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Multiple Ant Colony Optimizations for Stereo Matching
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International Journal of Image Processing (IJIP)
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Volume:  3    Issue:  5
Pages:  184-251
Publication Date:   November 2009
ISSN (Online): 1985-2304
Pages 
203 - 217
Author(s)  
Wangxiaonian - China
Ajay Somkuwar - India
 
Published Date   
30-11-2009 
Publisher 
CSC Journals, Kuala Lumpur, Malaysia
ADDITIONAL INFORMATION
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
 
KEYWORDS:   Mammography, medical image processing, Adaptive Resonance theory, image enhancement 
 
 
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The stereo matching problem, which obtains the correspondence between right and left images, can be cast as a search problem. The matching of all candidates in the same line forms a 2D optimization task and the two dimensional (2D) optimization is a NP-hard problem. There are two characteristics in stereo matching. Firstly, the local optimization process along each scan-line can be done concurrently; secondly, there are some relationship among adjacent scan-lines can be explored to promote the matching correctness. Although there are many methods, such as GCPs, GGCPs are proposed, but these so called GCPs maybe not be ground. The relationship among adjacent scan-lines is posteriori, that is to say the relationship can only be discovered after every optimization is finished. The Multiple Ant Colony Optimization(MACO) is efficient to solve large scale problem. It is a proper way to settle down the stereo matching task with constructed MACO, in which the master layer values the sub-solutions and propagate the reliability after every local optimization is finished. Besides, whether the ordering and uniqueness constraints should be considered during the optimization is discussed, and the proposed algorithm is proved to guarantee its convergence to find the optimal matched pairs.  
 
 
 
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Wangxiaonian : Colleagues
Ajay Somkuwar : Colleagues  
 
 
 
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