disease results from Anopheles mosquitoes that are infected by Plasmodium species. The clinical diagnosis of malaria based on the history, symptoms and clinical findings must always be confirmed by laboratory diagnosis. Laboratory diagnosis of malaria involves identification of malaria parasite or its antigen / products in the blood of the patient. Manual diagnosis of malaria parasite by the pathologists has proven to become cumbersome. Therefore, there is a need of automatic, efficient and accurate identification of malaria parasite. In this paper, we proposed a computer vision based approach to identify the malaria parasite from light microscopy images. This research deals with the challenges involved in the automatic detection of malaria parasite tissues. Our proposed method is based on the pixel-based approach. We used K-means clustering (unsupervised approach) for the segmentation to identify malaria parasite tissues.

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

Exploring Architectural Details Through a Wearable Egocentric Vision Device

PubMed Central

Alletto, Stefano; Abati, Davide; Serra, Giuseppe; Cucchiara, Rita

2016-01-01

Augmented user experiences in the cultural heritage domain are in increasing demand by the new digital native tourists of 21st century. In this paper, we propose a novel solution that aims at assisting the visitor during an outdoor tour of a cultural site using the unique first person perspective of wearable cameras. In particular, the approach exploits computer vision techniques to retrieve the details by proposing a robust descriptor based on the covariance of local features. Using a lightweight wearable board, the solution can localize the user with respect to the 3D point cloud of the historical landmark and provide him with information about the details at which he is currently looking. Experimental results validate the method both in terms of accuracy and computational effort. Furthermore, user evaluation based on real-world experiments shows that the proposal is deemed effective in enriching a cultural experience. PMID:26901197

GPU-based real-time trinocular stereo vision

NASA Astrophysics Data System (ADS)

Yao, Yuanbin; Linton, R. J.; Padir, Taskin

2013-01-01

Most stereovision applications are binocular which uses information from a 2-camera array to perform stereo matching and compute the depth image. Trinocular stereovision with a 3-camera array has been proved to provide higher accuracy in stereo matching which could benefit applications like distance finding, object recognition, and detection. This paper presents a real-time stereovision algorithm implemented on a GPGPU (General-purpose graphics processing unit) using a trinocular stereovision camera array. Algorithm employs a winner-take-all method applied to perform fusion of disparities in different directions following various image processing techniques to obtain the depth information. The goal of the algorithm is to achieve real-time processing speed with the help of a GPGPU involving the use of Open Source Computer Vision Library (OpenCV) in C++ and NVidia CUDA GPGPU Solution. The results are compared in accuracy and speed to verify the improvement.

Exploring Architectural Details Through a Wearable Egocentric Vision Device.

PubMed

Alletto, Stefano; Abati, Davide; Serra, Giuseppe; Cucchiara, Rita

2016-02-17

Augmented user experiences in the cultural heritage domain are in increasing demand by the new digital native tourists of 21st century. In this paper, we propose a novel solution that aims at assisting the visitor during an outdoor tour of a cultural site using the unique first person perspective of wearable cameras. In particular, the approach exploits computer vision techniques to retrieve the details by proposing a robust descriptor based on the covariance of local features. Using a lightweight wearable board, the solution can localize the user with respect to the 3D point cloud of the historical landmark and provide him with information about the details at which he is currently looking. Experimental results validate the method both in terms of accuracy and computational effort. Furthermore, user evaluation based on real-world experiments shows that the proposal is deemed effective in enriching a cultural experience.

Edge Detection and Geometric Methods in Computer Vision,

DTIC Science & Technology

1985-02-01

enlightening discussion) Derivations or Eqs. 3.29, 3.31, 3.32 (some statistics) Experimental results (pictures)-- not very informative, extensive or useful. lie... neurophysiology and hardware design. If one views 9 the state space as a free vector space on the labels over the field of weights (which we take to be R), then

Stereo Orthogonal Axonometric Perspective for the Teaching of Descriptive Geometry

ERIC Educational Resources Information Center

Méxas, José Geraldo Franco; Guedes, Karla Bastos; Tavares, Ronaldo da Silva

2015-01-01

Purpose: The purpose of this paper is to present the development of a software for stereo visualization of geometric solids, applied to the teaching/learning of Descriptive Geometry. Design/methodology/approach: The paper presents the traditional method commonly used in computer graphic stereoscopic vision (implemented in C language) and the…

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

EPA Science Inventory

Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deploy...

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.

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

Real-Time Evaluation of Breast Self-Examination Using Computer Vision

PubMed Central

Mohammadi, Eman; Dadios, Elmer P.; Gan Lim, Laurence A.; Cabatuan, Melvin K.; Naguib, Raouf N. G.; Avila, Jose Maria C.; Oikonomou, Andreas

2014-01-01

Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance. PMID:25435860

Real-time evaluation of breast self-examination using computer vision.

PubMed

Mohammadi, Eman; Dadios, Elmer P; Gan Lim, Laurence A; Cabatuan, Melvin K; Naguib, Raouf N G; Avila, Jose Maria C; Oikonomou, Andreas

2014-01-01

Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most cost-effective approach for early breast cancer detection. The general objective of this paper is to design and develop a computer vision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and tracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and blocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region. The palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated, checked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to confirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown that the BSE evaluation algorithm presented in this paper provides robust performance.

Dense depth maps from correspondences derived from perceived motion

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2017-01-01

Many computer vision applications require finding corresponding points between images and using the corresponding points to estimate disparity. Today's correspondence finding algorithms primarily use image features or pixel intensities common between image pairs. Some 3-D computer vision applications, however, do not produce the desired results using correspondences derived from image features or pixel intensities. Two examples are the multimodal camera rig and the center region of a coaxial camera rig. We present an image correspondence finding technique that aligns pairs of image sequences using optical flow fields. The optical flow fields provide information about the structure and motion of the scene, which are not available in still images but can be used in image alignment. We apply the technique to a dual focal length stereo camera rig consisting of a visible light-infrared camera pair and to a coaxial camera rig. We test our method on real image sequences and compare our results with the state-of-the-art multimodal and structure from motion (SfM) algorithms. Our method produces more accurate depth and scene velocity reconstruction estimates than the state-of-the-art multimodal and SfM algorithms.

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

Former food products safety: microbiological quality and computer vision evaluation of packaging remnants contamination.

PubMed

Tretola, M; Di Rosa, A R; Tirloni, E; Ottoboni, M; Giromini, C; Leone, F; Bernardi, C E M; Dell'Orto, V; Chiofalo, V; Pinotti, L

2017-08-01

The use of alternative feed ingredients in farm animal's diets can be an interesting choice from several standpoints, including safety. In this respect, this study investigated the safety features of selected former food products (FFPs) intended for animal nutrition produced in the framework of the IZS PLV 06/14 RC project by an FFP processing plant. Six FFP samples, both mash and pelleted, were analysed for the enumeration of total viable count (TVC) (ISO 4833), Enterobacteriaceae (ISO 21528-1), Escherichia coli (ISO 16649-1), coagulase-positive Staphylococci (CPS) (ISO 6888), presumptive Bacillus cereus and its spores (ISO 7932), sulphite-reducing Clostridia (ISO 7937), yeasts and moulds (ISO 21527-1), and the presence in 25 g of Salmonella spp. (ISO 6579). On the same samples, the presence of undesired ingredients, which can be identified as remnants of packaging materials, was evaluated by two different methods: stereomicroscopy according to published methods; and stereomicroscopy coupled with a computer vision system (IRIS Visual Analyzer VA400). All FFPs analysed were safe from a microbiological point of view. TVC was limited and Salmonella was always absent. When remnants of packaging materials were considered, the contamination level was below 0.08% (w/w). Of note, packaging remnants were found mainly from the 1-mm sieve mesh fractions. Finally, the innovative computer vision system demonstrated the possibility of rapid detection for the presence of packaging remnants in FFPs when combined with a stereomicroscope. In conclusion, the FFPs analysed in the present study can be considered safe, even though some improvements in FFP processing in the feeding plant can be useful in further reducing their microbial loads and impurity.

SU-C-209-06: Improving X-Ray Imaging with Computer Vision and Augmented Reality

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

MacDougall, R.D.; Scherrer, B; Don, S

Purpose: To determine the feasibility of using a computer vision algorithm and augmented reality interface to reduce repeat rates and improve consistency of image quality and patient exposure in general radiography. Methods: A prototype device, designed for use with commercially available hardware (Microsoft Kinect 2.0) capable of depth sensing and high resolution/frame rate video, was mounted to the x-ray tube housing as part of a Philips DigitalDiagnost digital radiography room. Depth data and video was streamed to a Windows 10 PC. Proprietary software created an augmented reality interface where overlays displayed selectable information projected over real-time video of the patient.more » The information displayed prior to and during x-ray acquisition included: recognition and position of ordered body part, position of image receptor, thickness of anatomy, location of AEC cells, collimated x-ray field, degree of patient motion and suggested x-ray technique. Pre-clinical data was collected in a volunteer study to validate patient thickness measurements and x-ray images were not acquired. Results: Proprietary software correctly identified ordered body part, measured patient motion, and calculated thickness of anatomy. Pre-clinical data demonstrated accuracy and precision of body part thickness measurement when compared with other methods (e.g. laser measurement tool). Thickness measurements provided the basis for developing a database of thickness-based technique charts that can be automatically displayed to the technologist. Conclusion: The utilization of computer vision and commercial hardware to create an augmented reality view of the patient and imaging equipment has the potential to drastically improve the quality and safety of x-ray imaging by reducing repeats and optimizing technique based on patient thickness. Society of Pediatric Radiology Pilot Grant; Washington University Bear Cub Fund.« less

[Stimulation parameters for automatic examination of color vision].

PubMed

Sommerhalder, J; Pelizzone, M; Roth, A

1997-05-01

We have developed a polyvalent computer controlled instrument, which uses the "two equation method" (Rayleigh and Moreland equations) to measure human colour vision. This "colorimeter" (or anomaloscope) was used to determine the influence of some important stimulation parameters. The influence of stimulus exposure time, observation field size, absolute stimulus luminance, saturation and luminance mismatches between mixture and reference stimuli were measured on our computer controlled colorimeter. All subjects were normal observers. 1) An exposure time of 2s was found to be optimal for clinical work. 2) The Moreland equation on a 7 degrees observation field yields results in which population variability is comparable to a Rayleigh equation on a 2 degrees field. 3) A retinal illuminance between 40 and 1000 trolands can be used for automated Moreland matches. 4) The saturation of the reference field for the Moreland match can be preset to a fixed value. 5) It is important to vary automatically the radiance of the reference field to provide an approximate luminance match as the ratio of primaries in the mixture field is changed. These measurements allows us to determine optimal conditions for automated colour vision examinations and to make recommendations for an international standard.

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.

Simulated Prosthetic Vision: The Benefits of Computer-Based Object Recognition and Localization.

PubMed

Macé, Marc J-M; Guivarch, Valérian; Denis, Grégoire; Jouffrais, Christophe

2015-07-01

Clinical trials with blind patients implanted with a visual neuroprosthesis showed that even the simplest tasks were difficult to perform with the limited vision restored with current implants. Simulated prosthetic vision (SPV) is a powerful tool to investigate the putative functions of the upcoming generations of visual neuroprostheses. Recent studies based on SPV showed that several generations of implants will be required before usable vision is restored. However, none of these studies relied on advanced image processing. High-level image processing could significantly reduce the amount of information required to perform visual tasks and help restore visuomotor behaviors, even with current low-resolution implants. In this study, we simulated a prosthetic vision device based on object localization in the scene. We evaluated the usability of this device for object recognition, localization, and reaching. We showed that a very low number of electrodes (e.g., nine) are sufficient to restore visually guided reaching movements with fair timing (10 s) and high accuracy. In addition, performance, both in terms of accuracy and speed, was comparable with 9 and 100 electrodes. Extraction of high level information (object recognition and localization) from video images could drastically enhance the usability of current visual neuroprosthesis. We suggest that this method-that is, localization of targets of interest in the scene-may restore various visuomotor behaviors. This method could prove functional on current low-resolution implants. The main limitation resides in the reliability of the vision algorithms, which are improving rapidly. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

DTIC Science & Technology

2008-01-01

task of learning dynamic textures from image sequences as well as to modeling biosurveillance drug-sales data. The constraint generation approach...previous methods in our experiments. One application of LDSs in computer vision is learning dynamic textures from video data [8]. An advantage of...over-the-counter (OTC) drug sales for biosurveillance , and sunspot numbers from the UCR archive [9]. Comparison to the best alternative methods [7, 10

Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

PubMed Central

Chen, Chao-I; Koseluk, Robert; Buchanan, Chase; Duerner, Andrew; Jeppesen, Brian; Laux, Hunter

2015-01-01

An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. PMID:25970254

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

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.

Range Image Flow using High-Order Polynomial Expansion

DTIC Science & Technology

2013-09-01

included as a default algorithm in the OpenCV library [2]. The research of estimating the motion between range images, or range flow, is much more...Journal of Computer Vision, vol. 92, no. 1, pp. 1‒31. 2. G. Bradski and A. Kaehler. 2008. Learning OpenCV : Computer Vision with the OpenCV Library

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

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

NASA Astrophysics Data System (ADS)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

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.

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.

Computer vision syndrome: a study of the knowledge, attitudes and practices in Indian ophthalmologists.

PubMed

Bali, Jatinder; Navin, Neeraj; Thakur, Bali Renu

2007-01-01

To study the knowledge, attitude and practices (KAP) towards computer vision syndrome prevalent in Indian ophthalmologists and to assess whether 'computer use by practitioners' had any bearing on the knowledge and practices in computer vision syndrome (CVS). A random KAP survey was carried out on 300 Indian ophthalmologists using a 34-point spot-questionnaire in January 2005. All the doctors who responded were aware of CVS. The chief presenting symptoms were eyestrain (97.8%), headache (82.1%), tiredness and burning sensation (79.1%), watering (66.4%) and redness (61.2%). Ophthalmologists using computers reported that focusing from distance to near and vice versa (P =0.006, chi2 test), blurred vision at a distance (P =0.016, chi2 test) and blepharospasm (P =0.026, chi2 test) formed part of the syndrome. The main mode of treatment used was tear substitutes. Half of ophthalmologists (50.7%) were not prescribing any spectacles. They did not have any preference for any special type of glasses (68.7%) or spectral filters. Computer-users were more likely to prescribe sedatives/anxiolytics (P = 0.04, chi2 test), spectacles (P = 0.02, chi2 test) and conscious frequent blinking (P = 0.003, chi2 test) than the non-computer-users. All respondents were aware of CVS. Confusion regarding treatment guidelines was observed in both groups. Computer-using ophthalmologists were more informed of symptoms and diagnostic signs but were misinformed about treatment modalities.

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.

Scene analysis for effective visual search in rough three-dimensional-modeling scenes

NASA Astrophysics Data System (ADS)

Wang, Qi; Hu, Xiaopeng

2016-11-01

Visual search is a fundamental technology in the computer vision community. It is difficult to find an object in complex scenes when there exist similar distracters in the background. We propose a target search method in rough three-dimensional-modeling scenes based on a vision salience theory and camera imaging model. We give the definition of salience of objects (or features) and explain the way that salience measurements of objects are calculated. Also, we present one type of search path that guides to the target through salience objects. Along the search path, when the previous objects are localized, the search region of each subsequent object decreases, which is calculated through imaging model and an optimization method. The experimental results indicate that the proposed method is capable of resolving the ambiguities resulting from distracters containing similar visual features with the target, leading to an improvement of search speed by over 50%.

