检索结果-内蒙古大学图书馆

International Conference on Pattern Recognition

作者： R. Bergevin D. Laurendeau D. Poussart Computer Vision and Digital Systems Laboratory Department of Electrical Engineering Laval University QUE Canada

Presents a method to compute the inter-frame transformation between two range image views of complex multi-part objects. No exact feature matching is attempted and no initial approximate transformation is provided. The method is naturally decomposed into two stages of initial estimation and final refinement of the transformation. A hierarchical triangulation-based surface representation provides an efficient way to select the control points at which the alignment of the two surfaces is to be evaluated. This representation also permits the selection of a manageable number of initial transformations among which at least one is to be in the parametric neighborhood of the actual transformation. Experimental results show that the computed transformation between two views of a complex multi-part object may provide angles of rotation within a fraction of a degree of the actual ones.< >

关键词： computer vision Layout Motion estimation Shape Digital systems Laboratories Cameras Object recognition Stereo vision Noise reduction

来源：评论

学校读者我要写书评

暂无评论

On empirical estimation of the parameters of edge enhancement filters

On empirical estimation of the parameters of edge enhancemen...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： A.A. Farag Y. Cao D.M. Rose E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The authors develop an empirical measure for the selection of the Gaussian filter that is commonly used for edge enhancement. The measure is based totally on the image at hand. Edge enhancement by a Gaussian filter has two distinct advantages: (1) the filter is fully described by a single parameter, the standard deviation sigma ; (2) the two-dimensional filter is separable and can be easily implemented. The filter's spatial support is a function of sigma . This support is normally in the range of +or-3.5 sigma . An empirical measure is described for the selection of the Gaussian filter's spatial support using the power spectrum density of the input image. Classic Fourier analysis is used to obtain a measure for the spatial support of the Gaussian filter given a particular image. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support needed to enhance the edges.< >

关键词： Parameter estimation Low pass filters image edge detection image segmentation Joining processes Smoothing methods Frequency estimation Density functional theory Shape Mathematics

来源：评论

学校读者我要写书评

暂无评论

image representation using vector wavelets

Image representation using vector wavelets

引用

International Conference on Pattern Recognition

作者： Y.V. Venkatesh K. Ramani R. Nandini Computer Vision Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science Bangalore India

A new layered representation of images is proposed using, what one may call, vector wavelets defined by generalized Hermite polynomials. This representation has some special properties: it is distinct from and superior to the other wavelet schemes of the literature; it is stable; it transforms the image into matrices of coefficients in the same manner as the standard transforms (Fourier, Hadamard and others), but at the specified 'scales'; the zero-crossings of the signal at various scales can be directly obtained from the coefficients; and the size of the resolution cell in the 'phase-space' is variable even at a specified scale, depending on the image being analysed. This representation has been successfully applied to different types of images, both synthetic and natural.< >

关键词： image representation Fourier transforms Wavelet transforms Polynomials Wavelet analysis Error correction Error correction codes image resolution Signal resolution image analysis

来源：评论

学校读者我要写书评

暂无评论

Anisotropic edge detection using mean field annealing

Anisotropic edge detection using mean field annealing

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： S.T. Acton A.C. Bovik Laboratory for Vision Systems Department of Electrical & Computer Engineering University of Texas Austin Austin TX USA

An edge detection technique that optimizes edge localization while providing edge continuity and edge thinning is introduced. The solution is obtained by annealing a mean field neural network, providing inexpensive solutions with high parameter insensitivity. Anisotropic diffusion is used to provide localized edge data through the scale-space. analysis of network parameters, diffusion parameters, network convergence, and scale-space equivalence is provided. Results are shown for real image data and compared with the results of other important edge detection schemes.< >

关键词： Anisotropic magnetoresistance image edge detection Annealing Smoothing methods Equations Detectors Joining processes Gaussian processes Laboratories Machine vision

来源：评论

学校读者我要写书评

暂无评论

A VLSI Implementation Of A Light Sensor With Imbedded Focal Plane Processing Capabilities

A VLSI Implementation Of A Light Sensor With Imbedded Focal ...

