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parallel ALGORITHMS FOR DETERMINING K-WIDTH CONNECTIVITY IN BINARY imageS

JOURNAL OF parallel AND distributed COMPUTING 1991年第1期12卷 12-23页

作者： DEHNE, F HAMBRUSCH, SE PURDUE UNIV DEPT COMP SCIW LAFAYETTEIN 47907

In this paper we consider a new form of connectivity in binary images, called k -width connectivity. Two pixels a and b of value “1” are in the same k -width component if and only if there exists a path of width k such that a is one of the k start pixels and b is one of the k end pixels of this path. We present characterizations of the k -width components and show how to determine the k -width components of an n × n image in O(n) and O (log 2 n ) time on a mesh of processors and hypercube, respectively, when the image is stored with one pixel per processor. Our methods use a reduction of the k -width-connectivity problem to the 1-width-connectivity problem. A distributed, space-efficient encoding of the k -width components of small size allows us to represent the solution using O (1) registers per processor. Our hypercube algorithm also implies an algorithm for the shuffle-exchange network.

关键词： image processing

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Examining the effects of CU/PE overlap and synchronization overhead when using the complete sums approach to image correlation

Examining the effects of CU/PE overlap and synchronization o...

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International Symposium on parallel and distributed processing (IPDPS)

作者： J.B. Armstrong M.A. Nichols H. Jay Siegel L.H. Jamieson Parallel Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

A mixed-mode parallel machine's processing elements (PEs) are capable of operating in and switching between the SIMD and MIMD modes of parallelism. The paper analyzes various mappings of image correlation algorithms onto a mixed-mode parallel processing system. The trade-offs that exist between the SIMD and MIMD modes explain why some sequences of instructions are performed better in one mode than in the other and are the primary basis employed in comparing different mappings of a parallel algorithm onto a mixed-mode system.< >

关键词： parallel machines parallel processing image analysis parallel algorithms image processing Switches Laboratories Large-scale systems Pixel Smoothing methods

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BDG-torus union graph-an efficient algorithmically specialized parallel interconnect

BDG-torus union graph-an efficient algorithmically specializ...

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International Symposium on parallel and distributed processing (IPDPS)

作者： N. Suri A. Mendelson D.K. Pradhan Department of Electrical and Computer Engineering University of Massachusetts Amherst MA Department of EE Technion-Israel Institute of Technology Israel

The binary de Bruijn graph (BDG) is a realizable alternative to the hypercube. An extension of the BDG by the edge set union with a torus is shown-union-graph (UG). This achieves graph capabilities/versatility comparable to the product shuffle (PS) graph and the hypercube within a fixed degree graph. The UG improves upon both in implementing pipelined and multi-phase algorithms. More importantly, the purpose being to design an algorithmically specialized interconnect, with the algorithmic features of a wide range of algorithms as well as direct architectural support for them, instead of simple providing for a set of graph embeddings in the interconnect. A set of examples demonstrate the UG's versatility in this aspect of algorithmic support.< >

关键词： Hypercubes Tree graphs Algorithm design and analysis Very large scale integration Costs Focusing Concurrent computing Finite element methods image analysis image processing

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A Neural Controller for Mobile Robots

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IFAC Proceedings Volumes 1991年第9期24卷 271-275页

作者： M.B. Zaremba E. Porada Département d’informatique Université du Québec à Hull PQ Canada J8X 3X7

A neural controller for visually guided navigation of a mobile robot in the presence of dynamic obstacles and a vector field of attraction forces is presented. Discrete information, obtained from a raster-type sensor, is subjected to parallel distributed processing aiming at real-time detection of geometrical properties of visual representations of the obstacles. A characteristic feature of the neural architecture adopted here is processing of the input data by a hidden layer of dipole units. This novel approach allows the controller to perform the operations of edge detection and recognition of geometrical features within the controller’s structure rather than using visual data pre-processed by classical convolution-based methods. Dipole processing combined with the ability of our network to learn arbitrary associations very rapidly by self-programming permits the processing of large amounts of input data without compromising the efficiency of the learning phase. The capability of the network to extract and process some geometrical characteristics of the environment works for both local (limited by a field of view window) and global navigation. The behavior of the robot in the vicinity of obstacles can be tuned and modified by changing the number of recursively generated obstacle hulls, the size of the window, and the weights of the force components intervening in the control.

关键词： Neural nets robotics navigation control image processing intelligent machines modeling

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A parallel distributed algorithm for feature extraction and disparity analysis of computer images 2

A parallel distributed algorithm for feature extraction and ...

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2nd IEEE Symposium on parallel and distributed processing, SPDP 1990

作者： Mousavi, M.S. Schalkoff, R.J. AT and T Bell Laboratories MiddletownNJ07748 United States Department of Electrical and Computer Engineering Clemson University ClemsonSC29631 United States

ISBN: (纸本)0818620870

A parallel distributed processing method for extracting features in stereo images is presented. The algorithm is edge-based and employs the epipolar constraint. First edges are detected in a multilayered network using two methods of locating the magnitude of directional first derivatives and the zero-crossing of second derivatives of smoothed images. The combined edge detection process helps to eliminate 'phantom' edges. Then features that are likely to be detectable in both images are selected. These features are edge intervals and edge orientation, that is, the intersection of image edges with the epipolar line and the corresponding slope of the edges at those points. The feature extraction process is implemented in a two-layered parallel distributed processing model. The first layer provides edge interval representations. The second layer computes a similarity of measure for each pair of primitive matches which are then forwarded to the second stage of the algorithm. The purpose of the second stage is to turn the difficult pixel correspondence problem into a constraint satisfaction problem by imposing relational constraints. This constraint satisfaction is then solved using a neural network. The results of computer simulations are presented to demonstrate the effectiveness of the approach. © 1990 IEEE.

