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Multiple Ant Colony Optimizations for Stereo Matching
Wangxiaonian, Ajay Somkuwar
Pages - 203 - 217     |    Revised - 30-10-2009     |    Published - 30-11-2009
Volume - 3   Issue - 5    |    Publication Date - November 2009  Table of Contents
Mammography, medical image processing, Adaptive Resonance theory, image enhancement
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.
CITED BY (2)  
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Associate Professor Wangxiaonian
- China
Dr. Ajay Somkuwar
Maulana Azad National Insititute of Technology - India

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