This paper presents an approach to texture segmentation by thresholding based on compactness measures of fuzzy sets to determine thresholds of an ill-defined image. The extension of fuzziness in the texture feature sp...
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This paper presents an approach to texture segmentation by thresholding based on compactness measures of fuzzy sets to determine thresholds of an ill-defined image. The extension of fuzziness in the texture feature space provides more meaningful results than by considering fuzziness in gray scale *** effectiveness of the algorithm is demonstrated by comparison with other traditional nonfuzzy methods or the controversial fuzzy method in gray scale *** addition,the efficiency of our algorithm is further improved by parallel implementation using distributed shared memory workstations.
Many imageprocessing tasks can be computed efficiently in a single program multiple data (SPMD) fashion on massively parallel systems. Although executing SPMD tasks on coarse-grained heterogeneous systems yields a co...
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Many imageprocessing tasks can be computed efficiently in a single program multiple data (SPMD) fashion on massively parallel systems. Although executing SPMD tasks on coarse-grained heterogeneous systems yields a cost-effective solution, heterogeneity introduces more complexity in data partitioning, mapping, and scheduling problems. In this paper, three image data partitioning schemes for parallelimageprocessing in heterogeneous systems are investigated and implemented using the parallel virtual machine message passing library. The partitioning schemes are based on the system characteristics (processing capability) incorporated within the distributed computing primitives (DCP) environment using SpecInt92 benchmark and our DCP-based benchmark. We compare the results with the baseline (Eq-based) scheme that equally partitions images regardless of processing speed. The results from the experiments show that the DCP-based partitioning scheme outperforms the Eq-based and Spec-based schemes.
Diagnostics in medicine is often based on analysis of medical images. Extraction of the shape of objects is one basic step for further image analysis. It consists of two steps: (i) edge detection and (ii) contour reco...
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Diagnostics in medicine is often based on analysis of medical images. Extraction of the shape of objects is one basic step for further image analysis. It consists of two steps: (i) edge detection and (ii) contour recovery based on the detected edge points. Here, the authors focus on the second step. They describe the boundary of an object by trigonometric polynomials and present a fast and robust method for the approximation of the boundary from a given set of nonuniformly distributed noisy edge points. The authors show how the proposed technique can be efficiently generalized to 3-D surface recovery. Examples from 2-D and 3-D echocardiography are given.
Hypermedia systems are very important as platforms in the future multimedia information network services. In order to provide more flexible and sophisticated multimedia presentation, it is desirable to simply and effi...
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Hypermedia systems are very important as platforms in the future multimedia information network services. In order to provide more flexible and sophisticated multimedia presentation, it is desirable to simply and efficiently transmit various media data from the databases distributed over network and present them on the user station depending on scenario so as to semantically integrate into multimedia information objects. In this paper, a new hypermedia system which is based on object-oriented structure to perform two different temporal synchronization methods, "lip synchronization" and "scene synchronization" is introduced. Lip synchronization method performs, fine-grained temporal synchronization between continuous media, such as audio and video. On the other hand in scene synchronization, coarse-grained temporal relation between continuous media and discrete media, such as image, graphics or text is maintained depending on the presentation scenario. Furthermore, several media which are semantically related to each other are unified into a Media Group (MG) to simplify its media treatment. The MGs and their involved processing functions are encapsulated into a Media Object (MO) and easily controlled by message passing procedure. In this paper, implementation of the hypermedia model which performs scene synchronization function between discrete and continuous media in the MOs depending on the presentation scenario, and context switching function between each media presentation is precisely described. Finally "Electric Museum" as a prototype application of hypermedia systems is introduced to evaluate the suggested synchronization mechanism.
We propose efficient load balancing methods for two computational problems namely ray tracing and bottom-up binary tree computing in a distributed environment. In the context of ray tracing, we propose a variant of a ...
