In most instances the boundaries between textured regions are defined by the gray level contrasts which result from the local interaction between the texture elements in each region. In such cases, the boundaries can ...
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ISBN:
(纸本)0819409391
In most instances the boundaries between textured regions are defined by the gray level contrasts which result from the local interaction between the texture elements in each region. In such cases, the boundaries can be accurately characterized by gray level edge segments. Using these edge segments to localize the texture boundary directly addresses the major problem associated with texture segmentation, namely the localization verses classification accuracy conflict. The accuracy of segmentation methods which rely only on spatially distributed properties to characterize the texture, is limited to the spacial extent of the property used. In contrast, gray level edges are significantly more localized. However, before they can be of any use, the gray level edge segments defining the texture boundary must be isolated from the edges defining the texture elements. In this paper, we define a set of properties to do this. We also incorporate these properties into a paralleldistributed algorithm which is used to segment a set of sample texture images.
Maximum-intensity projection (MIP) algorithms are currently used for construction of magnetic resonance (MR) angiograms. In this application, projections calculated at different angles through the image are used to fo...
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ISBN:
(纸本)0819408042
Maximum-intensity projection (MIP) algorithms are currently used for construction of magnetic resonance (MR) angiograms. In this application, projections calculated at different angles through the image are used to form a cine loop, thus providing a three- dimensional representation from which vascular structure may be deciphered. MIP algorithms cast parallel rays through the MR image volume which has been acquired such that the flow within the vasculature has the highest intensities. The maximum voxel intensity along each ray is placed on the projection plane where the ray meets the plane. Thus, the flow within the vasculature shows up in the projection plane. This research strivesto discover methods of reducing the projection calculation time, thus making the technology more accessible to users of less powerful systems. A novel approach was developed for calculating projections in which each image slice was pre-sorted into bins of intensities. By thresholding the intensities used, the background pixels can be ignored and only those intensities that relate to flow are used in the projection. Thresholding reduces the total number of pixels considered for the projection plane, thereby saving calculation time. Additional time savings resulted from precalculating projection `templates' and filling multiple projection planes at the same time. The algorithms were written in C on a 80386- based system. The new algorithm demonstrated more than a seven-fold increase in projection calculation speed over a benchmark algorithm.
Introduces a system (PAFE) which provides a flexible framework for feature extraction. This system is constructed based on the multi agents model, in which many agents work co-operatively and concurrently. The objecti...
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Introduces a system (PAFE) which provides a flexible framework for feature extraction. This system is constructed based on the multi agents model, in which many agents work co-operatively and concurrently. The objective of this system is to achieve flexible control and coarse-grained parallelism of feature extraction by organizing feature extraction as parallel graph search.< >
The authors present a parallel storage scheme to distribute the elements of an N*N matrix over N memory banks, where N is any (odd or even) power of two, such that any rows, columns, forward and backward diagonals, an...
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The authors present a parallel storage scheme to distribute the elements of an N*N matrix over N memory banks, where N is any (odd or even) power of two, such that any rows, columns, forward and backward diagonals, and square or rectangular blocks can be accessed simultaneously without memory conflict. They present a simple scheme for address generation, which requires only logic operations and can be completed in constant time. They present two network implementation methods for data alignments for this storage scheme. Different from previously proposed routing algorithms, the algorithms for hypercube routing in this paper are free from network conflict. They do not require buffering and time length of a 'step' is shorter, therefore they are more efficient in terms of both hardware cost and speed. The authors also present a simple MIN implementation scheme for the realization of the data alignments. Schemes for processing smaller matrices efficiently on larger scale systems are also developed.< >
Several methods for parallel affine image warping on a linear processor array are considered. The methods were implemented on the Carnegie Mellon Warp machine and the Carnegie Mellon-Intel Corporation iWarp computer (...
