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IEEE Region 10 International Conference TENCON

作者： D. O'Mara R. Owens Robotics & Vision Research Group Department of Computer Science University of Western Australia Nedlands WA Australia

An important example of bilateral symmetry in nature is the approximate bilateral symmetry exhibited by humans. Detecting and measuring bilateral symmetry in medical images should provide benefits in a clinical environment. This paper presents a method for detecting the dominant plane of bilateral symmetry in an image of arbitrary dimension and subsequently measuring the degree of bilateral symmetry in the image. By adapting the work of others, we provide a unique solution to the problem by using a simple representation of the data and a more sensitive measure of symmetry.

关键词： Digital images Image edge detection Humans Biomedical imaging Magnetic field measurement Data compression Reflection Medical robotics Robot vision systems Anthropometry

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Designing stereo heads using task domain constraints

Designing stereo heads using task domain constraints

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International Conference on Pattern Recognition

作者： S.M. Thayer C.S. Gourley Electrical and Compute Engineering Department Computer Vision and Robotics Research Laboratory University of Tennessee Knoxville TN USA

A novel paradigm for the synthesis of convergent-axis stereo geometries is presented. This paradigm incorporates constraints that represent task-oriented properties that can be easily derived in many applications of stereo-ranging, particularly those involving manipulation. Given these properties, a solution that selects the set of optimal design parameters, in the sense of accuracy, under the given constraints is presented. Results of this algorithm are discussed and analyzed in terms of the optimality of the minimum-area technique used in the derivation.

关键词： Cameras Stereo vision Solid modeling computer vision Laboratories Lenses Equations Robot vision systems Computational geometry Contracts

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EXPERIMENTS IN ACTIVE vision WITH REAL AND VIRTUAL ROBOT HEADS

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APPLIED INTELLIGENCE 1995年第3期5卷 237-250页

作者： MARAPANE, SB TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department The University of Tennessee Knoxville

In the emerging paradigm of animate vision, the visual processes are not thought of as being independent of cognitive or motor processing, but as an integrated system within the context of visual behavior. Intimate coupling of sensory and motor systems have found to improve significantly the performance of behavior based vision systems. In order to study active vision systems one requires sensory-motor systems. Designing, building, and operating such a test bed is a challenging task. In this paper we describe the status of on-going work in developing a sensory-motor robotic system, R2H, with ten degrees of freedoms (DOF) for research in active vision. To complement the R2H system a Graphical Simulation and Animation (GSA) environment is also developed. The objective of building the GSA system is to create a comprehensive design tool to design and study the behavior of active systems and their interactions with the environment. GSA system aids the researchers to develop high performance and reliable software and hardware in a most effective manner. The GSA environment integrates sensing and motor actions and features complete kinematic simulation of the R2H system, it's sensors and it's workspace. With the aid of the GSA environment a Depth from Focus (DFF), Depth from Vergence, and Depth from Stereo modules are implemented and tested. The power and usefulness of the GSA system as a research tool is demonstrated by acquiring and analyzing images in the real and virtual worlds using the same software implemented and tested in the virtual world.

关键词： ACTIVE vision ROBOT HEADS ROBOT SIMULATION DEPTH EXTRACTION

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A NEURAL-NETWORK FILTER TO DETECT SMALL TARGETS IN HIGH CLUTTER BACKGROUNDS

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IEEE TRANSACTIONS ON NEURAL NETWORKS 1995年第1期6卷 252-257页

作者： SHIRVAIKAR, MV TRIVEDI, MM The Computer Vision and Robotics Research LaboratoryElectrical and Computer Engineering Department University of Tennessee Knoxville TN USA

The detection of objects in high-resolution aerial imagery has proven to be a difficult task. In our application, the amount of image clutter is extremely high. Under these conditions, detection based on low-level image cues tends to perform poorly. Neural network techniques have been proposed in object detection applications due to proven robust performance characteristics. A neural network filter was designed and trained to detect targets in thermal infrared images. The feature extraction stage was eliminated and raw gray levels were utilized as input to the network. Two fundamentally different approaches were used to design the training sets. In the first approach, actual image data were utilized for training. In the second case, a model-based approach was adopted to design the training set vectors. The training set consisted of object and background data. The neuron transfer function was modified to improve network convergence and speed and the backpropagation training algorithm was used to train the network. The neural network filter was tested extensively on real image data. Receiver Operating Characteristic (ROC) curves were determined in each case. The detection and false alarm rates were excellent for the neural network filters. Their overall performance was much superior to that of the size-matched contrast-box filter, especially in the images with higher amounts of visual clutter.

关键词： Neural networks Filters Object detection Infrared detectors Robustness Infrared imaging Feature extraction Neurons Transfer functions Convergence

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LOCALIZED RADON TRANSFORM-BASED DETECTION OF SHIP WAKES IN SAR IMAGES

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1995年第1期33卷 35-45页

作者： COPELAND, AC RAVICHANDRAN, G TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper presents a Radon transform-based approach to the detection of ship wakes in Synthetic Aperture Radar (SAR) images, The key element of this technique is a localization of the Radon transform, whereby the intensity integration is performed over short line segments rather than across the entire image. A linear feature detection algorithm, which utilizes this localized Radon transform, is then developed, In this algorithm, referred to as the feature space line detector (FSLD) algorithm, the transform space is subjected to processing which server to isolate and locate the response of linear features and suppress the responses of false alarms, This algorithm is tested on both synthetic images corrupted by various levels of Weibull multiplicative noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions,

