| Summary: | 碩士 === 國立成功大學 === 電機工程學系碩博士班 === 96 === Study of human face recognition system has grown vigorously for last decades. The biometrics of human face is an important feature in the identity authentication. The traditional principal component analysis (PCA), Eigenface, and linear decision algorithm (LDA) operate directly on a whole pattern represented as a vector and acquire a set of projection vectors to extract global features from given training patterns. The computation loads in these methods are heavy. In this thesis, a novel fusion algorithm of the wavelet transform, Sobel operator and orthogonal projection is proposed for human face recognition, where the Haar wavelet transform is utilized to reduce the dimension of images, the Sobel operator is adopted to extract facial features, and the orthogonal projection is presented to perform feature transformation and face recognition. The Olivetti Research Lab (ORL) face database is adopted to demonstrate the feasibility and effectiveness of the proposed face recognition system.
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