| Summary: | 碩士 === 國立交通大學 === 電控工程研究所 === 100 === Pattern recognition is an important issue in the field of computer vision. The difficulty of pattern recognition is how to integrate the image features and compute the image similarities so that the objective can be successfully identified. Template matching is a technique to compute the image similarities. Base on the difference of matching methods, template matching can be divided into two categories: rigid template matching and deformable model matching. Rigid template matching is faster, but its accuracy rate is lower than that of deformable model matching. We present a two-stage template matching algorithm which possesses the advantages of these two approaches. First, we use the rigid template matching to find out the candidate images which are likely to be similar to the objective, and then compute the similarities between candidate images and the objective using deformable model matching. After sorting the result, we achieve the purpose of pattern recognition. In this paper, we experiment on three different pattern recognition problems: handwritten digit recognition, face recognition of a graduation photo, and character recognition of a traditional Chinese painting, and we calculate the accuracy rate. The experimental result shows that the algorithm can successfully reduce the amount of computation task required in deformable model matching, and has a better accuracy rate compared to rigid template matching.
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