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We propose efficient load balancing methods for two computational problems namely ray tracing and bottom-up binary tree computing in a distributed environment. In the context of ray tracing, we propose a variant of a static load balancing technique presented in [15] where the sampling is based on partitioning the object space. Our approach partitions the image instead and uses an efficient scheduling technique for load balancing. Computations carried out on a binary tree arise naturally in imageprocessing and network optimization problems. Many of these problems are solved efficiently in parallel by the popular tree contraction technique [1]. In this paper, we explore the tree-contraction technique in a distributed setting using the grain packing method [9]. Implementations of our algorithms on a cluster of workstations using parallel Virtual Machine (PVM) [6] demonstrate near-perfect load balancing.
We describe a distributed and iterative approach to perform the unitary transformations in the square root information filter implementation of the Kalman filter, providing an alternative to the common QR factorizatio...
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We describe a distributed and iterative approach to perform the unitary transformations in the square root information filter implementation of the Kalman filter, providing an alternative to the common QR factorization-based approaches. The new approach is useful in approximate computation of filtered estimates for temporally evolving random fields defined by local interactions and observations. Using several examples motivated by computer vision applications, we demonstrate that near-optimal estimates can be computed for problems of practical importance using only a small number of iterations, which can be performed in a finely parallel manner over the spatial domain of the random field.
image matching has played a key role in object recognition and localization. One central problem is to find an efficient and effective approach to search for the best matching between two image sets. In contrast to th...
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image matching has played a key role in object recognition and localization. One central problem is to find an efficient and effective approach to search for the best matching between two image sets. In contrast to the conventional matching techniques, the innovation of our method detailed in this paper is to propose a hierarchical Chamfer matching scheme based on the dynamic detection of interesting points. The algorithm extends the traditional methods by introducing interesting points to replace edge points in distance transform for the matching measurement. The search for the best matching is guided by minimizing a given matching criterion in an interesting points pyramid from coarse level to fine level. The pyramid is created through a dynamic thresholding scheme and such a hierarchical structure aims to reduce the computation load. The processing speed is further improved by parallel implementation on a low cost heterogeneous PVM (parallel Virtual Machine) network without specific software and hardware requirements. The experimental results demonstrate that our algorithm is simple to implement and quite insensitive to noise and other disturbances with reliability and efficiency.
Fourier inversion is an efficient method for image reconstruction in a variety of applications, for example, in computed tomography and magnetic resonance imaging. Fourier inversion normally consists of two steps, int...
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Fourier inversion is an efficient method for image reconstruction in a variety of applications, for example, in computed tomography and magnetic resonance imaging. Fourier inversion normally consists of two steps, interpolation of data onto a rectilinear grid, if necessary, and inverse Fourier transformation, This paper presents interpolation by the scan-line method, in which the interpolation algorithm is implemented in a form consisting only of row operations and data transposes, The two-dimensional inverse Fourier transformation can also be implemented with only row operations and data transposes, Accordingly, Fourier inversion can easily be implemented on a parallel computer that supports row operations and data transposes on row distributed data The conditions under which the scan-line implementations are algorithmically equivalent to the original serial computer implementation are described and methods for improving accuracy outside of those conditions are presented, The scan-line algorithm is implemented on the iWarp parallel computer using the Adapt language for parallelimageprocessing. This implementation is applied to magnetic resonance data acquired along radial-lines and spiral trajectories through Fourier transform space.
The principles of scalable computing have been used in an investigation of the application of high speed data networks and remote computer resources in providing visualization tools for research and development activi...
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This paper presents a parallel approach to a hierarchical image matching scheme using the Hausdorff distance for object recognition and localization in aerial images. Unlike the conventional matching methods in which ...
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This paper presents a parallel approach to a hierarchical image matching scheme using the Hausdorff distance for object recognition and localization in aerial images. Unlike the conventional matching methods in which edge pixels are considered as image feature pixels in distance transform and the blind pointwise comparison procedure in terms of the Hausdorff distance is applied, a guided image matching system is developed by the hierarchical detection of interesting points via a dynamic thresholding scheme for the search of the best matching between two image sets. Furthermore, the concept of remote procedure call (RPC) in distributed systems is introduced for the parallel implementation to achieve the speedup without specific software and hardware requirement.
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