High-Speed Image Matching Using Partial Template Consisting of Multiple Rectangular Areas Extracted by Genetic Algorithm

摘要

In normalized correlation matching, a template image is set by manual operation before the matching process. Namely, the contents and the size of a template image are determined by the human sense. This paper proposes a method of performing high-speed normalized correlation matching by extracting multiple partial areas automatically, which is effective in image matching. These extracted multiple partial areas become the new template image. The proposed method extracts multiple partial areas suitable for matching by genetic algorithm. The experimental results show that multiple partial areas including an image pattern that was useful for matching were extracted by the proposed method and that the processing time for image matching was reduced to 50%. The proposed method has higher reliability than conventional methods.