Vision-Based Real-Time Traversable Region Detection for Mobile Robot in the Outdoors.

PubMed

Deng, Fucheng; Zhu, Xiaorui; He, Chao

2017-09-13

Environment perception is essential for autonomous mobile robots in human-robot coexisting outdoor environments. One of the important tasks for such intelligent robots is to autonomously detect the traversable region in an unstructured 3D real world. The main drawback of most existing methods is that of high computational complexity. Hence, this paper proposes a binocular vision-based, real-time solution for detecting traversable region in the outdoors. In the proposed method, an appearance model based on multivariate Gaussian is quickly constructed from a sample region in the left image adaptively determined by the vanishing point and dominant borders. Then, a fast, self-supervised segmentation scheme is proposed to classify the traversable and non-traversable regions. The proposed method is evaluated on public datasets as well as a real mobile robot. Implementation on the mobile robot has shown its ability in the real-time navigation applications.

Fusion of Multiple Sensing Modalities for Machine Vision

DTIC Science & Technology

1994-05-31

Modeling of Non-Homogeneous 3-D Objects for Thermal and Visual Image Synthesis," Pattern Recognition, in press. U [11] Nair, Dinesh , and J. K. Aggarwal...20th AIPR Workshop: Computer Vision--Meeting the Challenges, McLean, Virginia, October 1991. Nair, Dinesh , and J. K. Aggarwal, "An Object Recognition...Computer Engineering August 1992 Sunil Gupta Ph.D. Student Mohan Kumar M.S. Student Sandeep Kumar M.S. Student Xavier Lebegue Ph.D., Computer

The Implications of Pervasive Computing on Network Design

NASA Astrophysics Data System (ADS)

Briscoe, R.

Mark Weiser's late-1980s vision of an age of calm technology with pervasive computing disappearing into the fabric of the world [1] has been tempered by an industry-driven vision with more of a feel of conspicuous consumption. In the modified version, everyone carries around consumer electronics to provide natural, seamless interactions both with other people and with the information world, particularly for eCommerce, but still through a pervasive computing fabric.

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.

Riemann tensor of motion vision revisited.

PubMed

Brill, M

2001-07-02

This note shows that the Riemann-space interpretation of motion vision developed by Barth and Watson is neither necessary for their results, nor sufficient to handle an intrinsic coordinate problem. Recasting the Barth-Watson framework as a classical velocity-solver (as in computer vision) solves these problems.

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.

Real-time simulation of the retina allowing visualization of each processing stage

NASA Astrophysics Data System (ADS)

Teeters, Jeffrey L.; Werblin, Frank S.

1991-08-01

The retina computes to let us see, but can we see the retina compute? Until now, the answer has been no, because the unconscious nature of the processing hides it from our view. Here the authors describe a method of seeing computations performed throughout the retina. This is achieved by using neurophysiological data to construct a model of the retina, and using a special-purpose image processing computer (PIPE) to implement the model in real time. Processing in the model is organized into stages corresponding to computations performed by each retinal cell type. The final stage is the transient (change detecting) ganglion cell. A CCD camera forms the input image, and the activity of a selected retinal cell type is the output which is displayed on a TV monitor. By changing the retina cell driving the monitor, the progressive transformations of the image by the retina can be observed. These simulations demonstrate the ubiquitous presence of temporal and spatial variations in the patterns of activity generated by the retina which are fed into the brain. The dynamical aspects make these patterns very different from those generated by the common DOG (Difference of Gaussian) model of receptive field. Because the retina is so successful in biological vision systems, the processing described here may be useful in machine vision.

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.

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.

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

Detection of Alzheimer's Disease by Three-Dimensional Displacement Field Estimation in Structural Magnetic Resonance Imaging.

PubMed

Wang, Shuihua; Zhang, Yudong; Liu, Ge; Phillips, Preetha; Yuan, Ti-Fei

2016-01-01

Within the past decade, computer scientists have developed many methods using computer vision and machine learning techniques to detect Alzheimer's disease (AD) in its early stages. However, some of these methods are unable to achieve excellent detection accuracy, and several other methods are unable to locate AD-related regions. Hence, our goal was to develop a novel AD brain detection method. In this study, our method was based on the three-dimensional (3D) displacement-field (DF) estimation between subjects in the healthy elder control group and AD group. The 3D-DF was treated with AD-related features. The three feature selection measures were used in the Bhattacharyya distance, Student's t-test, and Welch's t-test (WTT). Two non-parallel support vector machines, i.e., generalized eigenvalue proximal support vector machine and twin support vector machine (TSVM), were then used for classification. A 50 × 10-fold cross validation was implemented for statistical analysis. The results showed that "3D-DF+WTT+TSVM" achieved the best performance, with an accuracy of 93.05 ± 2.18, a sensitivity of 92.57 ± 3.80, a specificity of 93.18 ± 3.35, and a precision of 79.51 ± 2.86. This method also exceled in 13 state-of-the-art approaches. Additionally, we were able to detect 17 regions related to AD by using the pure computer-vision technique. These regions include sub-gyral, inferior parietal lobule, precuneus, angular gyrus, lingual gyrus, supramarginal gyrus, postcentral gyrus, third ventricle, superior parietal lobule, thalamus, middle temporal gyrus, precentral gyrus, superior temporal gyrus, superior occipital gyrus, cingulate gyrus, culmen, and insula. These regions were reported in recent publications. The 3D-DF is effective in AD subject and related region detection.

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.

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.

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 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...

Quantification of color vision using a tablet display.

PubMed

Chacon, Alicia; Rabin, Jeff; Yu, Dennis; Johnston, Shawn; Bradshaw, Timothy

2015-01-01

Accurate color vision is essential for optimal performance in aviation and space environments using nonredundant color coding to convey critical information. Most color tests detect color vision deficiency (CVD) but fail to diagnose type or severity of CVD, which are important to link performance to occupational demands. The computer-based Cone Contrast Test (CCT) diagnoses type and severity of CVD. It is displayed on a netbook computer for clinical application, but a more portable version may prove useful for deployments, space and aviation cockpits, as well as accident and sports medicine settings. Our purpose was to determine if the CCT can be conducted on a tablet display (Windows 8, Microsoft, Seattle, WA) using touch-screen response input. The CCT presents colored letters visible only to red (R), green (G), and blue (B) sensitive retinal cones to determine the lowest R, G, and B cone contrast visible to the observer. The CCT was measured in 16 color vision normals (CVN) and 16 CVDs using the standard netbook computer and a Windows 8 tablet display calibrated to produce equal color contrasts. Both displays showed 100% specificity for confirming CVN and 100% sensitivity for detecting CVD. In CVNs there was no difference between scores on netbook vs. tablet displays. G cone CVDs showed slightly lower G cone CCT scores on the tablet. CVD can be diagnosed with a tablet display. Ease-of-use, portability, and complete computer capabilities make tablets ideal for multiple settings, including aviation, space, military deployments, accidents and rescue missions, and sports vision. Chacon A, Rabin J, Yu D, Johnston S, Bradshaw T. Quantification of color vision using a tablet display.

Edge analyzing properties of center/surround response functions in cybernetic vision

NASA Technical Reports Server (NTRS)

Jobson, D. J.

1984-01-01

The ability of center/surround response functions to make explicit high resolution spatial information in optical images was investigated by performing convolutions of two dimensional response functions and image intensity functions (mainly edges). The center/surround function was found to have the unique property of separating edge contrast from shape variations and of providing a direct basis for determining contrast and subsequently shape of edges in images. Computationally simple measures of contrast and shape were constructed for potential use in cybernetic vision systems. For one class of response functions these measures were found to be reasonably resilient for a range of scan direction and displacements of the response functions relative to shaped edges. A pathological range of scan directions was also defined and methods for detecting and handling these cases were developed. The relationship of these results to biological vision is discussed speculatively.

Journal Writing with Web 2.0 Tools: A Vision for Older Adults

ERIC Educational Resources Information Center

Shepherd, Craig E.; Aagard, Steven

2011-01-01

This article describes how Web 2.0 technologies may facilitate journaling and related inquiry methods among older adults. Benefits and limitations of journaling are summarized as well as computer skills of older adults. We then describe how Web 2.0 technologies can enhance journaling among older adults by diminishing feelings of isolation,…

Methods for Identifying Object Class, Type, and Orientation in the Presence of Uncertainty

DTIC Science & Technology

1990-08-01

on Range Finding Techniques for Computer Vision," IEEE Trans. on Pattern Analysis and Machine Intellegence PAMI-5 (2), pp 129-139 March 1983. 15. Yang... Artificial Intelligence Applications, pp 199-205, December 1984. 16. Flynn, P.J. and Jain, A.K.," On Reliable Curvature Estimation, " Proceedings of the

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

A Method of Three-Dimensional Recording of Mandibular Movement Based on Two-Dimensional Image Feature Extraction

PubMed Central

Li, Zhongke; Yang, Huifang; Lü, Peijun; Wang, Yong; Sun, Yuchun

2015-01-01

Background and Objective To develop a real-time recording system based on computer binocular vision and two-dimensional image feature extraction to accurately record mandibular movement in three dimensions. Methods A computer-based binocular vision device with two digital cameras was used in conjunction with a fixed head retention bracket to track occlusal movement. Software was developed for extracting target spatial coordinates in real time based on two-dimensional image feature recognition. A plaster model of a subject’s upper and lower dentition were made using conventional methods. A mandibular occlusal splint was made on the plaster model, and then the occlusal surface was removed. Temporal denture base resin was used to make a 3-cm handle extending outside the mouth connecting the anterior labial surface of the occlusal splint with a detection target with intersecting lines designed for spatial coordinate extraction. The subject's head was firmly fixed in place, and the occlusal splint was fully seated on the mandibular dentition. The subject was then asked to make various mouth movements while the mandibular movement target locus point set was recorded. Comparisons between the coordinate values and the actual values of the 30 intersections on the detection target were then analyzed using paired t-tests. Results The three-dimensional trajectory curve shapes of the mandibular movements were consistent with the respective subject movements. Mean XYZ coordinate values and paired t-test results were as follows: X axis: -0.0037 ± 0.02953, P = 0.502; Y axis: 0.0037 ± 0.05242, P = 0.704; and Z axis: 0.0007 ± 0.06040, P = 0.952. The t-test result showed that the coordinate values of the 30 cross points were considered statistically no significant. (P<0.05) Conclusions Use of a real-time recording system of three-dimensional mandibular movement based on computer binocular vision and two-dimensional image feature recognition technology produced a recording accuracy of approximately ± 0.1 mm, and is therefore suitable for clinical application. Certainly, further research is necessary to confirm the clinical applications of the method. PMID:26375800

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.

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

PubMed

Sabanci, Kadir; Kayabasi, Ahmet; Toktas, Abdurrahim

2017-06-01

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

Computing Optic Flow with ArduEye Vision Sensor

DTIC Science & Technology

2013-01-01

processing algorithm that can be applied to the flight control of other robotic platforms. 15. SUBJECT TERMS Optical flow, ArduEye, vision based ...2 Figure 2. ArduEye vision chip on Stonyman breakout board connected to Arduino Mega (8) (left) and the Stonyman vision chips (7...robotic platforms. There is a significant need for small, light , less power-hungry sensors and sensory data processing algorithms in order to control the

Insect vision as model for machine vision

NASA Astrophysics Data System (ADS)

Osorio, D.; Sobey, Peter J.

1992-11-01

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

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.

Differences in children and adolescents' ability of reporting two CVS-related visual problems.

PubMed

Hu, Liang; Yan, Zheng; Ye, Tiantian; Lu, Fan; Xu, Peng; Chen, Hao

2013-01-01

The present study examined whether children and adolescents can correctly report dry eyes and blurred distance vision, two visual problems associated with computer vision syndrome. Participants are 913 children and adolescents aged 6-17. They were asked to report their visual problems, including dry eyes and blurred distance vision, and received an eye examination, including tear film break-up time (TFBUT) and visual acuity (VA). Inconsistency was found between participants' reports of dry eyes and TFBUT results among all 913 participants as well as for all of four subgroups. In contrast, consistency was found between participants' reports of blurred distance vision and VA results among 873 participants who had never worn glasses as well as for the four subgroups. It was concluded that children and adolescents are unable to report dry eyes correctly; however, they are able to report blurred distance vision correctly. Three practical implications of the findings were discussed. Little is known about children's ability to report their visual problems, an issue critical to diagnosis and treatment of children's computer vision syndrome. This study compared children's self-reports and clinic examination results and found children can correctly report blurred distance vision but not dry eyes.

Analysis of Global Properties of Shapes

DTIC Science & Technology

2010-06-01

Conference on Computer Vision (ICCV) ( Bejing , China , 2005), IEEE. [113] Thrun, S., and Wegbreit, B. Shape from symmetry. In Proceedings of the...International Conference on Computer Vision (ICCV) ( Bejing , China , 2005), IEEE. [114] Toshev, A., Shi, J., and Daniilidis, K. Image matching via saliency...applications ranging from sampling points to finding correspondences to shape simplification. Discrete variants of the Laplace-Beltrami opera - tor [108] and

MRF energy minimization and beyond via dual decomposition.

PubMed

Komodakis, Nikos; Paragios, Nikos; Tziritas, Georgios

2011-03-01

This paper introduces a new rigorous theoretical framework to address discrete MRF-based optimization in computer vision. Such a framework exploits the powerful technique of Dual Decomposition. It is based on a projected subgradient scheme that attempts to solve an MRF optimization problem by first decomposing it into a set of appropriately chosen subproblems, and then combining their solutions in a principled way. In order to determine the limits of this method, we analyze the conditions that these subproblems have to satisfy and demonstrate the extreme generality and flexibility of such an approach. We thus show that by appropriately choosing what subproblems to use, one can design novel and very powerful MRF optimization algorithms. For instance, in this manner we are able to derive algorithms that: 1) generalize and extend state-of-the-art message-passing methods, 2) optimize very tight LP-relaxations to MRF optimization, and 3) take full advantage of the special structure that may exist in particular MRFs, allowing the use of efficient inference techniques such as, e.g., graph-cut-based methods. Theoretical analysis on the bounds related with the different algorithms derived from our framework and experimental results/comparisons using synthetic and real data for a variety of tasks in computer vision demonstrate the extreme potentials of our approach.

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.

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.

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.

BI-sparsity pursuit for robust subspace recovery

DOE PAGES

Bian, Xiao; Krim, Hamid

2015-09-01

Here, the success of sparse models in computer vision and machine learning in many real-world applications, may be attributed in large part, to the fact that many high dimensional data are distributed in a union of low dimensional subspaces. The underlying structure may, however, be adversely affected by sparse errors, thus inducing additional complexity in recovering it. In this paper, we propose a bi-sparse model as a framework to investigate and analyze this problem, and provide as a result , a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We additionally demonstrate the effectiveness ofmore » our method by experiments on real-world vision data.« less

Quantum chemical methods for the investigation of photoinitiated processes in biological systems: theory and applications.

