| Summary: | 碩士 === 元智大學 === 電機工程研究所 === 88 === For a 3D image, there are different views with various angles. In this thesis, we present a design of minimum average correlation energy （MACE） filter function to recognize a target with 3D rotational views. Our research is emphasizing on optimum discriminant capability.
First, we propose a method that uses nonzero order joint transform correlation (NOJTC) along with Lagrange multipliers technique for image recognition. The NOJTC has a powerful capability to achieve shift-invariance and a potential for distortion-tolerant image recognition. It has been shown that relative high correlation peak can be observed. Then, we extend this concept to design JTCs to perform 3D rotational-invariance. From numerical results, we can see that discriminant performance. Finally, we add noise and background to see the results of recognition.
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