Template matching via search history driven genetic algorithm

Takumi Nakane; Takuya Akashi; Chao Zhang

doi:10.1117/12.2624210

30 April 2022 Template matching via search history driven genetic algorithm

Takumi Nakane, Takuya Akashi, Chao Zhang

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121770D (2022) https://doi.org/10.1117/12.2624210
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

Pixel-based template matching suffers from computational cost by increasing potential solutions. Genetic algorithms has been adopted to search hopeful solutions, whereas there is a demand for more accurate matching. In this paper, we propose to employ a modified real-coded genetic algorithm to solve the template matching problem. Specifically, individuals sampled during the exploration process are stored in an archive and spatially clustered in the search space. An enhanced crossover (abbreviated as SHX) exploits the extra cluster information to generate new individuals in more promising regions. To solve the matching problem, this algorithm searches for suitable geometric parameters using a pixel-level dense similarity measure. Experimental results show the effectiveness of SHX for solving the template matching problem.

Citation Download Citation

Takumi Nakane, Takuya Akashi, and Chao Zhang "Template matching via search history driven genetic algorithm", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121770D (30 April 2022); https://doi.org/10.1117/12.2624210

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