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Image Matching Using a Bat Algorithm with Mutation
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AI
DOI：10.4028/www.scientific.net/amm.203.88.png)
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Abstract
En 中文
Due to shortcoming of traditional image matching for computing the fitness for every pixel in the searching space, a new bat algorithm with mutation (BAM) is proposed to solve image matching problem, and a modification is applied to mutate between bats during the process of the new solutions updating. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for this improved meta-heuristic approach BAM is also presented. To prove the performance of this proposed meta-heuristic method, BAM is compared with BA and other population-based optimization methods, DE and SGA. The experiment shows that the proposed approach is more effective and feasible in image matching than the other model.
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