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检索条件"机构=Computer Vision and Image Processing Laboratory Electrical and Computer Engineering"

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Velocity tuned generalized Sobel operators for multiresolution computation of optical flow

Velocity tuned generalized Sobel operators for multiresoluti...

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IEEE International Conference on image processing

作者： M. Gokstorp P.-E. Danielsson Image Processing Laboratory Computer Engineering Division Department of Electrical Engineering Linköping University Sweden

Optical flow computation may be divided into four processing steps where the first is extraction of image features suitable for flow estimation. Using a generalization of the basic flow constraint it is possible to estimate flow vectors from a set of feature images obtained from the input image sequence. Generalized Sobel operators provide a suitable set of feature extraction operators. The set of five filters up to second order provides good approximations of ideal edge and line detectors. A review of spatial and frequency constraints on optical flow suggests a multiresolution approach to optical flow where the initial feature extractors consists of velocity tuned operators. We show that two-dimensional generalized Sobel operators may be extended to spatio-temporal velocity tuned filters for optical flow estimation. Experimental results compare well to existing methods.< >

关键词： Optical computing image motion analysis Optical filters Band pass filters Gabor filters Feature extraction Spatial resolution Frequency Equations image edge detection

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Analysis of texture images using robust fractal description

Analysis of texture images using robust fractal description

引用

1995 IEEE Southwest Symposium on image Analysis and Interpretation, IAI 1994

作者： Avadhanam, N. Mitra, S. Center for Image Processing and Integrated Computing Dept. of Electr. and Comput. Eng. California Univ. DavisCA95616 United States Computer Vision and Image Analysis Lab Dept. of Electrical Engineering Texas Tech University LubbockTX79401 United States

ISBN: (纸本)0818662506

A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to the lacunarity measure is used to characterize natural textures since fractal dimension alone cannot totally characterize texture images. Segmentation of natural textures is successfully achieved by a k-means clustering algorithm using fractal dimension and the additional measure as representative features. © 1994 IEEE.

关键词： image texture

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Analysis of texture images using robust fractal description

Analysis of texture images using robust fractal description

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IEEE Southwest Symposium on image Analysis and Interpretation

作者： N. Avadhanam S. Mitra Center for Image Processing & Integrated Computing Department of Electrical & Computer Engineering University of California Davis CA USA Computer Vision and Image Analysis Lab Department of Electrical Engineering Texas Tech University Lubbock TX USA

关键词： image analysis image texture analysis Robustness Fractals Maximum likelihood estimation image segmentation Polymers image motion analysis computer vision Clustering algorithms

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New morphological operators: BERD and BDRE

New morphological operators: BERD and BDRE

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IEEE Southwest Symposium on image Analysis and Interpretation

作者： A. Kher S. Mitra Computer Vision and Image Analysis Laboratory Department of Electrical Engineering Texas Tech University Lubbock TX USA

The authors briefly describe their new morphological operators of "boundary erosion region dilation (BERD)" and "boundary dilation region erosion (BDRE)". The paper covers definitions, properties, and some of the applications of these operators. BERD and BDRE operations may be used to approximately perform the job of various common morphological filtering operations with lesser computational times. BERD and BDRE operations with 2-D structuring elements may be used to construct robust connectivity preserving filters. Unlike commonly used median closing and opening operators/sup 1,5,6/, these filters do not destroy thin regions which rapidly change their direction or the regions which can not be probed by straight lines in limited directions. They have used these connectivity preserving filters for removing speckle noise from SAR images while retaining thin regions and fine details of regions boundaries.< >

关键词： Morphological operations Filters image analysis image processing Filtering Morphology Pixel computer vision Laboratories Noise robustness

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Handwritten character recognition by an adaptive fuzzy clustering algorithm

Handwritten character recognition by an adaptive fuzzy clust...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： A. Sharan S. Mitra Computer Vision and Image Analysis Laboratory Department of Electrical Engineering Texas Tech University Lubbock TX USA

Unconstrained handwritten characters pose a serious challenge to the development of a recognition algorithm. Many approaches have been studied over the years for such a recognition algorithm. We use an adaptive neuro-fuzzy clustering algorithm for classification and recognition of handwritten characters of a variety of styles and investigate the effectiveness of Fourier coefficients as representative features of handwritten characters in the presence of noise. Our results indicate that the adaptive clustering algorithm outperforms k-means clustering in handwritten character recognition for the same data representation. However some misclassifications cannot be avoided due to inherent problems associated with large variability in handwriting styles and the presence of excessive noise in practice.< >

关键词： Character recognition Clustering algorithms Handwriting recognition Writing Humans Euclidean distance computer vision image analysis Laboratories image recognition

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Fuzzy inferencing with ART networks

Fuzzy inferencing with ART networks

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International Joint Conference on Neural Networks (IJCNN)

作者： S. Mitra Computer Vision and Image Analysis Laboratory Department of Electrical Engineering Texas Tech University Lubbock TX USA

A recent trend in developing adaptive decision models has been to integrate the concept of fuzzy membership functions of data samples with adaptive learning inherent to neural nets. Several different approaches have been suggested for such integration involving Adaptive Resonance Theory (ART) as well as Kohonen self-organizing neural networks. Such neuro-fuzzy models appear to be quite effective in successful clustering of complex data samples encountered in many pattern recognition and control applications where traditional decision models fail due to lack of knowledge of data distributions and unavailability of training data sets. The strengths and weaknesses of currently existing ART-based neuro-fuzzy models are described.< >

关键词： Subspace constraints Clustering algorithms Neural networks Fuzzy neural networks Euclidean distance computer vision image sequence analysis Laboratories Resonance Pattern recognition

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Piecewise and local class models for image restoration

Piecewise and local class models for image restoration

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IEEE International Conference on image processing

