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| Image Registration for Recovering Affine Transformation Using Nelder Mead Simplex Method for Optimization
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Full
text: |
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Download
Complete Issue PDF(3.43MB) |
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Volume: 3 Issue: 5 |
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Pages: 184-251 |
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Publication
Date: November 2009 |
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ISSN
(Online): 1985-2304 |
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Pages |
218 - 228 |
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Author(s) |
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Published
Date |
30-11-2009 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
Colleague |
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KEYWORDS: Vector Quantization, Multi-core, Shared Memory, Clustering |
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| This paper proposes a parallel approach for the Vector Quantization (VQ) problem in image processing. VQ deals with codebook generation from the input training data set and replacement of any arbitrary data with the nearest codevector. Most of the efforts in VQ have been directed towards designing parallel search algorithms for the codebook, and little has hitherto been done in evolving a parallelized procedure to obtain an optimum codebook. This parallel algorithm addresses the problem of designing an optimum codebook using the traditional LBG type of vector quantization algorithm for shared memory systems and for the efficient usage of parallel processors. Using the codebook formed from a training set, any arbitrary input data is replaced with the nearest codevector from the codebook. The effectiveness of the proposed algorithm is indicated. |
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| Mehfuza Suleman Holia : Colleagues
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| V.K.Thakar : Colleagues
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