Extracting features of components in an image is an important step for recognition of objects in the image. In this paper, we develop a general formula for extracting some geometric features of image components such a...
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Extracting features of components in an image is an important step for recognition of objects in the image. In this paper, we develop a general formula for extracting some geometric features of image components such as area, perimeter, compactness, height, width, diameter, moments, and centroid. We then design a fast algorithm for the general formula on SIMD mesh-connected computers. The algorithm uses a pipelining technique to compute a geometric property of kn components at the same time. It takes O([m/kn]n) time to compute a geometric property of all the components in an n x n image on an n x n SIMD mesh-connected computer with O(k) local space in each processing element, where m is the number of components in the image and k is an integer between 1 and [m/n]. Compared with previous algorithms, it speeds up the feature extraction process by at least k times. (C) 1997 Pattern Recognition Society.
A multipolar methodology is applied to the boundary element method (direct and indirect formulation) in order to solve bidimentional Stokes cavity flow. The algorithm based on mixed multipolar expansion and numerical ...
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A multipolar methodology is applied to the boundary element method (direct and indirect formulation) in order to solve bidimentional Stokes cavity flow. The algorithm based on mixed multipolar expansion and numerical integration is applied not only for very large problems but also for intermediate and small problems. In comparison with the direct formulation, the indirect formulation is more stable with the iterative solvers, and does not need to be preconditioned to obtain a fast convergence. A good result in memory saving and computing time is obtained that enables us to run huge examples which are prohibitive for traditional BEM implementations. (C) 1997 Elsevier Science Ltd.
The distance transform (DT) and the medial axis transform (MAT) are two image computation tools used to extract the information about the shape and the position of the foreground pixels relative to each other. The DT ...
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The distance transform (DT) and the medial axis transform (MAT) are two image computation tools used to extract the information about the shape and the position of the foreground pixels relative to each other. The DT converts a binary image into an image, where each pixel has a value to represent the distance from it to its nearest foreground pixel. The MAT of an image is a set of maximal squares that represents the foreground pixels of an image. Extensively applications of these two transforms are used in the fields of computer vision and image processing, such as expanding shrinking, thinning and computing shape factor etc. There are many different distance transforms based on different distance metrics. The chessboard distance transform (CDT) is one kind of distance transform (DT) which converts an image based on the chessboard distance metrics. In this paper, we first demonstrate that both transforms (i.e. MAT and CDT) are interchangeable. Then the corresponding algorithms are also proposed. That is, the MAT can be found by utilizing a CDT algorithm and vice versa. That is also true in any computation models.
The parallel computation model upon which the proposed algorithms are based is the hyper-bus broadcast network. The hyper-bus broadcast network consists of processors which are connected by global buses only. Based on...
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The parallel computation model upon which the proposed algorithms are based is the hyper-bus broadcast network. The hyper-bus broadcast network consists of processors which are connected by global buses only. Based on such an improved architecture, we first design two O(1) time basic operations for finding the maximum and minimum of N numbers each of size O(log N)-bit and computing the matrix multiplication operation of two Nx N matrices, respectively. Then, based on these two basic operations, three of the most important instances in the algebraic path problem, the connectivity problem, and several related problems are all solved in O(log N) time. These include the all-pair shortest paths, the minimum-weight spanning tree, the transitive closure, the connected component, the biconnected component, the articulation point, and the bridge problems, either in an undirected or a directed graph, respectively.
In this paper, preliminary research results on a new algorithm for finding all the eigenvalues and eigenvectors of a real diagonalizable matrix with real eigenvalues are presented. The basic mathematical theory behind...
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In this paper, preliminary research results on a new algorithm for finding all the eigenvalues and eigenvectors of a real diagonalizable matrix with real eigenvalues are presented. The basic mathematical theory behind this approach is reviewed and is followed by a discussion of the numerical considerations of the actual implementation. The numerical algorithm has been tested on thousands of matrices on both a Gray-2 and an IBM RS/6000 Model 580 workstation. The results of these tests are presented. Finally, issues concerning the parallel implementation of the algorithm are discussed. The algorithm's heavy reliance on matrix-matrix multiplication, coupled with the divide and conquer nature of this algorithm, should yield a highly parallelizable algorithm.
In this paper, a multi-parameter error resolution technique is introduced and applied to the collocation method for Volterra integral equations. By using this technique, an approximation of higher accuracy is obtained...