关键词： Feature extraction

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parallel algorithms for determining k-width- connectivity in binary images 2

Parallel algorithms for determining k-width- connectivity in...

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2nd IEEE Symposium on parallel and distributed processing, SPDP 1990

作者： Dehnc, Frank Hambrusch, Susanne E. School of Computer Science Carleton University OttawaK1S 5B6 Canada Department of Computer Sciences Purdue University West LafayetteIN47907 United States

ISBN: (纸本)0818620870

In this paper we consider a new form of connectivity in binary images, called k-width-connectivity. Two pixels a and 6 of value are in the same k-width- component if and only if there exists a path of width k such that a is one of the k start pixels and b is one of the k end pixels of this path. We present characterizations of the k-width-components and show how to determine the k-width-components of an n x n image in O(n) and 0(log2 n) time on a mesh of processors and hypercube, respectively, when the image is stored with one pixel per processor. Our methods use a reduction of the k-width-connectivity problem to the 1-width-connectivity problem. A distributed, space-efficient encoding of the k-width-components of small size allows us represent the solution using O(l) registers per processor. Our hypercube algorithm also implies an algorithm for the shuffle-exchange network. © 1990 IEEE.

关键词： Pixels

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A parallel distributed algorithm for feature extraction and disparity analysis of computer images

A parallel distributed algorithm for feature extraction and ...

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International Symposium on parallel and distributed processing (IPDPS)

作者： M.S. Mousavi R.J. Schalkoff AT and T Bell Laboratories Inc. Middletown NJ USA Department of Electrical & Computer Engineering Clemson University Clemson SC USA

关键词： distributed algorithms Feature extraction image analysis Algorithm design and analysis Concurrent computing distributed computing image edge detection Stereo vision Neural networks distributed processing

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parallel algorithms for determining k-width- connectivity in binary images

Parallel algorithms for determining k-width- connectivity in...

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International Symposium on parallel and distributed processing (IPDPS)

作者： F. Dehne S.E. Hambrusch School of Computer Science Carleton University Ottawa Canada Department of Computer Sciences Purdue University West Lafayette IN USA

The authors consider a new form of connectivity in binary images, called k-width-connectivity. Two pixels a and b of value '1' are in the same k-width-component if and only if there exists a path of width k such that a is one of the k start pixels and b is one of the k end pixels of this path. The authors present characterisations of the k-width-components and show how to determine the k-width-components of an n*n image in O(n) and O(log/sup 2/ n) time on a mesh of processors and hypercube, respectively, when the image is stored with one pixel per processor. The methods use a reduction of the k-width-connectivity problem to the 1-width-connectivity problem. A distributed, space-efficient encoding of the k-width-components of small size allows the solution to be represented using O(l) registers per processor. The hypercube algorithm also implies an algorithm for the shuffle-exchange network.< >

关键词： parallel algorithms Pixel Hypercubes Computer science Concurrent computing Encoding Registers Fault tolerance Councils Contracts

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image ALGEBRA TECHNIQUES FOR parallel image-processing

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JOURNAL OF parallel AND distributed COMPUTING 1987年第1期4卷 7-44页

作者： RITTER, GX GADER, PD UNIV FLORIDA DEPT MATHGAINESVILLEFL 32611

An image algebra has been defined which is capable of expressing a wide variety of gray-level image-to-image transformations. The purpose of this paper is fourfold: (1) to introduce the reader to the basic concepts of the image algebra; (2) to show how it suggests a general-purpose cellular pyramid array processor for real time image processing tasks; (3) to demonstrate how the image algebra can be used to formulate the problem of mapping algorithms to specific hardware; and (4) to show how algebraic techniques can be used to develop systematic methods for deriving parallel algorithms.

关键词： image processing

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MAPPING image-processing OPERATIONS ONTO A LINEAR SYSTOLIC MACHINE

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distributed COMPUTING 1986年第4期1卷 246-257页

作者： KUNG, HT WEBB, JA 1. Department of Computer Science Carnegie Mellon University 15213 Pittsburgh PA USA

A high-performance systolic machine, called Warp, is operational at Carnegie Mellon. The machine has a programmable systolic array of linearly connected cells, each capable of performing 10 million floating-point operations per second. Many image processing operations have been programmed on the machine. This programming experience has yielded new insights in the mapping of image processing operations onto a parallel computer. This paper identifies three major mapping methods that are particularly suited to a Warp-like parallel machine using a linear array of processing elements. These mapping methods correspond to partitioning of input dataset, partitioning of output dataset, and partitioning of computation along the time domain (pipelining). parallel implementations of several important image processing operations are presented to illustrate the mapping methods. These operations include the Fast Fourier transform (FFT), connected component labelling, Hough transform image warping and relaxation.

关键词： image processing Systolic arrays parallel processing Connected component labelling Hough transform image warping Relaxation

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