A robust recognition system for partially occluded faces
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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This paper describes a nonlinear face recognition method based on polynomial spatial frequency image processing. This nonlinear method is known as the polynomial distance classifier correlation filter (PDCCF). PDCCF is a member of a well-known family of filters called correlation filters. Correlation filters are attractive because of their shift invariance and potential for distortion tolerant pattern recognition. PDCCF addresses more than one filter in the system, each one with a different form of non-linearity. Our experimental results on the Olivetti Research Laboratory (ORL) and Extended Yale B (EYB) face datasets show that PDCCF outperforms the principal component analysis (PCA), and the local binary pattern (LBP).