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Hierarchical clustering on SIMD machines with alignment network

Hierarchical clustering on SIMD machines with alignment netw...

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Li, Xiaobo Univ of Alberta Edmonton Alberta Can

ISBN: (纸本)081861952x

Several parallel algorithms and parallel architectures have been developed for partitional clustering. Hierarchical clustering algorithms are also widely used in exploratory pattern analysis and unsupervised learning. The author proposes parallel algorithms on single-instruction/multiple-data (SIMD) machines for hierarchical clustering, which require intensive computation and large memory storage. The machine model includes a parallel memory system and an alignment network, to facilitate parallel access of both pattern matrix and proximity matrix. Since clustering algorithms tend to generate clusters even when applied to random datal clustering-tendency and cluster-validity studies are usually performed. The author proposes a parallel algorithm to compute one type of cluster validity measure global fit of hierarchy for quantitative data. For a problem with N patterns, considering validity study as well as clustering, the number of memory accesses is reduced from O(3) on a sequential machine to O(N2) on an SIMD machine with N processing elements (PEs). More general algorithms for different numbers of PEs are also given.

关键词： image processing

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Automatic thresholding algorithm based on an illumination-independent contrast measure

Automatic thresholding algorithm based on an illumination-in...

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Shio, Akio NTT Corp Yokosuka Jpn

ISBN: (纸本)081861952x

An automatic and dynamic thresholding based on an illumination-independent contrast measure is proposed. In this algorithm, a local threshold is calculated for each segmented square region in an image. Since the thresholds obtained in regions that include no characters or objects would produce only noise by thresholding, they are modified by regionwise interpolation based on the contrast measure. The contrast measure is introduced by an illumination reflectance image formation model proposed by T. G. Stockham where the gray-level function is expressed as the product of an illumination component and a reflectance component. The contrast measure is expressed by the ratio of the standard derivation to the mean of the object reflectance. It is found that, if the illumination function is smooth, the ratio can be calculated from just an image function and the characteristics of the video camera are without knowing about the shape of the illumination function. The characteristics are determined for two types of video cameras. The experimental results using 100 outdoor scene images for each camera show that (1) almost all the characters included in the images successfully binarized with the same parameters by this method;(2) this algorithm is independent of character or object size and its gray-level values;(3) the contrast measure is approximately independent of illumination;and (4) this method is applicable to real-world scene images.

关键词： image processing

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Representation and transformation of uncertainty in an evidence theory framework

Representation and transformation of uncertainty in an evide...

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Betz, John W. Prince, Jerry L. Bello, Martin G. Anal Sci Corp Reading MA USA

ISBN: (纸本)081861952x

Interpreting uncertain information, a fundamental requirement of many computer-vision and pattern recognition systems is commonly supported by models of the uncertainty. Evidence theory, also called Dempster-Shafer theory, is particularly useful for representing and combining uncertain information when a single precise uncertainty model is unavailable. A framework is presented for deriving and transforming evidence-theoretic belief representations of uncertain variables that denote numerical quantities. Belief is derived from probabilistic models using relationships between probability bounds and the support and plausibility functions used in evidence theory. This model-based approach to belief representation is illustrated by an algorithm currently used in a vision system to label anomalous high-intensity pixels in imagery. As the uncertain variables are manipulated to form features and object discriminants, the belief representation of the uncertain variables must be transformed accordingly. Belief transformations, analogous to the transformation of probability-density functions in mappings of random variables, are derived to maintain the same rigorous belief representation for computed quantities. The results demonstrate novel ways to address uncertainty in the use of sensor information, and contribute to understanding of the similarities and distinctions of probability theory and evidence theory.

关键词： image processing

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Adaptive, CMOS neural array for pattern association

Adaptive, CMOS neural array for pattern association

引用

Eighth Annual International Phoenix conference on computers and Communications - 1989 conference proceedings

作者： Walker, M. Hassler, P. Akers, L.A. Arizona State Univ Tempe AZ USA

The authors report on the design, simulation and training of a CMOS synthetic neural array for pattern association. The circuit architecture is functionally equivalent to theoretical neural network models, but limited interconnection between layers is used to reduce interconnection densities to VLSI-implementable levels. Simulations of the limited-interconnect architecture demonstrate its ability to replicate a small set of desired neuromorphic behaviors. An analog cell and chip architecture for a 512-element, feedforward neural IC are described. Schematics are presented which illustrate fundamental design considerations.

关键词： pattern recognition

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Representing and comparing shapes using shape polynomials

Representing and comparing shapes using shape polynomials

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Taubin, Gabriel Bolle, Ruud M. Cooper, David B. Brown Univ Providence RI USA

ISBN: (纸本)081861952x

The problem of multiresolution 2-D and 3-D shape representation is addressed. Shape is defined as a probability measure with compact support. Both object representations, typically sets of curves and/or surface patches, and observations, sets of scattered data, can be represented in this way. Global properties of shapes are defined as expectations (statistical averages) of certain functions. In particular, the moments of the shapes are global properties. To any shape S and every integer d > 0 is associated a shape polynomial of degree 2d, whose coefficients are functions of the moments of S. These polynomials are related to the shape S in an affine-invariant way. They yield small values near S and large values far away, and their level sets approximate S. The shape polynomials define two distances between shapes. As asymmetric measures how well one shape fits as a subset of another one;a symmetric version indicates how equal two shapes are. The evaluation of these distance measures is determined by a sequence of computationally very fast matrix operations. The distance measures are used for recognition and positioning of objects in occluded environments.

关键词： image processing

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Application of robust sequential edge detection and linking to boundaries of low contrast lesions in medical images

Application of robust sequential edge detection and linking ...