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Several methods for parallel affine image warping on a linear processor array are considered. The methods were implemented on the Carnegie Mellon Warp machine and the Carnegie Mellon-Intel Corporation iWarp computer (treated as a linear array), and performance figures are provided. Both systolic methods, which feed one of the images in a stream, and non-systolic methods, which partition both images, are treated. A scanline method that combines some of the features of both, but which requires a fast transposed method is also described. The authors articulate three characteristics that affect the design of parallelimage warping algorithms: affine warping is easily invertible, the mapping is known at the start of execution, and nearby input pixels map to nearby output pixels. The authors conclude that non-systolic methods give slightly better execution time and are easier to programs than systolic methods but require much larger processor memories.< >
The authors discuss two classes of unsupervised feature extraction methods. They show that a system based on second order moments can learn the Karhunen-Loeve expansion in parallel. Then they show that systems based o...
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The authors discuss two classes of unsupervised feature extraction methods. They show that a system based on second order moments can learn the Karhunen-Loeve expansion in parallel. Then they show that systems based on second order moments only have important drawbacks. The second class of systems described avoids this problem by using fourth order moments. Since these systems are much harder to analyze the authors demonstrate some of their advantages with the help of some experiments.< >
This paper presents a system for dynamic intelligent scheduling and control of reconfigurable parallel processors. The purpose of the system is to provide a rapid prototyping capability for computer vision/image proce...
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This paper presents a system for dynamic intelligent scheduling and control of reconfigurable parallel processors. The purpose of the system is to provide a rapid prototyping capability for computer vision/imageprocessing tasks. The scheduler particularly addresses the problems of algorithms with execution times that depend on the image data and processing scenarios that vary dynamically based on the input image. Since conventional scheduling methods cannot produce schedules for most tasks of this type, a dynamic controller is used to schedule the task and reconfigure the machine “on the fly.” This dynamic scheduling system attempts to balance the overall processing scenario with the needs of the individual routines that make up the task. This paper discusses the implementation of the DISC ( D ynamic I ntelligent S cheduling and C ontrol) system. Emphasis is on the scheduling heuristics as they apply to a reconfigurable parallel processor, the information in the system database, and the use of the system for prototyping computer vision/imageprocessing tasks on a partitionable parallel system.
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 s...
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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.
Some concepts for the parallelization on distributed memory computers of a large finite element package for the numerical simulation of coupled problems are discussed in this paper. Two different approaches, based on ...
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Some concepts for the parallelization on distributed memory computers of a large finite element package for the numerical simulation of coupled problems are discussed in this paper. Two different approaches, based on physical and spatial decomposition of the coupled problem, are considered. The parallel algorithms were implemented on an iPSC/2 Hypercube, and results for a test problem and an industrial application are discussed. Moreover, a concept for a block-level domain decomposer is presented that guarantees good load balancing and allows the use of individual meshes for each part of the coupled problem. Adaptive modifications of either mesh in the course of the computation can also be included in this concept without significant reduction of efficiency.
In recent years neural networks have been used to solve some of the difficult real time character recognition problems. These SIMD implementations of the networks have achieve some success, but the real potential of n...
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ISBN:
(纸本)0819405515
In recent years neural networks have been used to solve some of the difficult real time character recognition problems. These SIMD implementations of the networks have achieve some success, but the real potential of neural networks are yet to be utilized. Several well known neural network architectures have been, modified, and implemented. These architecture are then applied to character recognition. The performance of these parallel character recognition systems are compared and contrasted. Feature localization and noise reduction are achieved using least squares optimized Gabor filtering. The filtered images are then presented to an FAUST based learning algorithm which produces the self- organizing sets of neural network generated features used for character recognition. Implementation of these algorithms on highly parallel computer with 1024 processors allows high speed character recognition to be achieved at a speed of 2.3 ms/image, with greater than 99% accuracy on machine print and 89% accuracy on unconstrained hand printed characters. These results are achieved using identical parallel processor programs demonstrating that the method is truly font independent. The back propagation is included to allow comparison with more conventional neural network character recognition methods. The network has one hidden layer with multiple concurrent feedback from the output layer to the hidden and from hidden layer to the input layer. This concurrent feedback and weight adjustment is only possible on a SIMD computer.
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