PubMed

Dreuw, Andreas

2006-11-13

With the advent of modern computers and advances in the development of efficient quantum chemical computer codes, the meaningful computation of large molecular systems at a quantum mechanical level became feasible. Recent experimental effort to understand photoinitiated processes in biological systems, for instance photosynthesis or vision, at a molecular level also triggered theoretical investigations in this field. In this Minireview, standard quantum chemical methods are presented that are applicable and recently used for the calculation of excited states of photoinitiated processes in biological molecular systems. These methods comprise configuration interaction singles, the complete active space self-consistent field method, and time-dependent density functional theory and its variants. Semiempirical approaches are also covered. Their basic theoretical concepts and mathematical equations are briefly outlined, and their properties and limitations are discussed. Recent successful applications of the methods to photoinitiated processes in biological systems are described and theoretical tools for the analysis of excited states are presented.

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

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

2003-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Choroideremia

MedlinePlus

... in Your Area Stories of Hope Videos Resources Low Vision Specialists Retinal Physicians My Retina Tracker Registry Genetic ... a treatment is discovered, help is available through low-vision aids, including optical, electronic, and computer-based devices. ...

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.

A Projection free method for Generalized Eigenvalue Problem with a nonsmooth Regularizer.

PubMed

Hwang, Seong Jae; Collins, Maxwell D; Ravi, Sathya N; Ithapu, Vamsi K; Adluru, Nagesh; Johnson, Sterling C; Singh, Vikas

2015-12-01

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libraries leverage such tools extensively. However, the ability to call the underlying solver only as a "black box" can often become restrictive. Many 'human in the loop' settings in vision frequently exploit supervision from an expert, to the extent that the user can be considered a subroutine in the overall system. In other cases, there is additional domain knowledge, side or even partial information that one may want to incorporate within the formulation. In general, regularizing a (generalized) eigenvalue problem with such side information remains difficult. Motivated by these needs, this paper presents an optimization scheme to solve generalized eigenvalue problems (GEP) involving a (nonsmooth) regularizer. We start from an alternative formulation of GEP where the feasibility set of the model involves the Stiefel manifold. The core of this paper presents an end to end stochastic optimization scheme for the resultant problem. We show how this general algorithm enables improved statistical analysis of brain imaging data where the regularizer is derived from other 'views' of the disease pathology, involving clinical measurements and other image-derived representations.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Towards Image Documentation of Grave Coverings and Epitaphs for Exhibition Purposes

NASA Astrophysics Data System (ADS)

Pomaska, G.; Dementiev, N.

2015-08-01

Epitaphs and memorials as immovable items in sacred spaces provide with their inscriptions valuable documents of history. Today not only photography or photos are suitable as presentation material for cultural assets in museums. Computer vision and photogrammetry provide methods for recording, 3D modelling, rendering under artificial light conditions as well as further options for analysis and investigation of artistry. For exhibition purposes epitaphs have been recorded by the structure from motion method. A comparison of different kinds of SFM software distributions could be worked out. The suitability of open source software in the mesh processing chain from modelling up to displaying on computer monitors should be answered. Raspberry Pi, a computer in SoC technology works as a media server under Linux applying Python scripts. Will the little computer meet the requirements for a museum and is the handling comfortable enough for staff and visitors? This contribution reports about the case study.

Identification of double-yolked duck egg using computer vision.

PubMed

Ma, Long; Sun, Ke; Tu, Kang; Pan, Leiqing; Zhang, Wei

2017-01-01

The double-yolked (DY) egg is quite popular in some Asian countries because it is considered as a sign of good luck, however, the double yolk is one of the reasons why these eggs fail to hatch. The usage of automatic methods for identifying DY eggs can increase the efficiency in the poultry industry by decreasing egg loss during incubation or improving sale proceeds. In this study, two methods for DY duck egg identification were developed by using computer vision technology. Transmittance images of DY and single-yolked (SY) duck eggs were acquired by a CCD camera to identify them according to their shape features. The Fisher's linear discriminant (FLD) model equipped with a set of normalized Fourier descriptors (NFDs) extracted from the acquired images and the convolutional neural network (CNN) model using primary preprocessed images were built to recognize duck egg yolk types. The classification accuracies of the FLD model for SY and DY eggs were 100% and 93.2% respectively, while the classification accuracies of the CNN model for SY and DY eggs were 98% and 98.8% respectively. The CNN-based algorithm took about 0.12 s to recognize one sample image, which was slightly faster than the FLD-based (about 0.20 s). Finally, this work compared two classification methods and provided the better method for DY egg identification.

Identification of double-yolked duck egg using computer vision

PubMed Central

Ma, Long; Sun, Ke; Tu, Kang; Pan, Leiqing; Zhang, Wei

2017-01-01

The double-yolked (DY) egg is quite popular in some Asian countries because it is considered as a sign of good luck, however, the double yolk is one of the reasons why these eggs fail to hatch. The usage of automatic methods for identifying DY eggs can increase the efficiency in the poultry industry by decreasing egg loss during incubation or improving sale proceeds. In this study, two methods for DY duck egg identification were developed by using computer vision technology. Transmittance images of DY and single-yolked (SY) duck eggs were acquired by a CCD camera to identify them according to their shape features. The Fisher’s linear discriminant (FLD) model equipped with a set of normalized Fourier descriptors (NFDs) extracted from the acquired images and the convolutional neural network (CNN) model using primary preprocessed images were built to recognize duck egg yolk types. The classification accuracies of the FLD model for SY and DY eggs were 100% and 93.2% respectively, while the classification accuracies of the CNN model for SY and DY eggs were 98% and 98.8% respectively. The CNN-based algorithm took about 0.12 s to recognize one sample image, which was slightly faster than the FLD-based (about 0.20 s). Finally, this work compared two classification methods and provided the better method for DY egg identification. PMID:29267387

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.

Eyesight quality and Computer Vision Syndrome.

PubMed

Bogdănici, Camelia Margareta; Săndulache, Diana Elena; Nechita, Corina Andreea

2017-01-01

The aim of the study was to analyze the effects that gadgets have on eyesight quality. A prospective observational study was conducted from January to July 2016, on 60 people who were divided into two groups: Group 1 - 30 middle school pupils with a mean age of 11.9 ± 1.86 and Group 2 - 30 patients evaluated in the Ophthalmology Clinic, "Sf. Spiridon" Hospital, Iași, with a mean age of 21.36 ± 7.16 years. The clinical parameters observed were the following: visual acuity (VA), objective refraction, binocular vision (BV), fusional amplitude (FA), Schirmer's test. A questionnaire was also distributed, which contained 8 questions that highlighted the gadget's impact on the eyesight. The use of different gadgets, such as computer, laptops, mobile phones or other displays become part of our everyday life and people experience a variety of ocular symptoms or vision problems related to these. Computer Vision Syndrome (CVS) represents a group of visual and extraocular symptoms associated with sustained use of visual display terminals. Headache, blurred vision, and ocular congestion are the most frequent manifestations determined by the long time use of gadgets. Mobile phones and laptops are the most frequently used gadgets. People who use gadgets for a long time have a sustained effort for accommodation. A small amount of refractive errors (especially myopic shift) was objectively recorded by various studies on near work. Dry eye syndrome could also be identified, and an improvement of visual comfort could be observed after the instillation of artificial tears drops. Computer Vision Syndrome is still under-diagnosed, and people should be made aware of the bad effects the prolonged use of gadgets has on eyesight.

Eyesight quality and Computer Vision Syndrome

PubMed Central

Bogdănici, Camelia Margareta; Săndulache, Diana Elena; Nechita, Corina Andreea

2017-01-01

The aim of the study was to analyze the effects that gadgets have on eyesight quality. A prospective observational study was conducted from January to July 2016, on 60 people who were divided into two groups: Group 1 – 30 middle school pupils with a mean age of 11.9 ± 1.86 and Group 2 – 30 patients evaluated in the Ophthalmology Clinic, “Sf. Spiridon” Hospital, Iași, with a mean age of 21.36 ± 7.16 years. The clinical parameters observed were the following: visual acuity (VA), objective refraction, binocular vision (BV), fusional amplitude (FA), Schirmer’s test. A questionnaire was also distributed, which contained 8 questions that highlighted the gadget’s impact on the eyesight. The use of different gadgets, such as computer, laptops, mobile phones or other displays become part of our everyday life and people experience a variety of ocular symptoms or vision problems related to these. Computer Vision Syndrome (CVS) represents a group of visual and extraocular symptoms associated with sustained use of visual display terminals. Headache, blurred vision, and ocular congestion are the most frequent manifestations determined by the long time use of gadgets. Mobile phones and laptops are the most frequently used gadgets. People who use gadgets for a long time have a sustained effort for accommodation. A small amount of refractive errors (especially myopic shift) was objectively recorded by various studies on near work. Dry eye syndrome could also be identified, and an improvement of visual comfort could be observed after the instillation of artificial tears drops. Computer Vision Syndrome is still under-diagnosed, and people should be made aware of the bad effects the prolonged use of gadgets has on eyesight. PMID:29450383

Computational test bench and flow chart for wavefront sensors

NASA Astrophysics Data System (ADS)

Abecassis, Úrsula V.; de Lima Monteiro, Davies W.; Salles, Luciana P.; Stanigher, Rafaela; Borges, Euller

2014-05-01

The wavefront reconstruction diagram has come to supply the need in literature of an ampler vision over the many methods and optronic devices used for the reconstruction of wavefronts and to show the existing interactions between those. A computational platform has been developed using the diagram's orientation for the taking of decision over the best technique and the photo sensible and electronic structures to be implemented. This work will be directed to an ophthalmological application in the development of an instrument of help for the diagnosis of optical aberrations of the human eye.

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.

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...

Atlantic salmon skin and fillet color changes effected by perimortem handling stress, rigor mortis, and ice storage.

PubMed

Erikson, U; Misimi, E

2008-03-01

The changes in skin and fillet color of anesthetized and exhausted Atlantic salmon were determined immediately after killing, during rigor mortis, and after ice storage for 7 d. Skin color (CIE L*, a*, b*, and related values) was determined by a Minolta Chroma Meter. Roche SalmoFan Lineal and Roche Color Card values were determined by a computer vision method and a sensory panel. Before color assessment, the stress levels of the 2 fish groups were characterized in terms of white muscle parameters (pH, rigor mortis, and core temperature). The results showed that perimortem handling stress initially significantly affected several color parameters of skin and fillets. Significant transient fillet color changes also occurred in the prerigor phase and during the development of rigor mortis. Our results suggested that fillet color was affected by postmortem glycolysis (pH drop, particularly in anesthetized fillets), then by onset and development of rigor mortis. The color change patterns during storage were different for the 2 groups of fish. The computer vision method was considered suitable for automated (online) quality control and grading of salmonid fillets according to color.

Spatial-frequency dependent binocular imbalance in amblyopia

PubMed Central

Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C.; Bex, Peter J.

2015-01-01

While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy. PMID:26603125

Spatial-frequency dependent binocular imbalance in amblyopia.

PubMed

Kwon, MiYoung; Wiecek, Emily; Dakin, Steven C; Bex, Peter J

2015-11-25

While amblyopia involves both binocular imbalance and deficits in processing high spatial frequency information, little is known about the spatial-frequency dependence of binocular imbalance. Here we examined binocular imbalance as a function of spatial frequency in amblyopia using a novel computer-based method. Binocular imbalance at four spatial frequencies was measured with a novel dichoptic letter chart in individuals with amblyopia, or normal vision. Our dichoptic letter chart was composed of band-pass filtered letters arranged in a layout similar to the ETDRS acuity chart. A different chart was presented to each eye of the observer via stereo-shutter glasses. The relative contrast of the corresponding letter in each eye was adjusted by a computer staircase to determine a binocular Balance Point at which the observer reports the letter presented to either eye with equal probability. Amblyopes showed pronounced binocular imbalance across all spatial frequencies, with greater imbalance at high compared to low spatial frequencies (an average increase of 19%, p < 0.01). Good test-retest reliability of the method was demonstrated by the Bland-Altman plot. Our findings suggest that spatial-frequency dependent binocular imbalance may be useful for diagnosing amblyopia and as an outcome measure for recovery of binocular vision following therapy.

What Is Low Vision?

MedlinePlus

... magnifying reading glasses or loupes for seeing the computer screen , sheet music, or for sewing telescopic glasses ... for the Blind services. The Low Vision Pilot Project The American Foundation for the Blind (AFB) has ...

Development of a Vision-Based Situational Awareness Capability for Unmanned Surface Vessels

DTIC Science & Technology

2017-09-01

used to provide an SA capability for USVs. This thesis addresses the following research questions: (1) Can a computer vision– based technique be...BLANK 51 VI. CONCLUSION AND RECOMMENDATIONS A. CONCLUSION This research demonstrated the feasibility of using a computer vision– based ...VISION- BASED SITUATIONAL AWARENESS CAPABILITY FOR UNMANNED SURFACE VESSELS by Ying Jie Benjemin Toh September 2017 Thesis Advisor: Oleg

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.

Feature extraction algorithm for space targets based on fractal theory

NASA Astrophysics Data System (ADS)

Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

2007-11-01

In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

Exploring Human Cognition Using Large Image Databases.

PubMed

Griffiths, Thomas L; Abbott, Joshua T; Hsu, Anne S

2016-07-01

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories. Copyright © 2016 Cognitive Science Society, Inc.

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.

Image Understanding Architecture

DTIC Science & Technology

1991-09-01

architecture to support real-time, knowledge -based image understanding , and develop the software support environment that will be needed to utilize...NUMBER OF PAGES Image Understanding Architecture, Knowledge -Based Vision, AI Real-Time Computer Vision, Software Simulator, Parallel Processor IL PRICE... information . In addition to sensory and knowledge -based processing it is useful to introduce a level of symbolic processing. Thus, vision researchers

Video image processing

NASA Technical Reports Server (NTRS)

Murray, N. D.

1985-01-01

Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

PubMed

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-10-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

PubMed Central

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-01-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN-based methods and other previous handcrafted methods. PMID:28974031

Low Vision Aids and Low Vision Rehabilitation

MedlinePlus

... SeeingAI), magnify, or illuminate. Another app, EyeNote, is free for Apple products. It scans and identifies the denomination of U.S. paper money. Computers that can read aloud or magnify what ...

Supporting Real-Time Computer Vision Workloads using OpenVX on Multicore+GPU Platforms

DTIC Science & Technology

2015-05-01

a registered trademark of the NVIDIA Corporation . Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection...from NVIDIA , we adapted an alpha- version of an NVIDIA OpenVX implementation called VisionWorks® [3] to run atop PGMRT (a graph-based mid- dleware...time support to an OpenVX implementation by NVIDIA called VisionWorks. Our modifications were applied to an alpha-version of VisionWorks. This alpha

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.

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.

Overview of sports vision

NASA Astrophysics Data System (ADS)

Moore, Linda A.; Ferreira, Jannie T.