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In this paper, a multi-parameter error resolution technique is introduced and applied to the collocation method for Volterra integral equations. By using this technique, an approximation of higher accuracy is obtained by using a multi-processor in parallel. Additionally, a correction scheme for approximation of higher accuracy and a global superconvergence result are presented.
The duality relation between shortest paths and potentials in directed graphs and the significance of both of these in the theory of network flows is well known. In this paper, we work out the analogous undirected not...
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The duality relation between shortest paths and potentials in directed graphs and the significance of both of these in the theory of network flows is well known. In this paper, we work out the analogous undirected notions, which neither are contained in nor contain their directed counterpart. They are more related to matching theory than to network flows: the corresponding min-path-max-potential theorem can be considered a weighted generalization of the Gallai-Edmonds structure theorem for matchings. In our earlier work [J. Combin. Theory Ser. B, 49 (1990), pp. 10-39], the corresponding theorems are proved in the special case of +/-1 bipartite weightings, and this special case already contains the main points of the general proof. The goal of the present paper is to extrapolate from this +/-1-weighted bipartite special case the arbitrarily weighted general min-path-max-potential theorem and to show some algorithmic consequences related to planar multiflows, the Chinese postman problem, the weighted and unweighted matching structure, etc. In order to make this paper self-contained, we also include a compact, revised variant of earlier proofs, adapted to the present context. In addition to good characterization theorems and polynomial algorithms, efficient (logarithmic polynomial) parallel algorithms follow for some of these problems.
We propose a new sequential width-independent thinning algorithm for binary images. The algorithm uses a 4-neighbor distance transformation, and is designed to preserve the topological properties and shape of the obje...
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We propose a new sequential width-independent thinning algorithm for binary images. The algorithm uses a 4-neighbor distance transformation, and is designed to preserve the topological properties and shape of the object to be thinned. Comparison of the run time with a standard algorithm is given.
作者:
Hungenahally, SGRIFFITH UNIV
FAC SCI & TECHNOLSIGNAL PROC & INTELLIGENT SYST RES LABBRISBANEQLD 4111AUSTRALIA
Development of efficient algorithms for parallel computer architectures is an on-going research area and in the recent past a great volume of theoretical work has been carried out for the search of suitable algorithms...
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ISBN:
(纸本)0780320182
Development of efficient algorithms for parallel computer architectures is an on-going research area and in the recent past a great volume of theoretical work has been carried out for the search of suitable algorithms in concurrent processing environment. In this paper, the results obtained in the implementation of an Optimal parallel algorithm developed by Deng and Iyengar (1992) in the esoteric area of arithmetic expression parsing is reported. The 'C' code developed and tested on an IBM Compatible Personal Computer in this investigative study, is a simple recursive descent parser and may be used for parallel parsing of arithmetic expressions. The algorithm was developed to suit the SIMD parallel architecture to avoid any communication bottlenecks posed by PVM system, however, design and structure of the code readily permits portability to a parallel computer system.< >
Groundwater transport of contaminants undergoing rate-limited or non-equilibrium sorption onto the solid matrix is often described by the dual-porosity or two-domain model, whereby the rate-limited reaction occurs bet...
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Groundwater transport of contaminants undergoing rate-limited or non-equilibrium sorption onto the solid matrix is often described by the dual-porosity or two-domain model, whereby the rate-limited reaction occurs between a mobile and an immobile region. When the sorption reaction is represented by a first-order kinetic relationship, the equation takes the form of a convection-dispersion partial differential equation with an integral term describing the mass transfer between the two regions. An efficient solution algorithm for this type of problems consists in the transformation of the original equation into the Laplace space and subsequent numerical solution of the resulting steady-state equation in the complex space. The exploitation of the Laplace transform to solve the time dependency restricts the application of the technique to linear advection and dispersion terms, while non-linear reactions can be accommodated in particular cases only. This approach has the advantage that it is easily parallelizable, and is therefore proposed in this paper as an efficient algorithm for the parallelization in time of these types of integrodifferential equations. The parallel efficiency of PFELT has been tested on a Gray T3D parallel computer for three sample problems of size N = 1071, 3721, and 15 275, respectively, where N is the number of nodal mesh points. The speed-ups obtained vary from 1.98, with two processors, to 39.93 with 64 processors, for the most favorable case. This corresponds to a percentage of parallel work greater than 98 per cent, and a parallel efficiency of more than 60 per cent in the best case, showing the good performance achievable with this algorithm. (C) 1997 by John Wiley & Sons, Ltd.
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