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Liu, Linnan Bland, Peyton H. Williams, David M. Schunck, Brian G. Meyer, Charles R. Univ of Michigan Ann Arbor MI USA

ISBN: (纸本)081861952x

An algorithm for the optimal edge contour estimation in medical images without a priori shape models is described. The proposed method is an intermediate-level approach compared with the usual low-level edge-detection operators. An optimal and robust contour estimator is derived by the minimization of a risk function which measures the error from both inappropriate choice of edge contour and the inappropriate choice of the noise model in the image. The result includes Huber's function. If a parametric statistical noise model and the Neyman-Pearson criterion are used, the result is an extension of maximum-likelihood function. A recursive formulation can be implemented by assuming an independent random field and a Markov path model. The assumption of independent statistics can be satisfied by use of an autoregressive moving-average preprocessor. The problem of varying edge strength is lessened using an adaptive trimmed mean. The robust algorithm is implemented using a priority-tree (stack) structure. The system's performance is illustrated by estimation of lesion boundaries in medical images.

关键词： image processing

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3D object recognition via simulated particles diffusion

3D object recognition via simulated particles diffusion

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Yacoob, Yaser Gold, Yaron I. Univ of Maryland College Park MD USA

ISBN: (纸本)081861952x

A novel approach for 3-D object recognition is presented. This approach is model-based, and assumes either 3-D or 2 1/2-D scene acquisition. Transformation detection is accomplished along with an object identification (six degrees of freedom, three rotational and three translational, are assumed). The diffusion-like simulation recently introduced as a means for characterization of shape is used in the extraction of point features. The point features represent regions on the object's surface that are extreme in curvature (i.e., concavities and convexities). Object matching is carried out by examining the correspondence between the object's set of point features and the model's set of point features, using an alignment strategy. Triangles are constructed between all possible triples of object's point features, and then are aligned to candidate corresponding triangles of the model's point features. 2 1/2 range images are transformed into a volumetric representation through a parallel projection onto the 3-D space. The resultant volume is suitable for processing by the diffusion-like simulation.

关键词： pattern recognition

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APPLYING AND VALIDATING NEURAL NETWORK TECHNOLOGY FOR NONDESTRUCTIVE EVALUATION OF MATERIALS

APPLYING AND VALIDATING NEURAL NETWORK TECHNOLOGY FOR NONDES...

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1989 ieee INTERNATIONAL conf ON SYSTEMS, MAN, AND CYBERNETICS : DECISION-MAKING IN LARGE-SCALE SYSTEMS

作者： CHEN, CH Southeastern Massachusetts Univ Electr & Comput Eng Dep North Dartmouth MA USA

The application of neural network technology to nondestructive evaluation (NDE) of materials is considered. Based on a limited ultrasonic NDE study using neural networks, it is demonstrated that the neural network technology is feasible for classifying well-defined defects in NDE. In other NDE problems in which image data can be used, neural networks also are likely to perform very well. At this stage of development, however, the conventional pattern recognition techniques cannot be completely replaced by the neural network technology.

关键词： Nondestructive examination

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Estimation of motion parameters for a deformable object from range data

Estimation of motion parameters for a deformable object from...

引用

proceedings CVPR '89: ieee computer society conference on computer Vision and pattern recognition

作者： Chaudhuri, Subhasis Chatterjee, Shankar Univ of California San Diego CA USA

ISBN: (纸本)081861952x

The authors study the estimation of generalized motion parameters for a deformable object from the range data. If the correspondence between two sets of points representing the coordinates of different points of an object undergoing rotational motion and deformation is known, the parameters can be estimated using different least-squares estimators. The total-least-squares (TLS) method is very appropriate when the observation and the data matrices are both perturbed by random noise. For Gaussian-distributed noise, the TLS solution is equivalent to maximum-likelihood estimation. The mean-square error in TLS is always smaller than in an ordinary least-squares (LS) estimator. The scope is analyzed of TLS in estimating the generalized motion parameters, as is the feasibility of decomposing the generalized motion parameters in terms of rotation and deformation parameters. The performance of TLS is compared to that of the LS estimator. It is found that the performance of the LS and TLS methods at low noise levels is almost identical. The accuracy of estimation of direction cosines of the rotation axis and the angle of rotation is not very dependent on whether LS or TLS method is used. However, as the noise level increases in the data matrix, TLS is more accurate in estimating the deformation parameters.

关键词： image processing

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Distortion invariant object recognition by matching hierarchically labeled graphs

Distortion invariant object recognition by matching hierarch...

引用

IJCNN International Joint conference on Neural Networks

作者： Buhmann, J. Lange, J. von der Malsburg, C. Univ of Southern California Comput Sci Dep Los Angeles CA USA

A graph-matching process of object recognition is proposed. It is applied to face recognition. Gray-level images are represented by a resolution hierarchy of local Gabor components, which are all scaled and rotated versions of each other. The components centered on one image point form a Gabor jet. A single jet provides a distortion-insensitive local representation of part of an image. Object recognition is achieved by matching jets corresponding to a preselected set of image points to jets in stored prototype patterns. For a selected image jet the best match in each stored image is determined, under a constraint preserving the spatial arrangement of all jets. The procedure amounts to labeled graph matching, with Gabor jets forming labels to nodes and topology determining links. A contrast-insensitive similarity measure between image jets and stored jets provides for invariance with respect to lighting conditions. The authors have formulated the matching procedure as an optimization task solved by diffusion of match points. This diffusion is controlled by a potential determined by jet similarity and the topology-preserving constraint. The algorithm is a simple implementation of the dynamical link architecture for neural networks.

关键词： pattern recognition

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