引用

IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： F. Parent M. Tremblay D. Laurendeau D. Poussart Computer Vision and Digital Systems Laboratory Department of Electrical Engineering Laval University Sainte Foy QUE Canada

来源：评论

学校读者我要写书评

暂无评论

Optimal nonlinear pattern restoration from noisy binary figures

Optimal nonlinear pattern restoration from noisy binary figu...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： D. Schonfeld Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

A mathematical framework for the solution of statistical inference problems on a class of random sets is proposed. It is based on a new definition of expected pattern. The least-mean-difference estimator (restoration filter) is proved, under certain conditions, to be equivalent to the minimization of the measure of size (area) of the set-difference between the original pattern and the expected pattern of the estimated (restored) pattern. Consequently, it is proved that, under certain conditions, if the estimator (restoration filter) is unbiased, then it is the least mean difference estimator (restoration filter).< >

关键词： Noise figure image restoration Pattern analysis Filters Set theory Signal restoration Laboratories Area measurement Size measurement Morphology

来源：评论

学校读者我要写书评

暂无评论

A Mean Field Solution to Anisotropic Edge Detection of Remotely Sensed images

A Mean Field Solution to Anisotropic Edge Detection of Remot...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S.T. Acton M.M. Crawford Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Center for Space Research and Department of Mechanical Engineering University of Texas Austin Austin TX USA

来源：评论

学校读者我要写书评

暂无评论

Further Studies on Frozen-Time Eigenvalues in the Stability analysis for Periodic Linear Systems

Further Studies on Frozen-Time Eigenvalues in the Stability ...

引用

Southeastern Symposium on System Theory

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

In this paper we present some enlightening results to show why and how stability assessment for Linear Time-Varying (LTV) systems based solely on the location of the "frozen-time eigenvalues (FTE)" fails to be sufficient or necessary, using two classes of parametrized periodic LTV systems derived from two examples given by Markus-Yamabe [6] and Wu [11]. Exact domain of stability in the parameter space obtained using analytical or numerical solutions of the Floquet characteristic Exponents are presented, and compared to that predicted by FTEs. The results are useful in the study of robustness and stabilization of Linear Time Invariant (LTI) systems, as will be shown in this paper that an unstable LTI system maybe stabilized or destabilized by periodic structural perturbations (pumping) without any control input.

关键词： Eigenvalues and eigenfunctions Stability analysis Linear systems Stability criteria Upper bound Robust stability Remote sensing image processing Laboratories Robust control

来源：评论

学校读者我要写书评

暂无评论

MORPHOLOGICAL REPRESENTATION OF DISCRETE AND BINARY imageS

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 1991年第6期39卷 1369-1379页

作者： GOUTSIAS, J SCHONFELD, D Department of Electrical and Computer Engineering Image Analysis and Communications Laboratory Johns Hopkins University Baltimore MD USA

We present a general theory for the morphological representation of discrete and binary images. The basis of this theory relies upon the generation of a set of nonoverlapping segments of an image via repeated erosions and set transformations, which in turn produces a decomposition that guarantees exact reconstruction. We introduce a general morphological representation and we study its properties. We also investigate the relationship between the proposed representation and some existing shape analysis tools (e.g., discrete size transform, pattern spectrum, skeletons), thus introducing the representation as the basis of a unified theory for geometrical image analysis. Particular cases of the general representation scheme are shown to yield a number of useful image decompositions which are directly related to various forms of morphological skeletons. We study the relationship between the representation and the various forms of morphological skeletons. As a result of this study we develop a unified theory for the mathematical description of the morphological skeleton decomposition of discrete and binary images.

关键词： Skeleton image reconstruction Discrete transforms Shape Pattern analysis image analysis image representation image sequence analysis image segmentation image coding

来源：评论

学校读者我要写书评

暂无评论

AN ITERATIVE GROWING AND PRUNING ALGORITHM FOR CLASSIFICATION TREE DESIGN

引用

IEEE TRANSACTIONS ON PATTERN analysis AND MACHINE INTELLIGENCE 1991年第2期13卷 163-174页

作者： GELFAND, SB RAVISHANKAR, CS DELP, EJ Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

A critical issue in classification tree design is obtaining right-sized trees, i.e., trees which neither underfit nor overfit the data. Instead of using stopping rules to halt partitioning, we follow the approach of growing a large tree with pure terminal nodes and selectively pruning it back. A new efficient iterative method is proposed to grow and prune classification trees. This method divides the data sample into two subsets and iteratively grows a tree with one subset and prunes it with the other subset, successively interchanging the roles of the two subsets. The convergence and other properties of the algorithm are established. Theoretical and practical considerations suggest that the iterative tree growing and pruning algorithm should perform better and require less computation than other widely used tree growing and pruning algorithms. Numerical results on a waveform recognition problem are presented to support this view.

关键词： CLASSIFICATION TREE ERROR RATE ESTIMATION GRAPH THEORY (TREES) PATTERN RECOGNITION TREE GROWING TREE PRUNING

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：