2003-03-01

Sports vision encompasses the visual assessment and provision of sports-specific visual performance enhancement and ocular protection for athletes of all ages, genders and levels of participation. In recent years, sports vision has been identified as one of the key performance indicators in sport. It is built on four main cornerstones: corrective eyewear, protective eyewear, visual skills enhancement and performance enhancement. Although clinically well established in the US, it is still a relatively new area of optometric specialisation elsewhere in the world and is gaining increasing popularity with eyecare practitioners and researchers. This research is often multi-disciplinary and involves input from a variety of subject disciplines, mainly those of optometry, medicine, physiology, psychology, physics, chemistry, computer science and engineering. Collaborative research projects are currently underway between staff of the Schools of Physics and Computing (DIT) and the Academy of Sports Vision (RAU).

On-Chip Imaging of Schistosoma haematobium Eggs in Urine for Diagnosis by Computer Vision

PubMed Central

Linder, Ewert; Grote, Anne; Varjo, Sami; Linder, Nina; Lebbad, Marianne; Lundin, Mikael; Diwan, Vinod; Hannuksela, Jari; Lundin, Johan

2013-01-01

Background Microscopy, being relatively easy to perform at low cost, is the universal diagnostic method for detection of most globally important parasitic infections. As quality control is hard to maintain, misdiagnosis is common, which affects both estimates of parasite burdens and patient care. Novel techniques for high-resolution imaging and image transfer over data networks may offer solutions to these problems through provision of education, quality assurance and diagnostics. Imaging can be done directly on image sensor chips, a technique possible to exploit commercially for the development of inexpensive “mini-microscopes”. Images can be transferred for analysis both visually and by computer vision both at point-of-care and at remote locations. Methods/Principal Findings Here we describe imaging of helminth eggs using mini-microscopes constructed from webcams and mobile phone cameras. The results show that an inexpensive webcam, stripped off its optics to allow direct application of the test sample on the exposed surface of the sensor, yields images of Schistosoma haematobium eggs, which can be identified visually. Using a highly specific image pattern recognition algorithm, 4 out of 5 eggs observed visually could be identified. Conclusions/Significance As proof of concept we show that an inexpensive imaging device, such as a webcam, may be easily modified into a microscope, for the detection of helminth eggs based on on-chip imaging. Furthermore, algorithms for helminth egg detection by machine vision can be generated for automated diagnostics. The results can be exploited for constructing simple imaging devices for low-cost diagnostics of urogenital schistosomiasis and other neglected tropical infectious diseases. PMID:24340107

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.

A new computer-based Farnsworth Munsell 100-hue test for evaluation of color vision.

PubMed

Ghose, Supriyo; Parmar, Twinkle; Dada, Tanuj; Vanathi, Murugesan; Sharma, Sourabh

2014-08-01

To evaluate a computer-based Farnsworth-Munsell (FM) 100-hue test and compare it with a manual FM 100-hue test in normal and congenital color-deficient individuals. Fifty color defective subjects and 200 normal subjects with a best-corrected visual acuity ≥ 6/12 were compared using a standard manual FM 100-hue test and a computer-based FM 100-hue test under standard operating conditions as recommended by the manufacturer after initial trial testing. Parameters evaluated were total error scores (TES), type of defect and testing time. Pearson's correlation coefficient was used to determine the relationship between the test scores. Cohen's kappa was used to assess agreement of color defect classification between the two tests. A receiver operating characteristic curve was used to determine the optimal cut-off score for the computer-based FM 100-hue test. The mean time was 16 ± 1.5 (range 6-20) min for the manual FM 100-hue test and 7.4 ± 1.4 (range 5-13) min for the computer-based FM 100-hue test, thus reducing testing time to <50 % (p < 0.05). For grading color discrimination, Pearson's correlation coefficient for TES between the two tests was 0.91 (p < 0.001). For color defect classification, Cohen's agreement coefficient was 0.98 (p < 0.01). The computer-based FM 100-hue is an effective and rapid method for detecting, classifying and grading color vision anomalies.

CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

NASA Technical Reports Server (NTRS)

Slotnick, Jeffrey; Khodadoust, Abdollah; Alonso, Juan; Darmofal, David; Gropp, William; Lurie, Elizabeth; Mavriplis, Dimitri

2014-01-01

This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030.

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.

The vertical monitor position for presbyopic computer users with progressive lenses: how to reach clear vision and comfortable head posture.

PubMed

Weidling, Patrick; Jaschinski, Wolfgang

2015-01-01

When presbyopic employees are wearing general-purpose progressive lenses, they have clear vision only with a lower gaze inclination to the computer monitor, given the head assumes a comfortable inclination. Therefore, in the present intervention field study the monitor position was lowered, also with the aim to reduce musculoskeletal symptoms. A comparison group comprised users of lenses that do not restrict the field of clear vision. The lower monitor positions led the participants to lower their head inclination, which was linearly associated with a significant reduction in musculoskeletal symptoms. However, for progressive lenses a lower head inclination means a lower zone of clear vision, so that clear vision of the complete monitor was not achieved, rather the monitor should have been placed even lower. The procedures of this study may be useful for optimising the individual monitor position depending on the comfortable head and gaze inclination and the vertical zone of clear vision of progressive lenses. For users of general-purpose progressive lenses, it is suggested that low monitor positions allow for clear vision at the monitor and for a physiologically favourable head inclination. Employees may improve their workplace using a flyer providing ergonomic-optometric information.

Computer vision syndrome: A review.

PubMed

Gowrisankaran, Sowjanya; Sheedy, James E

2015-01-01

Computer vision syndrome (CVS) is a collection of symptoms related to prolonged work at a computer display. This article reviews the current knowledge about the symptoms, related factors and treatment modalities for CVS. Relevant literature on CVS published during the past 65 years was analyzed. Symptoms reported by computer users are classified into internal ocular symptoms (strain and ache), external ocular symptoms (dryness, irritation, burning), visual symptoms (blur, double vision) and musculoskeletal symptoms (neck and shoulder pain). The major factors associated with CVS are either environmental (improper lighting, display position and viewing distance) and/or dependent on the user's visual abilities (uncorrected refractive error, oculomotor disorders and tear film abnormalities). Although the factors associated with CVS have been identified the physiological mechanisms that underlie CVS are not completely understood. Additionally, advances in technology have led to the increased use of hand-held devices, which might impose somewhat different visual challenges compared to desktop displays. Further research is required to better understand the physiological mechanisms underlying CVS and symptoms associated with the use of hand-held and stereoscopic displays.

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

PubMed

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

2018-03-01

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

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

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.

Effects of job-related stress and burnout on asthenopia among high-tech workers.

PubMed

Ostrovsky, Anat; Ribak, Joseph; Pereg, Avihu; Gaton, Dan

2012-01-01

Eye- and vision-related symptoms are the most frequent health problems among computer users. The findings of eye strain, tired eyes, eye irritation, burning sensation, redness, blurred vision and double vision, when appearing together, have recently been termed 'computer vision syndrome', or asthenopia. To examine the frequency and intensity of asthenopia among individuals employed in research and development departments of high-tech firms and the effects of job stress and burnout on ocular complaints, this study included 106 subjects, 42 high-tech workers (study group) and 64 bank employees (control group). All participants completed self-report questionnaires covering demographics, asthenopia, satisfaction with work environmental conditions, job-related stress and burnout. There was a significant between-group difference in the intensity of asthenopia, but not in its frequency. Burnout appeared to be a significant contributing factor to the intensity and frequency of asthenopia. This study shows that burnout is a significant factor in asthenopic complaints in high-tech workers. This manuscript analyses the effects of psychological environmental factors, such as job stress and burnout, on ocular complaints at the workplace of computer users. The findings may have an ergonomic impact on how to improve health, safety and comfort of the working environment among computer users, for better perception of the job environment, efficacy and production.

Remote logo detection using angle-distance histograms

NASA Astrophysics Data System (ADS)

Youn, Sungwook; Ok, Jiheon; Baek, Sangwook; Woo, Seongyoun; Lee, Chulhee

2016-05-01

Among all the various computer vision applications, automatic logo recognition has drawn great interest from industry as well as various academic institutions. In this paper, we propose an angle-distance map, which we used to develop a robust logo detection algorithm. The proposed angle-distance histogram is invariant against scale and rotation. The proposed method first used shape information and color characteristics to find the candidate regions and then applied the angle-distance histogram. Experiments show that the proposed method detected logos of various sizes and orientations.

Integrating computation into the undergraduate curriculum: A vision and guidelines for future developments

NASA Astrophysics Data System (ADS)

Chonacky, Norman; Winch, David

2008-04-01

There is substantial evidence of a need to make computation an integral part of the undergraduate physics curriculum. This need is consistent with data from surveys in both the academy and the workplace, and has been reinforced by two years of exploratory efforts by a group of physics faculty for whom computation is a special interest. We have examined past and current efforts at reform and a variety of strategic, organizational, and institutional issues involved in any attempt to broadly transform existing practice. We propose a set of guidelines for development based on this past work and discuss our vision of computationally integrated physics.

Computer vision syndrome and associated factors among medical and engineering students in chennai.

PubMed

Logaraj, M; Madhupriya, V; Hegde, Sk

2014-03-01

Almost all institutions, colleges, universities and homes today were using computer regularly. Very little research has been carried out on Indian users especially among college students the effects of computer use on the eye and vision related problems. The aim of this study was to assess the prevalence of computer vision syndrome (CVS) among medical and engineering students and the factors associated with the same. A cross-sectional study was conducted among medical and engineering college students of a University situated in the suburban area of Chennai. Students who used computer in the month preceding the date of study were included in the study. The participants were surveyed using pre-tested structured questionnaire. Among engineering students, the prevalence of CVS was found to be 81.9% (176/215) while among medical students; it was found to be 78.6% (158/201). A significantly higher proportion of engineering students 40.9% (88/215) used computers for 4-6 h/day as compared to medical students 10% (20/201) (P < 0.001). The reported symptoms of CVS were higher among engineering students compared with medical students. Students who used computer for 4-6 h were at significantly higher risk of developing redness (OR = 1.2, 95% CI = 1.0-3.1,P = 0.04), burning sensation (OR = 2.1,95% CI = 1.3-3.1, P < 0.01) and dry eyes (OR = 1.8, 95% CI = 1.1-2.9, P = 0.02) compared to those who used computer for less than 4 h. Significant correlation was found between increased hours of computer use and the symptoms redness, burning sensation, blurred vision and dry eyes. The present study revealed that more than three-fourth of the students complained of any one of the symptoms of CVS while working on the computer.

Parallel computation of level set method for 500 Hz visual servo control

NASA Astrophysics Data System (ADS)

Fei, Xianfeng; Igarashi, Yasunobu; Hashimoto, Koichi

2008-11-01

We propose a 2D microorganism tracking system using a parallel level set method and a column parallel vision system (CPV). This system keeps a single microorganism in the middle of the visual field under a microscope by visual servoing an automated stage. We propose a new energy function for the level set method. This function constrains an amount of light intensity inside the detected object contour to control the number of the detected objects. This algorithm is implemented in CPV system and computational time for each frame is 2 [ms], approximately. A tracking experiment for about 25 s is demonstrated. Also we demonstrate a single paramecium can be kept tracking even if other paramecia appear in the visual field and contact with the tracked paramecium.

Body-Based Gender Recognition Using Images from Visible and Thermal Cameras

PubMed Central

Nguyen, Dat Tien; Park, Kang Ryoung

2016-01-01

Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction system. In most previous studies, researchers attempted to recognize gender by using visible light images of the human face or body. However, shadow, illumination, and time of day greatly affect the performance of these methods. To overcome this problem, we propose a new gender recognition method based on the combination of visible light and thermal camera images of the human body. Experimental results, through various kinds of feature extraction and fusion methods, show that our approach is efficient for gender recognition through a comparison of recognition rates with conventional systems. PMID:26828487

Body-Based Gender Recognition Using Images from Visible and Thermal Cameras.

PubMed

Nguyen, Dat Tien; Park, Kang Ryoung

2016-01-27

Gender information has many useful applications in computer vision systems, such as surveillance systems, counting the number of males and females in a shopping mall, accessing control systems in restricted areas, or any human-computer interaction system. In most previous studies, researchers attempted to recognize gender by using visible light images of the human face or body. However, shadow, illumination, and time of day greatly affect the performance of these methods. To overcome this problem, we propose a new gender recognition method based on the combination of visible light and thermal camera images of the human body. Experimental results, through various kinds of feature extraction and fusion methods, show that our approach is efficient for gender recognition through a comparison of recognition rates with conventional systems.

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.

On-line determination of pork color and intramuscular fat by computer vision

NASA Astrophysics Data System (ADS)

Liao, Yi-Tao; Fan, Yu-Xia; Wu, Xue-Qian; Xie, Li-juan; Cheng, Fang

2010-04-01

In this study, the application potential of computer vision in on-line determination of CIE L*a*b* and content of intramuscular fat (IMF) of pork was evaluated. Images of pork chop from 211 pig carcasses were captured while samples were on a conveyor belt at the speed of 0.25 m•s-1 to simulate the on-line environment. CIE L*a*b* and IMF content were measured with colorimeter and chemical extractor as reference. The KSW algorithm combined with region selection was employed in eliminating the surrounding fat of longissimus dorsi muscle (MLD). RGB values of the pork were counted and five methods were applied for transforming RGB values to CIE L*a*b* values. The region growing algorithm with multiple seed points was applied to mask out the IMF pixels within the intensity corrected images. The performances of the proposed algorithms were verified by comparing the measured reference values and the quality characteristics obtained by image processing. MLD region of six samples could not be identified using the KSW algorithm. Intensity nonuniformity of pork surface in the image can be eliminated efficiently, and IMF region of three corrected images failed to be extracted. Given considerable variety of color and complexity of the pork surface, CIE L*, a* and b* color of MLD could be predicted with correlation coefficients of 0.84, 0.54 and 0.47 respectively, and IMF content could be determined with a correlation coefficient more than 0.70. The study demonstrated that it is feasible to evaluate CIE L*a*b* values and IMF content on-line using computer vision.

Another 25 Years of AIED? Challenges and Opportunities for Intelligent Educational Technologies of the Future

ERIC Educational Resources Information Center

Pinkwart, Niels

2016-01-01

This paper attempts an analysis of some current trends and future developments in computer science, education, and educational technology. Based on these trends, two possible future predictions of AIED are presented in the form of a utopian vision and a dystopian vision. A comparison of these two visions leads to seven challenges that AIED might…

Merged Vision and GPS Control of a Semi-Autonomous, Small Helicopter

NASA Technical Reports Server (NTRS)

Rock, Stephen M.

1999-01-01

This final report documents the activities performed during the research period from April 1, 1996 to September 30, 1997. It contains three papers: Carrier Phase GPS and Computer Vision for Control of an Autonomous Helicopter; A Contestant in the 1997 International Aerospace Robotics Laboratory Stanford University; and Combined CDGPS and Vision-Based Control of a Small Autonomous Helicopter.

Constraints for the Trifocal Tensor

NASA Astrophysics Data System (ADS)

Alzati, Alberto; Tortora, Alfonso

In this chapter we give an account of two different methods to find constraints for the trifocal tensor Т, used in geometric computer vision. We also show how to single out a set of only eight equations that are generically complete, i.e. for a generic choice of Т, they suffice to decide whether Т is indeed trifocal. Note that eight is minimum possible number of constraints.

