检索结果-内蒙古大学图书馆

IEEE International Conference on Systems, Man and Cybernetics

作者： N. Ansari E.J. Delp Center for Communications and Signal Processing Electrical and Computer Engineering Department New Jersey Institute of Technology Newark NJ USA Computer Vision and Image Processing Laboratory School of Electrical Engineering Purdue University IN USA

A technique to guide landmark matching known as hopping dynamic programming is described. The location of the model in the scene is estimated with a least-squares fit. A heuristic measure is then computed to decide if the model is in the scene. The shape features of an object are the landmarks associated with the object. The landmarks of an object are defined as the points of interest of the object that have important shape attributes. Examples of landmarks are corners, holes, protrusions, and high-curvature points.< >

关键词： Shape measurement Layout computer vision Pattern recognition Signal processing image processing Laboratories Performance evaluation Least squares approximation Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A medical axis transform algorithm for compression and vectorization of document images

A medical axis transform algorithm for compression and vecto...

引用

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

作者： J.W. Brandt A.K. Jain Computer Vision Research Laboratory Department of Electrical Engineering and Computer Science University of California Davis CA USA

It is proposed that the medial axis transformation (MAT), being an invertible transformation, has value in lossless data compression, and, since the MAT conveys the line structure of an image, that it is also useful for vector conversion. To this end, some properties of the MAT are established and then exploited to devise a specialized chain-code representation. This MAT-based chain-code language captures any binary image but is particularly suited to line drawings. An extension of the language that can express chain-code sequences as linear and quadratic line segments under tunable error tolerance is described. The representation has achieved acceptable lossless data compression and significant additional compression for line drawings when vectorization is employed. As the error tolerance is increased, the amount of compression increases together with distortion. Thus, the method can be used to obtain a rate/distortion curve for binary images.< >

关键词： Biomedical imaging image coding image segmentation computer vision Skeleton Rate distortion theory Data compression computer science Vectors image converters

来源：评论

学校读者我要写书评

暂无评论

Object recognition using fast adaptive Hough transform

Object recognition using fast adaptive Hough transform

引用

IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： D.D. Haule A.S. Malowany Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada

A fast adaptive Hough transform (FAHT) approach is developed for detecting shapes which can be characterized by two parameters. This class of shapes includes both linear and circular image features. The method is based on identifying linear and circular segments in images by searching for clusters of evidence in two-dimensional parameter spaces. The FAHT differs from HT in the degree of freedom allowed in the placement and choice of shape of the window which defines the range of parameters under study at each resolution. This method is superior to that of HT implementation in both storage and computational requirements. The ideas of the FAHT are illustrated by tackling the problem of identifying linear segments in images by searching for clusters of evidence in two-dimensional parameter spaces. It is shown that the method is robust to the addition of extraneous noise and can be used to analyze complex images containing more than one shape.< >

关键词： Object recognition Shape image analysis image segmentation Equations computer vision Noise robustness Noise shaping image edge detection Robot vision systems

来源：评论

学校读者我要写书评

暂无评论

High-speed 2-D hardware convolution architecture based on VLSI systolic arrays

High-speed 2-D hardware convolution architecture based on VL...

引用

IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： D.D. Haule A.S. Malowany Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada

The design of a special-purpose systolic image convolution processor for use in a robot vision system is described. It presents a high-speed two-dimensional hardware convolution architecture based on VSLI systolic arrays for image processing applications. An architecture for the parallel processing of the generalized two-dimensional convolution is summarized. A VLSI convolution chip was designed to accommodate various convolution window sizes. The number of coefficients being handled is directly proportional to the number of systolic computing elements (processors) used. In the present design three such processors are configured on one VLSI chip. Signed coefficients and unsigned data of eight bits are supported. All processing and interprocessor communications are performed bit-serially. The chip design incorporates error detection during convolution, and overflow avoidance techniques are possible for maximum system autonomy. The chip is estimated to operate at a maximum frequency of 16 MHz.< >

关键词： Hardware Convolution Very large scale integration computer architecture Frequency estimation Robot vision systems Systolic arrays image processing Parallel processing Process design

来源：评论

学校读者我要写书评

暂无评论

Numerical analysis of visual patterns

Numerical analysis of visual patterns

引用

Multidimensional Signal Processing Workshop

作者： A.C. Bovik N. Gopal T. Emmoth Laboratory for Vision Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

Summary form only given, as follows. Similarities are found between spatial pattern analysis and other low-level cooperative image analysis tasks. Visual pattern analysis proceeds analogously via estimation of emergent 2D image frequencies. Unlike shape-from-X or optical flow paradigms, constraints are derived from the responses of multiple oriented spatial frequency channels rather than directly from the image irradiance measurements. By selecting channel filters that are sufficiently concentrated in both space and frequency, highly accurate spatial frequency estimates are computed on a local basis. Two related methods are proposed. In the first, a constrained estimate of the emergent image frequencies is obtained by resolving the responses of multiple channel filters in a process similar to photometric stereo. The second approach formulates the estimation of frequencies as an extremum problem regularized by a smoothing term. An iterative constraint propagation algorithm is developed analogous to those used in variational/relaxational approaches to shape-from-X (shading, texture) and optical flow. Examples illustrate both approaches using synthetic and natural images.