作者： S.T. Acton A.C. Bovik School of Electrical Computer Engineering Oklahoma State University Stillwater OK USA Laboratory for Vision SystemsCenter for Vision and Image Science Department of Electrical Computer Engineering University of Texas Austin Austin TX USA

In this paper, we present a new approach to image restoration based on a flexible constraint framework that encapsulates structural assumptions about the uncorrupted image. Piecewise and local class (PALC) models are defined and utilized to restore images degraded by linear blurring and additive noise. The restoration process is accomplished by iteratively deconvolving the solution image while simultaneously optimizing local image characteristics defined by the PALC models. Solution images to this ill-posed, combinatorial problem are computed using the novel generalized deterministic annealing (GDA) optimization technique. The results demonstrate high quality image restoration as measured by local feature integrity, improvement in signal-to-noise ratio, and reduction of restoration artifacts, especially in the presence of heavy-tailed additive noise.< >

关键词： image restoration Additive noise Degradation image edge detection Deconvolution Bismuth computer vision Machine vision image enhancement Maximum likelihood estimation

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Well-defined series and parallel D-spectra for linear time-varying systems

Well-defined series and parallel D-spectra for linear time-v...

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American Control Conference (ACC)

作者： J.J. Zhu Electrical and Computer Engineering DepartmentRemote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA

An nth-order, scalar, linear time-varying (LTV) systems y(n)+/spl Sigma//sub k=1//sup n//spl alpha//sub k/(t)/sup (k-1)/=0 can be conveniently represented as /spl Dscr//sub /spl alpha//{y}=0 using the scalar polynomial. Differential operator (SPDO) /spl Dscr//sub /spl alpha//=/spl delta//sup n/+/spl Sigma//sub k=1//sup n//spl alpha//sub k/(t)/spl delta//sup k-1/, where /spl delta/=d/dt is the derivative operator. Based on a classical result of Floquet (1879) on the factorization of SPDO /spl Dscr//sub /spl alpha//=(/spl delta/-/spl lambda//sub n/(t))...(/spl delta/-/spl lambda//sub 1/(t)), a unified eigenvalue theory has recently been developed. In that theory the collection {/spl lambda//sub k/(t)}/sub k=1//sup n/ are called a series D-spectrum (SD-spectrum) for /spl Dscr//sub /spl alpha// and an n-parameter family {/spl rho//sub k/(t)=/spl lambda//sub 1,k/(t)}/sub k=1//sup n/ are called a parallel D-spectrum (PD-spectrum) for /spl Dscr//sub /spl alpha//, where /spl lambda//sub 1,k/(t) are particular solutions for /spl lambda//sub 1/(t) satisfying some nonlinear independence constraints. Although more than a century old, the important Floquet factorization has apparently not been fully harnessed in LTV system theory and control, due mainly to the well-known fact that even for a 2nd-order time-invariant SPDO, the PD-eigenvalue /spl rho/(t)=/spl lambda//sub 1/(t) satisfying the scalar Riccati equation /spl lambda//spl dot//sub 1/+/spl lambda//sub 1//sup 2/+/spl alpha//sub 2//spl lambda//sub 1/+/spl alpha//sub 1//spl lambda//sub 1/=0 may suffer from finite-time singularities known as finite-escapes. In this paper, necessary and sufficient conditions for the existence of well-defined (free of finite-time singularities) SD- and PD-spectra for SPDOs with complex- and real-valued coefficients are presented. The new results will have significant impact on applications of the unified eigenvalue theory to the analysis and control of LTV systems, and its further development.

关键词： Time varying systems Eigenvalues and eigenfunctions Control systems Riccati equations Polynomials Constraint theory Control system analysis Remote sensing image processing Laboratories

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Parallel D-eigenvalues and parallel D-eigenvectors for linear time-varying systems

Parallel D-eigenvalues and parallel D-eigenvectors for linea...

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Southeastern Symposium on System Theory

作者： J.J. Zhu Electrical and Computer Engineering Department Remote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA

Singular behavior of PD-eigenvalues of an nth-order scalar polynomial differential operator (SPDO) /spl Dscrsub /spl alpha=/spl deltasup n/+/spl Sigmasub k=1sup nspl alphasub k/(t)/spl deltasup k/spl minus/1/, where /spl delta/=d/dt, is investigated. Main results of this paper include: (i) definition and properties of PD-eigenvectors associated with PD-eigenvalues, (ii) definitions and properties of generalized PD-eigenvectors and generalized PD-eigenvalues for singular PD-eigenvalues; (iii) application of (i) and (ii) in stability analysis of linear time-varying (LTV) systems /spl Dscrsub /spl alpha/spl lcub/y/spl rcub/=0, and (iv) application (i) and (ii) in the realization of PD-characteristic equation. The new results will have a significant impact on applications of the unified eigenvalue theory to the analysis and control of LTV control systems, and its further development.< >

关键词： Time varying systems Eigenvalues and eigenfunctions Control systems Polynomials Stability analysis Control system analysis Riccati equations Remote sensing image processing Laboratories

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Meromorphic D-similarity transformation for linear time-varying systems

Meromorphic D-similarity transformation for linear time-vary...

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Southeastern Symposium on System Theory

作者： J.J. Zhu Electrical and Computer Engineering Department Remote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA

This study constitutes an effort in identifying a class of unbounded coordinate transformations for vector linear time-varying systems of the form x/spl dot/=A(t)x. Main results of this paper include: (i) the definition and properties of meromorphic D-similarity transformations, (ii) two theorems on stability preserving meromorphic transformations. The results appear to be somewhat restrictive, but certainly shed some light on this intriguing yet difficult problem.< >

关键词： Time varying systems Polynomials Vectors Stability analysis Remote sensing image processing Laboratories Asymptotic stability

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