An optimized content-aware image retargeting method: toward expanding the perceived visual field of the high-density retinal prosthesis recipients

NASA Astrophysics Data System (ADS)

Li, Heng; Zeng, Yajie; Lu, Zhuofan; Cao, Xiaofei; Su, Xiaofan; Sui, Xiaohong; Wang, Jing; Chai, Xinyu

2018-04-01

Objective. Retinal prosthesis devices have shown great value in restoring some sight for individuals with profoundly impaired vision, but the visual acuity and visual field provided by prostheses greatly limit recipients’ visual experience. In this paper, we employ computer vision approaches to seek to expand the perceptible visual field in patients implanted potentially with a high-density retinal prosthesis while maintaining visual acuity as much as possible. Approach. We propose an optimized content-aware image retargeting method, by introducing salient object detection based on color and intensity-difference contrast, aiming to remap important information of a scene into a small visual field and preserve their original scale as much as possible. It may improve prosthetic recipients’ perceived visual field and aid in performing some visual tasks (e.g. object detection and object recognition). To verify our method, psychophysical experiments, detecting object number and recognizing objects, are conducted under simulated prosthetic vision. As control, we use three other image retargeting techniques, including Cropping, Scaling, and seam-assisted shrinkability. Main results. Results show that our method outperforms in preserving more key features and has significantly higher recognition accuracy in comparison with other three image retargeting methods under the condition of small visual field and low-resolution. Significance. The proposed method is beneficial to expand the perceived visual field of prosthesis recipients and improve their object detection and recognition performance. It suggests that our method may provide an effective option for image processing module in future high-density retinal implants.

Effect of contact lens use on Computer Vision Syndrome.

PubMed

Tauste, Ana; Ronda, Elena; Molina, María-José; Seguí, Mar

2016-03-01

To analyse the relationship between Computer Vision Syndrome (CVS) in computer workers and contact lens use, according to lens materials. Cross-sectional study. The study included 426 civil-service office workers, of whom 22% were contact lens wearers. Workers completed the Computer Vision Syndrome Questionnaire (CVS-Q) and provided information on their contact lenses and exposure to video display terminals (VDT) at work. CVS was defined as a CVS-Q score of 6 or more. The covariates were age and sex. Logistic regression was used to calculate the association (crude and adjusted for age and sex) between CVS and individual and work-related factors, and between CVS and contact lens type. Contact lens wearers are more likely to suffer CVS than non-lens wearers, with a prevalence of 65% vs 50%. Workers who wear contact lenses and are exposed to the computer for more than 6 h day(-1) are more likely to suffer CVS than non-lens wearers working at the computer for the same amount of time (aOR = 4.85; 95% CI, 1.25-18.80; p = 0.02). Regular contact lens use increases CVS after 6 h of computer work. © 2016 The Authors Ophthalmic & Physiological Optics © 2016 The College of Optometrists.

An automated method for accurate vessel segmentation.

PubMed

Yang, Xin; Liu, Chaoyue; Le Minh, Hung; Wang, Zhiwei; Chien, Aichi; Cheng, Kwang-Ting Tim

2017-05-07

Vessel segmentation is a critical task for various medical applications, such as diagnosis assistance of diabetic retinopathy, quantification of cerebral aneurysm's growth, and guiding surgery in neurosurgical procedures. Despite technology advances in image segmentation, existing methods still suffer from low accuracy for vessel segmentation in the two challenging while common scenarios in clinical usage: (1) regions with a low signal-to-noise-ratio (SNR), and (2) at vessel boundaries disturbed by adjacent non-vessel pixels. In this paper, we present an automated system which can achieve highly accurate vessel segmentation for both 2D and 3D images even under these challenging scenarios. Three key contributions achieved by our system are: (1) a progressive contrast enhancement method to adaptively enhance contrast of challenging pixels that were otherwise indistinguishable, (2) a boundary refinement method to effectively improve segmentation accuracy at vessel borders based on Canny edge detection, and (3) a content-aware region-of-interests (ROI) adjustment method to automatically determine the locations and sizes of ROIs which contain ambiguous pixels and demand further verification. Extensive evaluation of our method is conducted on both 2D and 3D datasets. On a public 2D retinal dataset (named DRIVE (Staal 2004 IEEE Trans. Med. Imaging 23 501-9)) and our 2D clinical cerebral dataset, our approach achieves superior performance to the state-of-the-art methods including a vesselness based method (Frangi 1998 Int. Conf. on Medical Image Computing and Computer-Assisted Intervention) and an optimally oriented flux (OOF) based method (Law and Chung 2008 European Conf. on Computer Vision). An evaluation on 11 clinical 3D CTA cerebral datasets shows that our method can achieve 94% average accuracy with respect to the manual segmentation reference, which is 23% to 33% better than the five baseline methods (Yushkevich 2006 Neuroimage 31 1116-28; Law and Chung 2008 European Conf. on Computer Vision; Law and Chung 2009 IEEE Trans. Image Process. 18 596-612; Wang 2015 J. Neurosci. Methods 241 30-6) with manually optimized parameters. Our system has also been applied clinically for cerebral aneurysm development analysis. Experimental results on 10 patients' data, with two 3D CT scans per patient, show that our system's automatic diagnosis outcomes are consistent with clinicians' manual measurements.

An automated method for accurate vessel segmentation

NASA Astrophysics Data System (ADS)

Yang, Xin; Liu, Chaoyue; Le Minh, Hung; Wang, Zhiwei; Chien, Aichi; (Tim Cheng, Kwang-Ting

2017-05-01

Vessel segmentation is a critical task for various medical applications, such as diagnosis assistance of diabetic retinopathy, quantification of cerebral aneurysm’s growth, and guiding surgery in neurosurgical procedures. Despite technology advances in image segmentation, existing methods still suffer from low accuracy for vessel segmentation in the two challenging while common scenarios in clinical usage: (1) regions with a low signal-to-noise-ratio (SNR), and (2) at vessel boundaries disturbed by adjacent non-vessel pixels. In this paper, we present an automated system which can achieve highly accurate vessel segmentation for both 2D and 3D images even under these challenging scenarios. Three key contributions achieved by our system are: (1) a progressive contrast enhancement method to adaptively enhance contrast of challenging pixels that were otherwise indistinguishable, (2) a boundary refinement method to effectively improve segmentation accuracy at vessel borders based on Canny edge detection, and (3) a content-aware region-of-interests (ROI) adjustment method to automatically determine the locations and sizes of ROIs which contain ambiguous pixels and demand further verification. Extensive evaluation of our method is conducted on both 2D and 3D datasets. On a public 2D retinal dataset (named DRIVE (Staal 2004 IEEE Trans. Med. Imaging 23 501-9)) and our 2D clinical cerebral dataset, our approach achieves superior performance to the state-of-the-art methods including a vesselness based method (Frangi 1998 Int. Conf. on Medical Image Computing and Computer-Assisted Intervention) and an optimally oriented flux (OOF) based method (Law and Chung 2008 European Conf. on Computer Vision). An evaluation on 11 clinical 3D CTA cerebral datasets shows that our method can achieve 94% average accuracy with respect to the manual segmentation reference, which is 23% to 33% better than the five baseline methods (Yushkevich 2006 Neuroimage 31 1116-28; Law and Chung 2008 European Conf. on Computer Vision; Law and Chung 2009 IEEE Trans. Image Process. 18 596-612; Wang 2015 J. Neurosci. Methods 241 30-6) with manually optimized parameters. Our system has also been applied clinically for cerebral aneurysm development analysis. Experimental results on 10 patients’ data, with two 3D CT scans per patient, show that our system’s automatic diagnosis outcomes are consistent with clinicians’ manual measurements.

Creating a Vision Channel for Observing Deep-Seated Anatomy in Medical Augmented Reality

NASA Astrophysics Data System (ADS)

Wimmer, Felix; Bichlmeier, Christoph; Heining, Sandro M.; Navab, Nassir

The intent of medical Augmented Reality (AR) is to augment the surgeon's real view on the patient with the patient's interior anatomy resulting from a suitable visualization of medical imaging data. This paper presents a fast and user-defined clipping technique for medical AR allowing for cutting away any parts of the virtual anatomy and images of the real part of the AR scene hindering the surgeon's view onto the deepseated region of interest. Modeled on cut-away techniques from scientific illustrations and computer graphics, the method creates a fixed vision channel to the inside of the patient. It enables a clear view on the focussed virtual anatomy and moreover improves the perception of spatial depth.

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.

Vision-related problems among the workers engaged in jewellery manufacturing.

PubMed

Salve, Urmi Ravindra

2015-01-01

American Optometric Association defines Computer Vision Syndrome (CVS) as "complex of eye and vision problems related to near work which are experienced during or related to computer use." This happens when visual demand of the tasks exceeds the visual ability of the users. Even though problems were initially attributed to computer-related activities subsequently similar problems are also reported while carrying any near point task. Jewellery manufacturing activities involves precision designs, setting the tiny metals and stones which requires high visual attention and mental concentration and are often near point task. It is therefore expected that the workers engaged in jewellery manufacturing may also experience symptoms like CVS. Keeping the above in mind, this study was taken up (1) To identify the prevalence of symptoms like CVS among the workers of the jewellery manufacturing and compare the same with the workers working at computer workstation and (2) To ascertain whether such symptoms have any permanent vision-related problems. Case control study. The study was carried out in Zaveri Bazaar region and at an IT-enabled organization in Mumbai. The study involved the identification of symptoms of CVS using a questionnaire of Eye Strain Journal, opthalmological check-ups and measurement of Spontaneous Eye Blink rate. The data obtained from the jewellery manufacturing was compared with the data of the subjects engaged in computer work and with the data available in the literature. A comparative inferential statistics was used. Results showed that visual demands of the task carried out in jewellery manufacturing were much higher than that of carried out in computer-related work.

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.

Verification, Validation, and Solution Quality in Computational Physics: CFD Methods Applied to Ice Sheet Physics

NASA Technical Reports Server (NTRS)

Thompson, David E.

2005-01-01

Procedures and methods for veri.cation of coding algebra and for validations of models and calculations used in the aerospace computational fluid dynamics (CFD) community would be ef.cacious if used by the glacier dynamics modeling community. This paper presents some of those methods, and how they might be applied to uncertainty management supporting code veri.cation and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modeling are discussed. After establishing sources of uncertainty and methods for code veri.cation, the paper looks at a representative sampling of veri.cation and validation efforts that are underway in the glacier modeling community, and establishes a context for these within an overall solution quality assessment. Finally, a vision of a new information architecture and interactive scienti.c interface is introduced and advocated.

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

The photochemical determinants of color vision: revealing how opsins tune their chromophore's absorption wavelength.

PubMed

Wang, Wenjing; Geiger, James H; Borhan, Babak

2014-01-01

The evolution of a variety of important chromophore-dependent biological processes, including microbial light sensing and mammalian color vision, relies on protein modifications that alter the spectral characteristics of a bound chromophore. Three different color opsins share the same chromophore, but have three distinct absorptions that together cover the entire visible spectrum, giving rise to trichromatic vision. The influence of opsins on the absorbance of the chromophore has been studied through methods such as model compounds, opsin mutagenesis, and computational modeling. The recent development of rhodopsin mimic that uses small soluble proteins to recapitulate the binding and wavelength tuning of the native opsins provides a new platform for studying protein-regulated spectral tuning. The ability to achieve far-red shifted absorption in the rhodopsin mimic system was attributed to a combination of the lack of a counteranion proximal to the iminium, and a uniformly neutral electrostatic environment surrounding the chromophore. © 2014 WILEY Periodicals, Inc.

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.

[A simulation study with finite element model on the unequal loss of peripheral vision caused by acceleration].

PubMed

Geng, Xiaoqi; Liu, Xiaoyu; Liu, Songyang; Xu, Yan; Zhao, Xianliang; Wang, Jie; Fan, Yubo

2017-04-01

An unequal loss of peripheral vision may happen with high sustaining multi-axis acceleration, leading to a great potential flight safety hazard. In the present research, finite element method was used to study the mechanism of unequal loss of peripheral vision. Firstly, a 3D geometric model of skull was developed based on the adult computer tomography (CT) images. The model of double eyes was created by mirroring with the previous right eye model. Then, the double-eye model was matched to the skull model, and fat was filled between eyeballs and skull. Acceleration loads of head-to-foot (G z ), right-to-left (G y ), chest-to-back (G x ) and multi-axis directions were applied to the current model to simulate dynamic response of retina by explicit dynamics solution. The results showed that the relative strain of double eyes was 25.7% under multi-axis acceleration load. Moreover, the strain distributions showed a significant difference among acceleration loaded in different directions. It indicated that a finite element model of double eyes was an effective means to study the mechanism of an unequal loss of peripheral vision at sustaining high multi-axis acceleration.

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.

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.

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.

Visual ergonomics in the workplace.

PubMed

Anshel, Jeffrey R

2007-10-01

This article provides information about visual function and its role in workplace productivity. By understanding the connection among comfort, health, and productivity and knowing the many options for effective ergonomic workplace lighting, the occupational health nurse can be sensitive to potential visual stress that can affect all areas of performance. Computer vision syndrome-the eye and vision problems associated with near work experienced during or related to computer use-is defined and solutions to it are discussed.

A Feasibility Study of View-independent Gait Identification

DTIC Science & Technology

2012-03-01

ice skates . For walking, the footprint records for single pixels form clusters that are well separated in space and time. (Any overlap of contact...Pattern Recognition 2007, 1-8. Cheng M-H, Ho M-F & Huang C-L (2008), "Gait Analysis for Human Identification Through Manifold Learning and HMM... Learning and Cybernetics 2005, 4516-4521 Moeslund T B & Granum E (2001), "A Survey of Computer Vision-Based Human Motion Capture", Computer Vision

Observability/Identifiability of Rigid Motion under Perspective Projection

DTIC Science & Technology

1994-03-08

Faugeras and S. Maybank . Motion from point mathces: multiplicity of solutions. Int. J, of Computer Vision, 1990. [16] D.B. Gennery. Tracking known...sequences. Int. 9. of computer vision, 1989. [37] S. Maybank . Theory of reconstruction from image motion. Springer Verlag, 1992. [38] Andrea 6...defined in section 5; in this appendix we show a simple characterization which is due to Faugeras and Maybank [15, 371. Theorem B.l . Let Q = UCVT

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.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

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.

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.

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.

Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators

PubMed Central

Demongeot, Jacques; Fouquet, Yannick; Tayyab, Muhammad; Vuillerme, Nicolas

2009-01-01

Background Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. Methodology First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. Conclusions We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery. PMID:19547712

An adhered-particle analysis system based on concave points

NASA Astrophysics Data System (ADS)

Wang, Wencheng; Guan, Fengnian; Feng, Lin

2018-04-01

Particles adhered together will influence the image analysis in computer vision system. In this paper, a method based on concave point is designed. First, corner detection algorithm is adopted to obtain a rough estimation of potential concave points after image segmentation. Then, it computes the area ratio of the candidates to accurately localize the final separation points. Finally, it uses the separation points of each particle and the neighboring pixels to estimate the original particles before adhesion and provides estimated profile images. The experimental results have shown that this approach can provide good results that match the human visual cognitive mechanism.