关键词： Numerical analysis Frequency estimation Optical filters Pattern analysis Optical variables control image motion analysis image texture analysis Frequency measurement Fluid flow measurement Shape measurement

来源：评论

学校读者我要写书评

暂无评论

Mean field theory and MT neurons

Mean field theory and MT neurons

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： A. Dobbins S.W. Zucker Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada Canadian Institute for Advanced Research Montreal QUE Canada

The problem of obtaining reliable estimates of the optic flow field and its variation is discussed. It is argued that circuitry in the middle temporal (MT) visual area is arranged to provide mean field approximations of the optical flow field, that is, the maximal neighborhood over which the local field can be well-approximated as uniform, parallel translation. In addition, the way the mean field approximation varies with neighborhood size and position is informative about the variation of the flow field. It is shown how receptive fields can be synthesized to represent the first-order differential information about the flow field. The same ideas are applicable to the binocular disparity vector field, and lead one to predict the existence of extrastriate neurons that are specialized for the local shear and stretch of the disparity and motion vector fields.< >

关键词： Neurons image motion analysis Circuits computer architecture computer vision Robot vision systems Laboratories Shape Optical devices Retina

来源：评论

学校读者我要写书评

暂无评论

A RULE BASED APPROACH FOR VISUAL-PATTERN INSPECTION

引用

IEEE TRANSACTIONS ON PATTERN analysis AND MACHINE INTELLIGENCE 1988年第1期10卷 56-68页

作者： DARWISH, AM JAIN, AK Computer Vision Research Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

The authors investigate the use of a priori knowledge about a scene to coordinate and control bilevel image segmentation, interpretation, and shape inspection of different objects in the scene. The approach is composed of two main steps. The first step consists of proper segmentation and labeling of individual regions in the image for subsequent ease in interpretation. General as well as scene-specific knowledge is used to improve the segmentation and interpretation processes. Once every region in the image has been identified, the second step proceeds by testing different regions to ensure they meet the design requirements, which are formalized by a set of rules. Morphological techniques are used to extract certain features from the previously processed image for rule verification purposes. As a specific example, results for detecting defects in printed circuit boards are presented.

关键词： computer vision image Interpretation Region Labelling Morphological Techniques Feature Extraction PCB Defect Detection Rule Based Approach Visual Pattern Inspection Bilevel image Segmentation Shape Inspection Scene Specific Knowledge Rule Verification Printed Circuit Boards computer vision computerised Pattern Recognition computerised Picture Processing Inspection Knowledge engineering

来源：评论

学校读者我要写书评

暂无评论

CONTROL POINT TRANSFORMS FOR SHAPE REPRESENTATION AND MEASUREMENT

引用

computer vision GRAPHICS AND image PROCESSING 1988年第1期42卷 87-111页

作者： PAGLIERONI, DW JAIN, AK Computer Vision Research Laboratory Department of Electrical and Computer Engineering University of California Davis California 95616 USA

A new fast transform from curve samples to least-squares normalized B-spline control points is developed and their relation to Fourier descriptors is established. Contour control point sequence scale, translation, and rotation are known to produce identical shape model variations. It is shown that under the conditions of our transform, such sequences are also directly applicable to efficient computation of many useful shape features or characteristics. First, methods for computing boundary curvature and mean contour sample from control points are presented. Then, transforms from contour control points to shape moments and projections are developed and tested.

关键词： MATHEMATICAL TRANSFORMATIONS

来源：评论

学校读者我要写书评

暂无评论

MAXIMUM-LIKELIHOOD image-RESTORATION ADAPTED FOR NONCOHERENT OPTICAL IMAGING

引用

JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND vision 1988年第5期5卷 666-673页

作者： HOLMES, TJ Department of Electrical and Computer Engineering Computer-Vision Laboratory University of Missouri-Columbia Columbia Missouri 65211 USA

Noncoherent optical-imaging systems are identified as potential applications for the maximum-likelihood image-restoration methods that are currently being studied for various modalities of nuclear-medicine imaging. An analogy between the quantum-photon measurements of such an optical system and that of a gamma camera allow for this new application. Results of a computer simulation are presented that support its feasibility. One important property revealed by this simulation is that the maximum-likelihood method demonstrates the ability to extrapolate the Fourier spectrum of a band-limited signal. This ability can be partially understood in that this algorithm, similar to some of the other spectral-extrapolation algorithms, constrains the solution to nonnegative values. This observation has implications on the potential of superresolution, the restoration of images from a defocused optical system, and three-dimensional imaging with a microscope.

关键词： computer simulation Fourier transforms image restoration Optical imaging Optical measurement Three dimensional microscopy

来源：评论

学校读者我要写书评

暂无评论

SIGNAL-PROCESSING CHARACTERISTICS OF DIFFERENTIAL-INTERFERENCE-CONTRAST MICROSCOPY .2. NOISE CONSIDERATIONS IN SIGNAL RECOVERY

引用

APPLIED OPTICS 1988年第7期27卷 1302-1309页

作者： HOLMES, TJ The author is with University of Missouri-Columbia Department of Electrical & Computer Engineering Computer-Vision Laboratory Columbia Missouri 65212.

A mathematical model and computer simulation, presented in a previous publication, of the optics of differential-interference-contrast (DIC) microscopy (DICM) is extended to consider the effects of stochastic noise. images resulting from this simulation indicate that, even in the presence of a significant level of noise, the resolution and detail of objects can be much improved with a proposed image-restoration algorithm. Thus the feasibility of superresolution with DICM in the presence of noise is supported.

关键词： computer simulation image quality image restoration Light intensity Refractive index Signal recovery

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：