This paper addresses design principles and definition of a non-invasive vision system assisting blinds in their dispalcements in non-cooperating environment The global environment perception and understanding is a a k...
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ISBN:
(纸本)0819438626
This paper addresses design principles and definition of a non-invasive vision system assisting blinds in their dispalcements in non-cooperating environment The global environment perception and understanding is a a key problem for such systems. The optical vision is one of sense providing the global information on nearest environment;its association with convenient global environment representation transmitted to blinds via tactile interface allows blinds to locate all moving and fixed obstacles. Adding vision sensor to electronic travel aid (ETA) for blinds increases blinds autonomy, helps them to orient and move in safety in 3D environment. The announced principles for vision-based ETA can be easily transposed to any robotics, and especially humanoids, vision system.
Color grading is an important process for various industries such as food processing, fruit and vegetable grading, etc. Quality and price are often determined by the color of product. For example, darker red color for...
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ISBN:
(纸本)0819438626
Color grading is an important process for various industries such as food processing, fruit and vegetable grading, etc. Quality and price are often determined by the color of product. For example, darker red color for apples means higher price. In color machine vision applications, image is acquired with a color CCD camera that outputs color information in three channels, red, green, and blue. When grading color, these three primary colors must be processed to determine the color level for separation. A very popular color space conversion technique for color image processing is RGB-to-HSI, where HSI represents hue, saturation and intensity, respectively. However, the conversion result is still three-dimensional information that makes determining color grades very difficult. A new color space conversion technique that can be implemented for high-speed real-time processing for color grading is introduced in this paper. Depending on the application, different color space conversion equations must be used. The result of this technique is a simple one-dimensional array that represents different color levels. This linear array makes linear color grading adjustment possible.
This paper presents a study of the impact of MMX technology and PIII Streaming SIMD (Single Instruction stream, Multiple Data stream) Extensions in image processing and machine vision application, which, because of th...
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ISBN:
(纸本)0819438626
This paper presents a study of the impact of MMX technology and PIII Streaming SIMD (Single Instruction stream, Multiple Data stream) Extensions in image processing and machine vision application, which, because of their hard real time constrains, is an undoubtedly challenging task. A comparison with a traditional scalar code and with another parallel SIMD architecture (IMAP-vision board) is discussed with emphasize of the particular programming strategies for speed optimization. More precisely we discuss the low level and intermediate level image processing algorithms, which are best suited for parallel SIMD implementation. High-level image processing algorithms are more suitable for parallel implementation on MIMD architectures. While the IMAP-vision system performs better because of the large number of processing elements, the MMX processor and PIII (with Streaming SIMD Extensions) remains a good candidate for low-level image processing.
vision is a part of a larger informational system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image ...
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ISBN:
(纸本)0819438626
vision is a part of a larger informational 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. The solution to Image Understanding problems is suggested in form of active multilevel hierarchical networks represented dually as discrete and continuous structures. Computational intelligence methods transform images into model-based knowledge representation. Certainty Dimension converts attractors in neural networks into fuzzy sets, preserving input-output relationships. Symbols naturally emerge in such networks. Symbolic Space is a dual structure that combines closed distributed space split by the set of fuzzy regions, and discrete set of symbols equivalent to the cores of regions represented as points in the Certainty dimension. Model Space carries knowledge in form of links and relations between the symbols, and supports graph, diagrammatic and topological operations. Composition of spaces works similar to M. Minsky frames and agents, Gerard Edelman's "maps of maps", etc., combining machine learning, classification and analogy together with induction, deduction and other methods of higher level model-based reasoning. Based on such principles, an Image Understanding system can convert images into knowledge models, effectively resolving uncertainty and ambiguity via feedback projections and does not require supercomputers.
Since 0. Lummer [6] and the industrial development and production of artificial illuminants it became more and more evident that between sunlight and human vision a specific — until today unexplained — "resonan...
