A hierarchical algorithm for fuzzy template matching in emotional facial images
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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In order to improve the speed of matching algorithm and simplify the processing of existing sub-block coding matching, a new template matching method combined local gray value encoding matching and phase correlation is proposed. Matching process is divided into rough matching and fine matching. Rough matching divides the image into certain size blocks called R-block, sums the gray value of each R-block pixel, encodes the R-block according to the gray value distribution of R-block with the adjacent R-block, and matches by step between the template and each search sub-image. Then, fine matching results are obtained using phase correlation according to initial match parameters. The time complexity of the proposed method is .The new algorithm is faster than traditional algorithm by two orders of magnitude, and the speed has improved twice compared with existing sub-block coding method. Experiments demonstrate that the new algorithm is robust to the linear transformation of pixel grey value and image noise, and it also has the stability of small-angle rotation.