Aircraft cockpit vision: Math model

NASA Technical Reports Server (NTRS)

Bashir, J.; Singh, R. P.

1975-01-01

A mathematical model was developed to describe the field of vision of a pilot seated in an aircraft. Given the position and orientation of the aircraft, along with the geometrical configuration of its windows, and the location of an object, the model determines whether the object would be within the pilot's external vision envelope provided by the aircraft's windows. The computer program using this model was implemented and is described.

Final Report for Geometric Observers and Particle Filtering for Controlled Active Vision

DTIC Science & Technology

2016-12-15

code) 15-12-2016 Final Report 01Sep06 - 09May11 Final Report for Geometric Observers & Particle Filtering for Controlled Active Vision 49414-NS.1Allen...Observers and Particle Filtering for Controlled Active Vision by Allen R. Tannenbaum School of Electrical and Computer Engineering Georgia Institute of...7 2.2.4 Conformal Area Minimizing Flows . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Particle Filters

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.

The neuroscience of vision-based grasping: a functional review for computational modeling and bio-inspired robotics.

PubMed

Chinellato, Eris; Del Pobil, Angel P

2009-06-01

The topic of vision-based grasping is being widely studied in humans and in other primates using various techniques and with different goals. The fundamental related findings are reviewed in this paper, with the aim of providing researchers from different fields, including intelligent robotics and neural computation, a comprehensive but accessible view on the subject. A detailed description of the principal sensorimotor processes and the brain areas involved is provided following a functional perspective, in order to make this survey especially useful for computational modeling and bio-inspired robotic applications.

Military Vision Research Program

DTIC Science & Technology

2011-07-01

accomplishments emanating from this research . • 3 novel computer-based tasks have been developed that measure visual distortions • These tests are based...10-1-0392 TITLE: Military Vision Research Program PRINCIPAL INVESTIGATOR: Dr. Darlene Dartt...CONTRACTING ORGANIZATION: The Schepens Eye Research

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.

Multidisciplinary unmanned technology teammate (MUTT)

NASA Astrophysics Data System (ADS)

Uzunovic, Nenad; Schneider, Anne; Lacaze, Alberto; Murphy, Karl; Del Giorno, Mark

2013-01-01

The U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) held an autonomous robot competition called CANINE in June 2012. The goal of the competition was to develop innovative and natural control methods for robots. This paper describes the winning technology, including the vision system, the operator interaction, and the autonomous mobility. The rules stated only gestures or voice commands could be used for control. The robots would learn a new object at the start of each phase, find the object after it was thrown into a field, and return the object to the operator. Each of the six phases became more difficult, including clutter of the same color or shape as the object, moving and stationary obstacles, and finding the operator who moved from the starting location to a new location. The Robotic Research Team integrated techniques in computer vision, speech recognition, object manipulation, and autonomous navigation. A multi-filter computer vision solution reliably detected the objects while rejecting objects of similar color or shape, even while the robot was in motion. A speech-based interface with short commands provided close to natural communication of complicated commands from the operator to the robot. An innovative gripper design allowed for efficient object pickup. A robust autonomous mobility and navigation solution for ground robotic platforms provided fast and reliable obstacle avoidance and course navigation. The research approach focused on winning the competition while remaining cognizant and relevant to real world applications.

Colour vision in AIDS patients without HIV retinopathy.

PubMed

Sommerhalder, J; Baglivo, E; Barbey, C; Hirschel, B; Roth, A; Pelizzone, M

1998-11-01

Patients suffering from AIDS develop ocular complications, the most frequent being HIV retinopathy. It is however not clear, if functional visual impairments can be observed as early indicators of ocular complications, before clinical diagnosis of HIV retinopathy is made at fundus examination. To address this issue, we measured colour vision in a group of 49 AIDS subjects with normal clinical fundi using the 'two equation method'. This method, combining red-green Rayleigh and the blue-green Moreland metameric matches, enables more complete and quantitative assessments of colour vision than those based on pigmentary tests. Data were collected on our computer controlled colorimeter and compared to those of normal subjects. While most AIDS subjects without HIV retinopathy demonstrated normal colour vision, a significant portion of them had wider matches than normal subjects (11% for the Rayleigh equation and 16% for the Moreland equation). Furthermore, matching ranges of the Moreland equation were significantly correlated with CD4 lymphocyte counts. Patients with low CD4 values tended to produce larger matching ranges than the patients with high CD4 values. A within subject study on 17 patients confirmed this trend and showed that the patients who increased/decreased their CD4 blood counts generally improved/impaired their colour discrimination in the Moreland match. No such correlation was found between the matching ranges of the Rayleigh equation and the CD4 counts. These results show that colour discrimination is slightly reduced in some AIDS subjects, although there are no detectable ocular complications. They also suggest two different types of colour vision impairments in AIDS patients without retinopathy: one reversible process affecting colour discrimination in the blue-green range; and another irreversible process affecting colour discrimination in the red-green range.

Potato Operation: automatic detection of potato diseases

NASA Astrophysics Data System (ADS)

Lefebvre, Marc; Zimmerman, Thierry; Baur, Charles; Guegerli, Paul; Pun, Thierry

1995-01-01

The Potato Operation is a collaborative, multidisciplinary project in the domain of destructive testing of agricultural products. It aims at automatizing pulp sampling of potatoes in order to detect possible viral diseases. Such viruses can decrease fields productivity by a factor of up to ten. A machine, composed of three conveyor belts, a vision system, a robotic arm and controlled by a PC has been built. Potatoes are brought one by one from a bulk to the vision system, where they are seized by a rotating holding device. The sprouts, where the viral activity is maximum, are then detected by an active vision process operating on multiple views. The 3D coordinates of the sampling point are communicated to the robot arm holding a drill. Some flesh is then sampled by the drill, then deposited into an Elisa plate. After sampling, the robot arm washes the drill in order to prevent any contamination. The PC computer simultaneously controls these processes, the conveying of the potatoes, the vision algorithms and the sampling procedure. The master process, that is the vision procedure, makes use of three methods to achieve the sprouts detection. A profile analysis first locates the sprouts as protuberances. Two frontal analyses, respectively based on fluorescence and local variance, confirm the previous detection and provide the 3D coordinate of the sampling zone. The other two processes work by interruption of the master process.

Towards photorealistic and immersive virtual-reality environments for simulated prosthetic vision: integrating recent breakthroughs in consumer hardware and software.

PubMed

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

2014-01-01

Simulated prosthetic vision (SPV) in normally sighted subjects is an established way of investigating the prospective efficacy of visual prosthesis designs in visually guided tasks such as mobility. To perform meaningful SPV mobility studies in computer-based environments, a credible representation of both the virtual scene to navigate and the experienced artificial vision has to be established. It is therefore prudent to make optimal use of existing hardware and software solutions when establishing a testing framework. The authors aimed at improving the realism and immersion of SPV by integrating state-of-the-art yet low-cost consumer technology. The feasibility of body motion tracking to control movement in photo-realistic virtual environments was evaluated in a pilot study. Five subjects were recruited and performed an obstacle avoidance and wayfinding task using either keyboard and mouse, gamepad or Kinect motion tracking. Walking speed and collisions were analyzed as basic measures for task performance. Kinect motion tracking resulted in lower performance as compared to classical input methods, yet results were more uniform across vision conditions. The chosen framework was successfully applied in a basic virtual task and is suited to realistically simulate real-world scenes under SPV in mobility research. Classical input peripherals remain a feasible and effective way of controlling the virtual movement. Motion tracking, despite its limitations and early state of implementation, is intuitive and can eliminate between-subject differences due to familiarity to established input methods.

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.

Four Frames Suffice. A Provisionary Model of Vision and Space,

DTIC Science & Technology

1982-09-01

0 * / Justifi ati AvailabilitY Codes 1. Introduction This paper is an attempt to specify’ a computationally and scientifically plausible model of how...abstract neural compuiting unit and a variety of construtions built of these units and their properties. All of this is part of the connectionist...chosen are inlerided to elucidate the nia’or scientific problems in intermediate level vision and would not be the best choice or a practical computer

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

Identifying local structural states in atomic imaging by computer vision

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

Laanait, Nouamane; Ziatdinov, Maxim; He, Qian

The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both localmore » and non-local information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale-invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect engineered multilayer graphene surface.« less

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.

Identifying local structural states in atomic imaging by computer vision

DOE PAGES

Laanait, Nouamane; Ziatdinov, Maxim; He, Qian; ...

2016-11-02

The availability of atomically resolved imaging modalities enables an unprecedented view into the local structural states of materials, which manifest themselves by deviations from the fundamental assumptions of periodicity and symmetry. Consequently, approaches that aim to extract these local structural states from atomic imaging data with minimal assumptions regarding the average crystallographic configuration of a material are indispensable to advances in structural and chemical investigations of materials. Here, we present an approach to identify and classify local structural states that is rooted in computer vision. This approach introduces a definition of a structural state that is composed of both localmore » and non-local information extracted from atomically resolved images, and is wholly untethered from the familiar concepts of symmetry and periodicity. Instead, this approach relies on computer vision techniques such as feature detection, and concepts such as scale-invariance. We present the fundamental aspects of local structural state extraction and classification by application to simulated scanning transmission electron microscopy images, and analyze the robustness of this approach in the presence of common instrumental factors such as noise, limited spatial resolution, and weak contrast. Finally, we apply this computer vision-based approach for the unsupervised detection and classification of local structural states in an experimental electron micrograph of a complex oxides interface, and a scanning tunneling micrograph of a defect engineered multilayer graphene surface.« less

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration

PubMed Central

Gong, Yuanzheng; Seibel, Eric J.

2017-01-01

Rapid development in the performance of sophisticated optical components, digital image sensors, and computer abilities along with decreasing costs has enabled three-dimensional (3-D) optical measurement to replace more traditional methods in manufacturing and quality control. The advantages of 3-D optical measurement, such as noncontact, high accuracy, rapid operation, and the ability for automation, are extremely valuable for inline manufacturing. However, most of the current optical approaches are eligible for exterior instead of internal surfaces of machined parts. A 3-D optical measurement approach is proposed based on machine vision for the 3-D profile measurement of tiny complex internal surfaces, such as internally threaded holes. To capture the full topographic extent (peak to valley) of threads, a side-view commercial rigid scope is used to collect images at known camera positions and orientations. A 3-D point cloud is generated with multiview stereo vision using linear motion of the test piece, which is repeated by a rotation to form additional point clouds. Registration of these point clouds into a complete reconstruction uses a proposed automated feature-based 3-D registration algorithm. The resulting 3-D reconstruction is compared with x-ray computed tomography to validate the feasibility of our proposed method for future robotically driven industrial 3-D inspection. PMID:28286351

Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration

NASA Astrophysics Data System (ADS)

Gong, Yuanzheng; Seibel, Eric J.

2017-01-01

Rapid development in the performance of sophisticated optical components, digital image sensors, and computer abilities along with decreasing costs has enabled three-dimensional (3-D) optical measurement to replace more traditional methods in manufacturing and quality control. The advantages of 3-D optical measurement, such as noncontact, high accuracy, rapid operation, and the ability for automation, are extremely valuable for inline manufacturing. However, most of the current optical approaches are eligible for exterior instead of internal surfaces of machined parts. A 3-D optical measurement approach is proposed based on machine vision for the 3-D profile measurement of tiny complex internal surfaces, such as internally threaded holes. To capture the full topographic extent (peak to valley) of threads, a side-view commercial rigid scope is used to collect images at known camera positions and orientations. A 3-D point cloud is generated with multiview stereo vision using linear motion of the test piece, which is repeated by a rotation to form additional point clouds. Registration of these point clouds into a complete reconstruction uses a proposed automated feature-based 3-D registration algorithm. The resulting 3-D reconstruction is compared with x-ray computed tomography to validate the feasibility of our proposed method for future robotically driven industrial 3-D inspection.

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.

Probabilistic Modeling and Visualization of the Flexibility in Morphable Models

NASA Astrophysics Data System (ADS)

Lüthi, M.; Albrecht, T.; Vetter, T.

Statistical shape models, and in particular morphable models, have gained widespread use in computer vision, computer graphics and medical imaging. Researchers have started to build models of almost any anatomical structure in the human body. While these models provide a useful prior for many image analysis task, relatively little information about the shape represented by the morphable model is exploited. We propose a method for computing and visualizing the remaining flexibility, when a part of the shape is fixed. Our method, which is based on Probabilistic PCA, not only leads to an approach for reconstructing the full shape from partial information, but also allows us to investigate and visualize the uncertainty of a reconstruction. To show the feasibility of our approach we performed experiments on a statistical model of the human face and the femur bone. The visualization of the remaining flexibility allows for greater insight into the statistical properties of the shape.

Photorefraction of eyes: history and future prospects.

PubMed

Howland, Howard C

2009-06-01

A brief history of photorefraction, i.e., the refraction of eyes by photography or computer image capture, is given. The method of photorefraction originated from an optical scheme for secret communication across the Berlin wall. This scheme used a lens whose focus about infinity was modulated by a movable reflecting surface. From this device, it was recognized that the vertebrate eye was such a reflector and that its double-pass pointspread could be used to compute its degree of defocus. Subsequently, a second, totally independent invention, more accurately termed "photoretinoscopy," used an eccentric light source and obtained retinoscopic-like images of the reflex in the pupil of the subject's eyes. Photoretinoscopy has become the preferred method of photorefraction and has been instantiated in a wide variety of devices used in vision screening and research. This has been greatly helped by the parallel development of computer and digital camera technology. It seems likely that photorefractive methods will continue to be refined and may eventually become ubiquitous in clinical practice.

Improved dense trajectories for action recognition based on random projection and Fisher vectors

NASA Astrophysics Data System (ADS)

Ai, Shihui; Lu, Tongwei; Xiong, Yudian

2018-03-01

As an important application of intelligent monitoring system, the action recognition in video has become a very important research area of computer vision. In order to improve the accuracy rate of the action recognition in video with improved dense trajectories, one advanced vector method is introduced. Improved dense trajectories combine Fisher Vector with Random Projection. The method realizes the reduction of the characteristic trajectory though projecting the high-dimensional trajectory descriptor into the low-dimensional subspace based on defining and analyzing Gaussian mixture model by Random Projection. And a GMM-FV hybrid model is introduced to encode the trajectory feature vector and reduce dimension. The computational complexity is reduced by Random Projection which can drop Fisher coding vector. Finally, a Linear SVM is used to classifier to predict labels. We tested the algorithm in UCF101 dataset and KTH dataset. Compared with existed some others algorithm, the result showed that the method not only reduce the computational complexity but also improved the accuracy of action recognition.