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ISBN:
(纸本)0819438626
Since 0. Lummer [6] and the industrial development and production of artificial illuminants it became more and more evident that between sunlight and human vision a specific — until today unexplained — "resonance" condition apparently exists. Therefore the recommendation holds to approximate as much as possible the spectral energy distribution of artificial illuminants to the one of sunlight. Especially in human color vision spectral shifts of illuminants always lead to hue shifts (cornbined Brightness-, Hue-, Saturation-Shifts) in the perception of colors. These hue shifts in human vision adaptively become compensated with more or less time delay, leading to a relatively good "color constancy" under variable illurninants. An — always far from perfect — explanation model, the von Kries-model, attributes this adaptive compensation of hue shifts to the photopigments in the cones of the human retina. Other — less perfect — models attributing this adaptation to cortical functions also exist [1, 2]. In parallel the need becomes evident to realize future color sensors "capable to measure colors normalized to the spectral sensitivity curves of human vision" [7]. It might be registered with satisfaction that a growing objectivity comes into this psychophysical field of color constancy in human vision by the publication of more and more precise data on relevant parameters in the physical conditions of the experiments.
With the low cost of solid-state camera systems, it is now possible to include many cameras on a mobile robot or other machine. However, video processing is still relatively expensive. Therefore it is often desirable ...
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ISBN:
(纸本)0819438626
With the low cost of solid-state camera systems, it is now possible to include many cameras on a mobile robot or other machine. However, video processing is still relatively expensive. Therefore it is often desirable to share several cameras with a single processor. The purpose of this paper is to describe the design of a video switching system that permits eight cameras to be multiplexed with a single chip. Multiples of eight could also easily be accomplished. The heart of the system is a Maxim video switch. The user simply selects using a three-bit control signal, which camera signal is selected. The output of the video switch is then the desired camera image. One application of this video switch is a four camera input system to a mobile robot being constructed at the University of Cincinnati. Other applications include surveillance and other mobile systems. The decision as to which camera to observe can be made automatically from a computer providing a great versatility. For example, supplemental motion detectors could be used to activate the camera selection for a surveillance system. Higher-level logic has been used on our mobile robot application. Still higher-level logic could be used to fuse the video information in various ways before processing. The significance of this device is that it provides a wealth of video information to be used at the discretion of either a human viewer or automatic system.
A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle (AGV) robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an...
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ISBN:
(纸本)0819434302
A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle (AGV) robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by a terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its I;igh robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification which are based on the analysis of the classifying neural network and the Neuro-fuzzy algorithm is presented. The significance of this work lies in the development of a new method for mobile robot navigation.
This paper introduces a fast and efficient indexing approach for both 2D & 3D model-based object recognition in the presence of rotation, translation, and scale Variations of objects. The indexing entries are comp...
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ISBN:
(纸本)0819434302
This paper introduces a fast and efficient indexing approach for both 2D & 3D model-based object recognition in the presence of rotation, translation, and scale Variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A Bst of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.
We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and defect regions found on wooden boards. Specifically we present...
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ISBN:
(纸本)0819434302
We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and defect regions found on wooden boards. Specifically we present a method to find an optimal set of parameters for a given two-dimensional object detection method. The method uses banks of Gabor filters to limit the range of spatial frequencies, where mutually distinct textures differ significantly in their dominant characterizing frequencies. By encoding images into multiple narrow spatial frequency and orientation channels a local classification of texture regions can be achieved. Unlike other methods applying Gabor filters, we do not use a full Gabor transform, but use feature selection techniques to maximize discrimination. The selection method uses a genetic algorithm to optimize various parameters of the system including Gabor weights, and the parameters of morphological pre-processing. We demonstrate the applicability of the method to the task of classifying wooden textures, and report experimental results using the proposed method.
In this paper a sequence of algorithms for image feature point detection and tracking as well as Euclidian reconstruction of rigid three-dimensional objects from point correspondences is presented. For fully automatic...
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ISBN:
(纸本)0819434302
In this paper a sequence of algorithms for image feature point detection and tracking as well as Euclidian reconstruction of rigid three-dimensional objects from point correspondences is presented. For fully automatic point feature detection, grayvalue images are processed. High-curvature points on contours, i.e. contour elements with locally maximal curvature, are tracked using a normalized correlation algorithm. High-curvature points that could be tracked in a sequence of more than three images are used as point features that are eligible for reconstruction. Since the general way to obtain the epipolar, projective, and Euclidian geometries from point feature correspondences is already solved, here the emphasis is on the performance of the algorithms in the presense of noise. Kanatani's epipolar geometry estimation method is improved and this is experimentally validated. Regarding Bougnoux's Euclidian geometry estimation method, the initial linear solution is now obtained with less uncertainty and the non-linear minimization does no longer converge to a hidden solution. Experimental results are given to assess the system performance.
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