关键词： Marine vehicles Radar detection computer vision Testing Synthetic aperture radar Image segmentation Detection algorithms Detectors Noise level Noise robustness

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CIRCULAR-MELLIN FEATURES FOR TEXTURE SEGMENTATION

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1995年第12期4卷 1629-1640页

作者： RAVICHANDRAN, G TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Dept. University of Tennessee Knoxville TN 37996-2100 USA

Texture is an important cue in region-based segmentation of images. In this paper, we provide insight into the development of a new set of distortion-invariant texture operators. These ''circular-Mellin'' operators are invariant to both scale and orientation of the target and represent the spectral decomposition of the image scene in the polar-log coordinate system. Coupled with the unique shift invariance property of the correlator architecture, we show that these circular-Mellin operators can be used for rotation-and scale-invariant feature extraction. We note that while these feature extractors have a functional form that is similar to the Gabor operators, they have distortion-invariant characteristics unlike the Gabor functions that make them more suitable for texture segmentation. A detailed analytical description of these operators and segmentation results to highlight their salient properties are presented.

关键词： Feature extraction Correlation Image segmentation Gabor filters Maximum likelihood detection Correlators Nonlinear filters

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RESIDUAL UNCERTAINTY IN 3-DIMENSIONAL RECONSTRUCTION USING 2-PLANES CALIBRATION AND STEREO METHODS

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PATTERN RECOGNITION 1995年第7期28卷 1073-1082页

作者： THAYER, S TRIVEDI, M Electrical and Computer Engineering Department Computer Vision and Robotics Research Laboratory The University of Tennessee Knoxville TN 37996-2100 U.S.A.

A necessary goal in the calibration of any instrument is an indication of how well the particular device performs. In the specific case where a camera system is used in the process of three-dimensional reconstruction or stereopsis, geometric measures of the accuracy, precision, and repeatability of 3-D point measurements give a quantitative evaluation of the success of that algorithm. This paper presents an experimental performance analysis of a traditional calibration algorithm as applied to the problem of three-dimensional vision. The study begins with an analysis of the algorithm in a single camera or monocular system. Monocular analysis concludes with a derivation of error boundaries under different. geometric constraints. Showing how this residual error propagates from the component monocular systems into a three-dimensional reconstruction, a binocular analysis derives the desired performance monitors. The paper concludes with a geometric interpretation of the results.

关键词： STEREOPSIS ACCURACY PRECISION REPEATABILITY MONOCULAR BINOCULAR 2-PLANES CALIBRATION

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A 3D local energy surface detector for confocal microscope imalges 3

A 3D local energy surface detector for confocal microscope i...

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3rd Australian and New Zealand Conference on Intelligent Information Systems, ANZIIS 1995

作者： Pudney, Chris Kovesi, Peter Robbins, Ben Biomedical Confocal Microscopy Research Centre Department of Pharmacology United States Robotics and Vision Research Group Department of Computer Science University of Western Australia NedlandsWA6907 Australia

ISBN: (纸本)0864224303

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature profiles: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters. The filters are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency-space and multiplied by the image's Fourier transform. Results are presented for real confocal images and synthetic 3D image volumes. © 1995 IEEE. All rights reserved.

关键词： Microscopes

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Feature detection using oriented local energy for 3D confocal microscope images 3rd

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3rd International computer Science Conference, ICSC 1995

作者： Pudney, Chris Kovesi, Peter Robbins, Ben Biomedical Confocal Microscopy Research Centre Department of Pharmacology The University of Western Australia NedlandsWA6907 Australia Robotics and Vision Research Group Department of Computer Science The University of Western Australia NedlandsWA6907 Australia

ISBN: (纸本)9783540606970

The ability to detect features within confocal microscope images is important for the interpretation and analysis of such data. Most detectors are gradient-based, and so are sensitive to noise, and fail to accurately locate some feature types that are important in confocal microscopy. The local energy feature detector developed by Morrone and Owens marks locations where there is maximal congruence of phase in the Fourier components of an image. Points of maximal phase congruency occur at all common feature types: step and roof edges, line features and Mach bands. A 3D implementation of the local energy feature detector, suitable for confocal microscope data, is presented. The detector computes local energy by convolving an image with oriented pairs of 3D filters that are 3D versions of Morlet wavelets. To increase the speed of the convolution, the filters are designed in frequency-space and multiplied by the image's Fourier transform. Results are presented for real confocal images and a synthetic 3D image volume. These results are compared with those from a 3D implementation of the Sobel edge detecto. © Springer-Verlag Berlin Heidelberg 1995.

关键词： Feature extraction

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Depth extraction using lateral or axial camera motion: an integration of depth from motion and stereo

Depth extraction using lateral or axial camera motion: an in...

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IEEE International Conference on Image Processing

作者： A.K. Dalmia M.M. Trivedi Web Systems Group Datacube Inc. Danvers MA USA Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficiency of spatial and temporal gradient analysis. As a result of this integration, depth measurements of a high quality are obtained at a speed approximately ten-times higher than that of stereo processing. Without any a priori information of the locations of the points in the scene, the correspondence problem in stereo processing is computationally expensive. In our approach, we use the spatial and temporal gradient analysis, which has been shown to provide the depth with a high efficiency but limited accuracy, to guide the stereo matching process. Experiments for lateral and axial camera translations have acquired depth results with a mean error of less than 3 percent.

关键词： Cameras Displacement measurement Robot vision systems computer vision Equations Laboratories Data engineering Velocity measurement Layout Energy resolution

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