Three-dimensional Imaging and Scanning: Current and Future Applications for Pathology

PubMed Central

Farahani, Navid; Braun, Alex; Jutt, Dylan; Huffman, Todd; Reder, Nick; Liu, Zheng; Yagi, Yukako; Pantanowitz, Liron

2017-01-01

Imaging is vital for the assessment of physiologic and phenotypic details. In the past, biomedical imaging was heavily reliant on analog, low-throughput methods, which would produce two-dimensional images. However, newer, digital, and high-throughput three-dimensional (3D) imaging methods, which rely on computer vision and computer graphics, are transforming the way biomedical professionals practice. 3D imaging has been useful in diagnostic, prognostic, and therapeutic decision-making for the medical and biomedical professions. Herein, we summarize current imaging methods that enable optimal 3D histopathologic reconstruction: Scanning, 3D scanning, and whole slide imaging. Briefly mentioned are emerging platforms, which combine robotics, sectioning, and imaging in their pursuit to digitize and automate the entire microscopy workflow. Finally, both current and emerging 3D imaging methods are discussed in relation to current and future applications within the context of pathology. PMID:28966836

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

Prevalence of vision impairment and refractive error in school children in Ba Ria – Vung Tau province, Vietnam

PubMed Central

Paudel, Prakash; Ramson, Prasidh; Naduvilath, Thomas; Wilson, David; Phuong, Ha Thanh; Ho, Suit M; Giap, Nguyen V

2014-01-01

Background To assess the prevalence of vision impairment and refractive error in school children 12–15 years of age in Ba Ria – Vung Tau province, Vietnam. Design Prospective, cross-sectional study. Participants 2238 secondary school children. Methods Subjects were selected based on stratified multistage cluster sampling of 13 secondary schools from urban, rural and semi-urban areas. The examination included visual acuity measurements, ocular motility evaluation, cycloplegic autorefraction, and examination of the external eye, anterior segment, media and fundus. Main Outcome Measures Visual acuity and principal cause of vision impairment. Results The prevalence of uncorrected and presenting visual acuity ≤6/12 in the better eye were 19.4% (95% confidence interval, 12.5–26.3) and 12.2% (95% confidence interval, 8.8–15.6), respectively. Refractive error was the cause of vision impairment in 92.7%, amblyopia in 2.2%, cataract in 0.7%, retinal disorders in 0.4%, other causes in 1.5% and unexplained causes in the remaining 2.6%. The prevalence of vision impairment due to myopia in either eye (–0.50 diopter or greater) was 20.4% (95% confidence interval, 12.8–28.0), hyperopia (≥2.00 D) was 0.4% (95% confidence interval, 0.0–0.7) and emmetropia with astigmatism (≥0.75 D) was 0.7% (95% confidence interval, 0.2–1.2). Vision impairment due to myopia was associated with higher school grade and increased time spent reading and working on a computer. Conclusions Uncorrected refractive error, particularly myopia, among secondary school children in Vietnam is a major public health problem. School-based eye health initiative such as refractive error screening is warranted to reduce vision impairment. PMID:24299145

Vision training methods for sports concussion mitigation and management.

PubMed

Clark, Joseph F; Colosimo, Angelo; Ellis, James K; Mangine, Robert; Bixenmann, Benjamin; Hasselfeld, Kimberly; Graman, Patricia; Elgendy, Hagar; Myer, Gregory; Divine, Jon

2015-05-05

There is emerging evidence supporting the use vision training, including light board training tools, as a concussion baseline and neuro-diagnostic tool and potentially as a supportive component to concussion prevention strategies. This paper is focused on providing detailed methods for select vision training tools and reporting normative data for comparison when vision training is a part of a sports management program. The overall program includes standard vision training methods including tachistoscope, Brock's string, and strobe glasses, as well as specialized light board training algorithms. Stereopsis is measured as a means to monitor vision training affects. In addition, quantitative results for vision training methods as well as baseline and post-testing *A and Reaction Test measures with progressive scores are reported. Collegiate athletes consistently improve after six weeks of training in their stereopsis, *A and Reaction Test scores. When vision training is initiated as a team wide exercise, the incidence of concussion decreases in players who participate in training compared to players who do not receive the vision training. Vision training produces functional and performance changes that, when monitored, can be used to assess the success of the vision training and can be initiated as part of a sports medical intervention for concussion prevention.

Robust image matching via ORB feature and VFC for mismatch removal

NASA Astrophysics Data System (ADS)

Ma, Tao; Fu, Wenxing; Fang, Bin; Hu, Fangyu; Quan, Siwen; Ma, Jie

2018-03-01

Image matching is at the base of many image processing and computer vision problems, such as object recognition or structure from motion. Current methods rely on good feature descriptors and mismatch removal strategies for detection and matching. In this paper, we proposed a robust image match approach based on ORB feature and VFC for mismatch removal. ORB (Oriented FAST and Rotated BRIEF) is an outstanding feature, it has the same performance as SIFT with lower cost. VFC (Vector Field Consensus) is a state-of-the-art mismatch removing method. The experiment results demonstrate that our method is efficient and robust.

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.

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.

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

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.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

PubMed

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

PubMed Central

Hancke, Gerhard P.

2017-01-01

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs). PMID:28934102

The role of convexity in perceptual completion: beyond good continuation.

PubMed

Liu, Z; Jacobs, D W; Basri, R

1999-01-01

Since the seminal work of the Gestalt psychologists, there has been great interest in understanding what factors determine the perceptual organization of images. While the Gestaltists demonstrated the significance of grouping cues such as similarity, proximity and good continuation, it has not been well understood whether their catalog of grouping cues is complete--in part due to the paucity of effective methodologies for examining the significance of various grouping cues. We describe a novel, objective method to study perceptual grouping of planar regions separated by an occluder. We demonstrate that the stronger the grouping between two such regions, the harder it will be to resolve their relative stereoscopic depth. We use this new method to call into question many existing theories of perceptual completion (Ullman, S. (1976). Biological Cybernetics, 25, 1-6; Shashua, A., & Ullman, S. (1988). 2nd International Conference on Computer Vision (pp. 321-327); Parent, P., & Zucker, S. (1989). IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 823-839; Kellman, P. J., & Shipley, T. F. (1991). Cognitive psychology, Liveright, New York; Heitger, R., & von der Heydt, R. (1993). A computational model of neural contour processing, figure-ground segregation and illusory contours. In Internal Conference Computer Vision (pp. 32-40); Mumford, D. (1994). Algebraic geometry and its applications, Springer, New York; Williams, L. R., & Jacobs, D. W. (1997). Neural Computation, 9, 837-858) that are based on Gestalt grouping cues by demonstrating that convexity plays a strong role in perceptual completion. In some cases convexity dominates the effects of the well known Gestalt cue of good continuation. While convexity has been known to play a role in figure/ground segmentation (Rubin, 1927; Kanizsa & Gerbino, 1976), this is the first demonstration of its importance in perceptual completion.

Clinical Characteristics and Low Vision Rehabilitation Methods for Partially Sighted School-Age Children

PubMed Central

Özen Tunay, Zuhal; Çalışkan, Deniz; İdil, Aysun; Öztuna, Derya

2016-01-01

Objectives: To determine the clinical features and the distribution of diagnosis in partially sighted school-age children, to report the chosen low vision rehabilitation methods and to emphasize the importance of low vision rehabilitation. Materials and Methods: The study included 150 partially sighted children between the ages of 6 and 18 years. The distribution of diagnosis, accompanying ocular findings, visual acuity of the children both for near and distance with and without low vision devices, and the methods of low vision rehabilitation (for distance and for near) were determined. The demographic characteristics of the children and the parental consanguinity were recorded. Results: The mean age of children was 10.6 years and the median age was 10 years; 88 (58.7%) of them were male and 62 (41.3%) of them were female. According to distribution of diagnoses among the children, the most frequent diagnosis was hereditary fundus dystrophies (36%) followed by cortical visual impairment (18%). The most frequently used rehabilitation methods were: telescopic lenses (91.3%) for distance vision; magnifiers (38.7%) and telemicroscopic systems (26.0%) for near vision. A significant improvement in visual acuity both for distance and near vision were determined with low vision aids. Conclusion: A significant improvement in visual acuity can be achieved both for distance and near vision with low vision rehabilitation in partially sighted school-age children. It is important for ophthalmologists and pediatricians to guide parents and children to low vision rehabilitation. PMID:27800263

Orientation diffusions.

PubMed

Perona, P

1998-01-01

Diffusions are useful for image processing and computer vision because they provide a convenient way of smoothing noisy data, analyzing images at multiple scales, and enhancing discontinuities. A number of diffusions of image brightness have been defined and studied so far; they may be applied to scalar and vector-valued quantities that are naturally associated with intervals of either the real line, or other flat manifolds. Some quantities of interest in computer vision, and other areas of engineering that deal with images, are defined on curved manifolds;typical examples are orientation and hue that are defined on the circle. Generalizing brightness diffusions to orientation is not straightforward, especially in the case where a discrete implementation is sought. An example of what may go wrong is presented.A method is proposed to define diffusions of orientation-like quantities. First a definition in the continuum is discussed, then a discrete orientation diffusion is proposed. The behavior of such diffusions is explored both analytically and experimentally. It is shown how such orientation diffusions contain a nonlinearity that is reminiscent of edge-process and anisotropic diffusion. A number of open questions are proposed at the end.

Analysis of coherent dynamical processes through computer vision

NASA Astrophysics Data System (ADS)

Hack, M. J. Philipp

2016-11-01

Visualizations of turbulent boundary layers show an abundance of characteristic arc-shaped structures whose apparent similarity suggests a common origin in a coherent dynamical process. While the structures have been likened to the hairpin vortices observed in the late stages of transitional flow, a consistent description of the underlying mechanism has remained elusive. Detailed studies are complicated by the chaotic nature of turbulence which modulates each manifestation of the process and which renders the isolation of individual structures a challenging task. The present study applies methods from the field of computer vision to capture the time evolution of turbulent flow features and explore the associated physical mechanisms. The algorithm uses morphological operations to condense the structure of the turbulent flow field into a graph described by nodes and links. The low-dimensional geometric information is stored in a database and allows the identification and analysis of equivalent dynamical processes across multiple scales. The framework is not limited to turbulent boundary layers and can also be applied to different types of flows as well as problems from other fields of science.

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.

Non-Contact Smartphone-Based Monitoring of Thermally Stressed Structures

PubMed Central

Ozturk, Turgut; Mas, David; Rizzo, Piervincenzo

2018-01-01

The in-situ measurement of thermal stress in beams or continuous welded rails may prevent structural anomalies such as buckling. This study proposed a non-contact monitoring/inspection approach based on the use of a smartphone and a computer vision algorithm to estimate the vibrating characteristics of beams subjected to thermal stress. It is hypothesized that the vibration of a beam can be captured using a smartphone operating at frame rates higher than conventional 30 Hz, and the first few natural frequencies of the beam can be extracted using a computer vision algorithm. In this study, the first mode of vibration was considered and compared to the information obtained with a conventional accelerometer attached to the two structures investigated, namely a thin beam and a thick beam. The results show excellent agreement between the conventional contact method and the non-contact sensing approach proposed here. In the future, these findings may be used to develop a monitoring/inspection smartphone application to assess the axial stress of slender structures, to predict the neutral temperature of continuous welded rails, or to prevent thermal buckling. PMID:29670034

Non-Contact Smartphone-Based Monitoring of Thermally Stressed Structures.

PubMed

Sefa Orak, Mehmet; Nasrollahi, Amir; Ozturk, Turgut; Mas, David; Ferrer, Belen; Rizzo, Piervincenzo

2018-04-18

The in-situ measurement of thermal stress in beams or continuous welded rails may prevent structural anomalies such as buckling. This study proposed a non-contact monitoring/inspection approach based on the use of a smartphone and a computer vision algorithm to estimate the vibrating characteristics of beams subjected to thermal stress. It is hypothesized that the vibration of a beam can be captured using a smartphone operating at frame rates higher than conventional 30 Hz, and the first few natural frequencies of the beam can be extracted using a computer vision algorithm. In this study, the first mode of vibration was considered and compared to the information obtained with a conventional accelerometer attached to the two structures investigated, namely a thin beam and a thick beam. The results show excellent agreement between the conventional contact method and the non-contact sensing approach proposed here. In the future, these findings may be used to develop a monitoring/inspection smartphone application to assess the axial stress of slender structures, to predict the neutral temperature of continuous welded rails, or to prevent thermal buckling.

Railway clearance intrusion detection method with binocular stereo vision

NASA Astrophysics Data System (ADS)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

People detection method using graphics processing units for a mobile robot with an omnidirectional camera

NASA Astrophysics Data System (ADS)

Kang, Sungil; Roh, Annah; Nam, Bodam; Hong, Hyunki

2011-12-01

This paper presents a novel vision system for people detection using an omnidirectional camera mounted on a mobile robot. In order to determine regions of interest (ROI), we compute a dense optical flow map using graphics processing units, which enable us to examine compliance with the ego-motion of the robot in a dynamic environment. Shape-based classification algorithms are employed to sort ROIs into human beings and nonhumans. The experimental results show that the proposed system detects people more precisely than previous methods.

Enhanced image capture through fusion

NASA Technical Reports Server (NTRS)

Burt, Peter J.; Hanna, Keith; Kolczynski, Raymond J.

1993-01-01

Image fusion may be used to combine images from different sensors, such as IR and visible cameras, to obtain a single composite with extended information content. Fusion may also be used to combine multiple images from a given sensor to form a composite image in which information of interest is enhanced. We present a general method for performing image fusion and show that this method is effective for diverse fusion applications. We suggest that fusion may provide a powerful tool for enhanced image capture with broad utility in image processing and computer vision.

Evaluation of Event-Based Algorithms for Optical Flow with Ground-Truth from Inertial Measurement Sensor

PubMed Central

Rueckauer, Bodo; Delbruck, Tobi

2016-01-01

In this study we compare nine optical flow algorithms that locally measure the flow normal to edges according to accuracy and computation cost. In contrast to conventional, frame-based motion flow algorithms, our open-source implementations compute optical flow based on address-events from a neuromorphic Dynamic Vision Sensor (DVS). For this benchmarking we created a dataset of two synthesized and three real samples recorded from a 240 × 180 pixel Dynamic and Active-pixel Vision Sensor (DAVIS). This dataset contains events from the DVS as well as conventional frames to support testing state-of-the-art frame-based methods. We introduce a new source for the ground truth: In the special case that the perceived motion stems solely from a rotation of the vision sensor around its three camera axes, the true optical flow can be estimated using gyro data from the inertial measurement unit integrated with the DAVIS camera. This provides a ground-truth to which we can compare algorithms that measure optical flow by means of motion cues. An analysis of error sources led to the use of a refractory period, more accurate numerical derivatives and a Savitzky-Golay filter to achieve significant improvements in accuracy. Our pure Java implementations of two recently published algorithms reduce computational cost by up to 29% compared to the original implementations. Two of the algorithms introduced in this paper further speed up processing by a factor of 10 compared with the original implementations, at equal or better accuracy. On a desktop PC, they run in real-time on dense natural input recorded by a DAVIS camera. PMID:27199639

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

PubMed Central

Joo, Deokjin; Kwan, Ye-seul; Song, Jongwoo; Pinho, Catarina; Hey, Jody; Won, Yong-Jin

2013-01-01

Background The explosively radiating evolution of cichlid fishes of Lake Malawi has yielded an amazing number of haplochromine species estimated as many as 500 to 800 with a surprising degree of diversity not only in color and stripe pattern but also in the shape of jaw and body among them. As these morphological diversities have been a central subject of adaptive speciation and taxonomic classification, such high diversity could serve as a foundation for automation of species identification of cichlids. Methodology/Principal Finding Here we demonstrate a method for automatic classification of the Lake Malawi cichlids based on computer vision and geometric morphometrics. For this end we developed a pipeline that integrates multiple image processing tools to automatically extract informative features of color and stripe patterns from a large set of photographic images of wild cichlids. The extracted information was evaluated by statistical classifiers Support Vector Machine and Random Forests. Both classifiers performed better when body shape information was added to the feature of color and stripe. Besides the coloration and stripe pattern, body shape variables boosted the accuracy of classification by about 10%. The programs were able to classify 594 live cichlid individuals belonging to 12 different classes (species and sexes) with an average accuracy of 78%, contrasting to a mere 42% success rate by human eyes. The variables that contributed most to the accuracy were body height and the hue of the most frequent color. Conclusions Computer vision showed a notable performance in extracting information from the color and stripe patterns of Lake Malawi cichlids although the information was not enough for errorless species identification. Our results indicate that there appears an unavoidable difficulty in automatic species identification of cichlid fishes, which may arise from short divergence times and gene flow between closely related species. PMID:24204918

Review of 3d GIS Data Fusion Methods and Progress

NASA Astrophysics Data System (ADS)

Hua, Wei; Hou, Miaole; Hu, Yungang

2018-04-01

3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

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.

