The following topics are dealt with: edge and boundary analysis;vision systems;motion;shape and 2-D description;stereo and 3-D description;patternrecognition;3-D models;architectures;vision models and texture;image s...
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ISBN:
(纸本)0818606339
The following topics are dealt with: edge and boundary analysis;vision systems;motion;shape and 2-D description;stereo and 3-D description;patternrecognition;3-D models;architectures;vision models and texture;image segmentation;applications and parallel algorithms;3-D analysis;contour analysis;character recognition;3-D descriptions from multiple views;and parallel architectures for imageprocessing. 123 papers were presented, of which 121 are published in full in the present proceedings.
The Bayesian segmentation model developed is motivated by consideration of the information needed for higher-level visual processing. A segmentation is regarded as a collection of parameters defining an image-valued s...
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ISBN:
(纸本)0818621486
The Bayesian segmentation model developed is motivated by consideration of the information needed for higher-level visual processing. A segmentation is regarded as a collection of parameters defining an image-valued stochastic process by separating topological (adjacency) and metric (shape) properties of the subdivision and intensity properties of each region. The prior selection is structured accordingly. The novel part of the representation, the subdivision topology, is assigned a prior by universal coding arguments, using the minimum description-length philosophy that the best segmentation allows the most efficient representation of visual data.< >
The three articles in this special section are selected papers from the ieee CS conference on computer Vision and patternrecognition that was held in Anchorage, AL, in June 2008.
The three articles in this special section are selected papers from the ieee CS conference on computer Vision and patternrecognition that was held in Anchorage, AL, in June 2008.
A recursive algorithm is given to directly compute the fast Fourier Transform (FFT) of a two-dimensional image array. The algorithm builds the FFT of a 2**m by 2**m matrix left bracket f right bracket by first mapping...
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A recursive algorithm is given to directly compute the fast Fourier Transform (FFT) of a two-dimensional image array. The algorithm builds the FFT of a 2**m by 2**m matrix left bracket f right bracket by first mapping its entries to form a new matrix left bracket f//1 right bracket , in a manner analogous to that used in one-dimensional FFT's. The FT of left bracket f right bracket is then found by computing the FT of all 2 by 2 submatrices of left bracket f//1 right bracket and recursively combining them into higher level submatrices until the 2**m by 2**m level is reached. This algorithm is shown to be computationally faster than the conventional method based on one-dimensional FFT's. The main features of this method, however, are its simplicity of updating the FFT of an image array when some of the array elements have been modified, and its suitability for implementation on a multiprocessor computer system. Applications of this algorithm to imageprocessing.are discussed and illustrative examples are given.
This work considers the problem of discovering areas of convergence of line-like shapes in an image. The motivating application is to use the convergence of the blood vessel network to automatically locate the optic n...
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ISBN:
(纸本)0818684976
This work considers the problem of discovering areas of convergence of line-like shapes in an image. The motivating application is to use the convergence of the blood vessel network to automatically locate the optic nerve in an ocular fundus image. A fuzzy segment model is proposed, based on a conjecture that line-like shapes only contribute to a perception of convergence in their near neighborhood. Using this model, a voting-type method is described to compute a convergence image, which can be searched for one absolute, or one or more relative, strongest points of convergence. Results are presented for twenty ocular fundus images, with a 65% success rate for finding the optic nerve.
This paper presents a general formulation enabling construction of all functions that are steerable under any transformation group. The method is based on a Lie-group theoretic approach.
ISBN:
(纸本)0818672587
This paper presents a general formulation enabling construction of all functions that are steerable under any transformation group. The method is based on a Lie-group theoretic approach.
The intensity-images captured by Time-of-Flight (ToF)-cameras are biased in several ways. The values differ significantly, depending on the integration time set within the camera and on the distance of the scene. Wher...
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ISBN:
(纸本)9781424423392
The intensity-images captured by Time-of-Flight (ToF)-cameras are biased in several ways. The values differ significantly, depending on the integration time set within the camera and on the distance of the scene. Whereas the integration time leads to an almost linear scaling of the whole image, the attenuation due to the distance is nonlinear resulting in higher intensities for objects closer to the camera. The background regions that are farther away contain comparably low values, leading to a bad contrast within the image. Another effect is that some kind of specularity may be observed due to uncommon reflecting conditions at some points within the scene. These three effects lead to intensity, images which exhibit significantly different values depending on the integration time of the camera and the distance to the scene, thus making parameterization of processing.steps like edge-detection, segmentation, registration and threshold computation a tedious task. Additionally, outliers with exceptionally high values lead to insufficient visualization results and problems in processing. In this work we propose scaling techniques which generate images whose intensities are independent of the integration time of the camera and the measured distance. Furthermore, a simple approach for reducing specularity effects is introduced.
It is shown that the Hough transform may be used for encoding of line curves and waveforms that consist of the concatenation of curves from an underlying set of families of curves. Several properties of the transform ...
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It is shown that the Hough transform may be used for encoding of line curves and waveforms that consist of the concatenation of curves from an underlying set of families of curves. Several properties of the transform are given in this context.
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