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

VOLUMNECT: measuring volumes with Kinect

NASA Astrophysics Data System (ADS)

Quintino Ferreira, Beatriz; Griné, Miguel; Gameiro, Duarte; Costeira, João. Paulo; Sousa Santos, Beatriz

2014-03-01

This article presents a solution to volume measurement object packing using 3D cameras (such as the Microsoft KinectTM). We target application scenarios, such as warehouses or distribution and logistics companies, where it is important to promptly compute package volumes, yet high accuracy is not pivotal. Our application auto- matically detects cuboid objects using the depth camera data and computes their volume and sorting it allowing space optimization. The proposed methodology applies to a point cloud simple computer vision and image processing methods, as connected components, morphological operations and Harris corner detector, producing encouraging results, namely an accuracy in volume measurement of 8mm. Aspects that can be further improved are identified; nevertheless, the current solution is already promising turning out to be cost effective for the envisaged scenarios.

FPGA-based real-time phase measuring profilometry algorithm design and implementation

NASA Astrophysics Data System (ADS)

Zhan, Guomin; Tang, Hongwei; Zhong, Kai; Li, Zhongwei; Shi, Yusheng

2016-11-01

Phase measuring profilometry (PMP) has been widely used in many fields, like Computer Aided Verification (CAV), Flexible Manufacturing System (FMS) et al. High frame-rate (HFR) real-time vision-based feedback control will be a common demands in near future. However, the instruction time delay in the computer caused by numerous repetitive operations greatly limit the efficiency of data processing. FPGA has the advantages of pipeline architecture and parallel execution, and it fit for handling PMP algorithm. In this paper, we design a fully pipelined hardware architecture for PMP. The functions of hardware architecture includes rectification, phase calculation, phase shifting, and stereo matching. The experiment verified the performance of this method, and the factors that may influence the computation accuracy was analyzed.

Colour based fire detection method with temporal intensity variation filtration

NASA Astrophysics Data System (ADS)

Trambitckii, K.; Anding, K.; Musalimov, V.; Linß, G.

2015-02-01

Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described. But it is not enough to use only colour information to detect fire properly. The main reason of this is that in the shooting conditions may be a lot of things having colour similar to fire. A temporary intensity variation of pixels is used to separate them from the fire. These variations are averaged over the series of several frames. This algorithm shows robust work and was realised as a computer program by using of the OpenCV library.

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed Central

Tsotsos, John K.

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide. PMID:28848458

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed

Tsotsos, John K

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide.

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.

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.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision

PubMed Central

Wu, Dung-Sheng

2018-01-01

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time. PMID:29565303

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision.

PubMed

Ho, Chao-Ching; Wu, Dung-Sheng

2018-03-22

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool electrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with the machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling processes were used to analyze the captured image of the state of the spark discharge at the tip and sidewall of the electrode. The results indicated an association between the accumulative size of the SACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths of the SACE-machined holes were a proportional function of the accumulative spark size with a high degree of correlation. The study proposes an innovative computer vision-based method to estimate the deepness and status of SACE-drilled holes in real time.

The Interdependence of Computers, Robots, and People.

ERIC Educational Resources Information Center

Ludden, Laverne; And Others

Computers and robots are becoming increasingly more advanced, with smaller and cheaper computers now doing jobs once reserved for huge multimillion dollar computers and with robots performing feats such as painting cars and using television cameras to simulate vision as they perform factory tasks. Technicians expect computers to become even more…

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

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.

Reading Digital with Low Vision

PubMed Central

Legge, Gordon E.

2017-01-01

Reading difficulty is a major consequence of vision loss for more than four million Americans with low vision. Difficulty in accessing print imposes obstacles to education, employment, social interaction and recreation. In recent years, research in vision science has made major strides in understanding the impact of low vision on reading, and the dependence of reading performance on text properties. The ongoing transition to the production and distribution of digital documents brings about new opportunities for people with visual impairment. Digital documents on computers and mobile devices permit customization of print size, spacing, font style, contrast polarity and page layout to optimize reading displays for people with low vision. As a result, we now have unprecedented opportunities to adapt text format to meet the needs of visually impaired readers. PMID:29242668

Vision Training Methods for Sports Concussion Mitigation and Management

PubMed Central

Clark, Joseph F.; Colosimo, Angelo; Ellis, James K.; Mangine, Robert; Bixenmann, Benjamin; Hasselfeld, Kimberly; Graman, Patricia; Elgendy, Hagar; Myer, Gregory; Divine, Jon

2015-01-01

There is emerging evidence supporting the use vision training, including light board training tools, as a concussion baseline and neuro-diagnostic tool and potentially as a supportive component to concussion prevention strategies. This paper is focused on providing detailed methods for select vision training tools and reporting normative data for comparison when vision training is a part of a sports management program. The overall program includes standard vision training methods including tachistoscope, Brock’s string, and strobe glasses, as well as specialized light board training algorithms. Stereopsis is measured as a means to monitor vision training affects. In addition, quantitative results for vision training methods as well as baseline and post-testing *A and Reaction Test measures with progressive scores are reported. Collegiate athletes consistently improve after six weeks of training in their stereopsis, *A and Reaction Test scores. When vision training is initiated as a team wide exercise, the incidence of concussion decreases in players who participate in training compared to players who do not receive the vision training. Vision training produces functional and performance changes that, when monitored, can be used to assess the success of the vision training and can be initiated as part of a sports medical intervention for concussion prevention. PMID:25992878

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.

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

PubMed

Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

2017-01-01

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands

PubMed Central

Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

2016-01-01

Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too. PMID:27656140

Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands.

PubMed

Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

2016-01-01

Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too.

A clinical study on "Computer vision syndrome" and its management with Triphala eye drops and Saptamrita Lauha.

PubMed

Gangamma, M P; Poonam; Rajagopala, Manjusha

2010-04-01

American Optometric Association (AOA) defines computer vision syndrome (CVS) as "Complex of eye and vision problems related to near work, which are experienced during or related to computer use". Most studies indicate that Video Display Terminal (VDT) operators report more eye related problems than non-VDT office workers. The causes for the inefficiencies and the visual symptoms are a combination of individual visual problems and poor office ergonomics. In this clinical study on "CVS", 151 patients were registered, out of whom 141 completed the treatment. In Group A, 45 patients had been prescribed Triphala eye drops; in Group B, 53 patients had been prescribed the Triphala eye drops and SaptamritaLauha tablets internally, and in Group C, 43 patients had been prescribed the placebo eye drops and placebo tablets. In total, marked improvement was observed in 48.89, 54.71 and 06.98% patients in groups A, B and C, respectively.

Enhanced flyby science with onboard computer vision: Tracking and surface feature detection at small bodies

NASA Astrophysics Data System (ADS)

Fuchs, Thomas J.; Thompson, David R.; Bue, Brian D.; Castillo-Rogez, Julie; Chien, Steve A.; Gharibian, Dero; Wagstaff, Kiri L.

2015-10-01

Spacecraft autonomy is crucial to increase the science return of optical remote sensing observations at distant primitive bodies. To date, most small bodies exploration has involved short timescale flybys that execute prescripted data collection sequences. Light time delay means that the spacecraft must operate completely autonomously without direct control from the ground, but in most cases the physical properties and morphologies of prospective targets are unknown before the flyby. Surface features of interest are highly localized, and successful observations must account for geometry and illumination constraints. Under these circumstances onboard computer vision can improve science yield by responding immediately to collected imagery. It can reacquire bad data or identify features of opportunity for additional targeted measurements. We present a comprehensive framework for onboard computer vision for flyby missions at small bodies. We introduce novel algorithms for target tracking, target segmentation, surface feature detection, and anomaly detection. The performance and generalization power are evaluated in detail using expert annotations on data sets from previous encounters with primitive bodies.

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.

Sensory Information Processing and Symbolic Computation

DTIC Science & Technology

1973-12-31

plague all image deblurring methods when working with high signal to noise ratios, is that of a ringing or ghost image phenomenon which surrounds high...Figure 11 The Impulse Response of an All-Pass Random Phase Filter 24 Figure 12 (a) Unsmoothed Log Spectra of the Sentence "The pipe began to...of automatic deblurring of images, linear predictive coding of speech and the refinement and application of mathematical models of human vision and

Vision-Based Georeferencing of GPR in Urban Areas

PubMed Central

Barzaghi, Riccardo; Cazzaniga, Noemi Emanuela; Pagliari, Diana; Pinto, Livio

2016-01-01

Ground Penetrating Radar (GPR) surveying is widely used to gather accurate knowledge about the geometry and position of underground utilities. The sensor arrays need to be coupled to an accurate positioning system, like a geodetic-grade Global Navigation Satellite System (GNSS) device. However, in urban areas this approach is not always feasible because GNSS accuracy can be substantially degraded due to the presence of buildings, trees, tunnels, etc. In this work, a photogrammetric (vision-based) method for GPR georeferencing is presented. The method can be summarized in three main steps: tie point extraction from the images acquired during the survey, computation of approximate camera extrinsic parameters and finally a refinement of the parameter estimation using a rigorous implementation of the collinearity equations. A test under operational conditions is described, where accuracy of a few centimeters has been achieved. The results demonstrate that the solution was robust enough for recovering vehicle trajectories even in critical situations, such as poorly textured framed surfaces, short baselines, and low intersection angles. PMID:26805842

2013 Progress Report -- DOE Joint Genome Institute

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

None

2013-11-01

In October 2012, we introduced a 10-Year Strategic Vision [http://bit.ly/JGI-Vision] for the Institute. A central focus of this Strategic Vision is to bridge the gap between sequenced genomes and an understanding of biological functions at the organism and ecosystem level. This involves the continued massive-scale generation of sequence data, complemented by orthogonal new capabilities to functionally annotate these large sequence data sets. Our Strategic Vision lays out a path to guide our decisions and ensure that the evolving set of experimental and computational capabilities available to DOE JGI users will continue to enable groundbreaking science.

Dynamic programming and graph algorithms in computer vision.

PubMed

Felzenszwalb, Pedro F; Zabih, Ramin

2011-04-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.

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

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.

A fast two-plus-one phase-shifting algorithm for high-speed three-dimensional shape measurement system

NASA Astrophysics Data System (ADS)

Wang, Wenyun; Guo, Yingfu

2008-12-01

Phase-shifting methods for 3-D shape measurement have long been employed in optical metrology for their speed and accuracy. For real-time, accurate, 3-D shape measurement, a four-step phase-shifting algorithm which has the advantage of its symmetry is a good choice; however, its measurement error is sensitive to any fringe image errors caused by various sources such as motion blur. To alleviate this problem, a fast two-plus-one phase-shifting algorithm is proposed in this paper. This kind of technology will benefit many applications such as medical imaging, gaming, animation, computer vision, computer graphics, etc.

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.

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

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

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.

In his 1960 paper Man-Machine Symbiosis, Licklider predicted that human brains and computing machines will be coupled in a tight partnership that 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. Today we are on the threshold of resurrecting the vision of symbiosis. While Licklider’s original vision suggested a co-equal relationship, here we discuss an updated vision, neo-symbiosis, in which the human holds a superordinate position in an intelligent human-computer collaborative environment. This paper was originally published as a journal article and is being publishedmore » as a chapter in an upcoming book series, Advances in Novel Approaches in Cognitive Informatics and Natural Intelligence.« less

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.

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.

Fast ray-tracing of human eye optics on Graphics Processing Units.

PubMed

Wei, Qi; Patkar, Saket; Pai, Dinesh K

2014-05-01

We present a new technique for simulating retinal image formation by tracing a large number of rays from objects in three dimensions as they pass through the optic apparatus of the eye to objects. Simulating human optics is useful for understanding basic questions of vision science and for studying vision defects and their corrections. Because of the complexity of computing such simulations accurately, most previous efforts used simplified analytical models of the normal eye. This makes them less effective in modeling vision disorders associated with abnormal shapes of the ocular structures which are hard to be precisely represented by analytical surfaces. We have developed a computer simulator that can simulate ocular structures of arbitrary shapes, for instance represented by polygon meshes. Topographic and geometric measurements of the cornea, lens, and retina from keratometer or medical imaging data can be integrated for individualized examination. We utilize parallel processing using modern Graphics Processing Units (GPUs) to efficiently compute retinal images by tracing millions of rays. A stable retinal image can be generated within minutes. We simulated depth-of-field, accommodation, chromatic aberrations, as well as astigmatism and correction. We also show application of the technique in patient specific vision correction by incorporating geometric models of the orbit reconstructed from clinical medical images. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

Omega-3 chicken egg detection system using a mobile-based image processing segmentation method

NASA Astrophysics Data System (ADS)

Nurhayati, Oky Dwi; Kurniawan Teguh, M.; Cintya Amalia, P.

2017-02-01

An Omega-3 chicken egg is a chicken egg produced through food engineering technology. It is produced by hen fed with high omega-3 fatty acids. So, it has fifteen times nutrient content of omega-3 higher than Leghorn's. Visually, its shell has the same shape and colour as Leghorn's. Each egg can be distinguished by breaking the egg's shell and testing the egg yolk's nutrient content in a laboratory. But, those methods were proven not effective and efficient. Observing this problem, the purpose of this research is to make an application to detect the type of omega-3 chicken egg by using a mobile-based computer vision. This application was built in OpenCV computer vision library to support Android Operating System. This experiment required some chicken egg images taken using an egg candling box. We used 60 omega-3 chicken and Leghorn eggs as samples. Then, using an Android smartphone, image acquisition of the egg was obtained. After that, we applied several steps using image processing methods such as Grab Cut, convert RGB image to eight bit grayscale, median filter, P-Tile segmentation, and morphology technique in this research. The next steps were feature extraction which was used to extract feature values via mean, variance, skewness, and kurtosis from each image. Finally, using digital image measurement, some chicken egg images were classified. The result showed that omega-3 chicken egg and Leghorn egg had different values. This system is able to provide accurate reading around of 91%.

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.