Face Recognition Based on Support Vector Machines
Jiang Lili, Liang Kun, Shuang Ye · 2012
Face recognition is the research focus of machine vision, pattern recognition and other areas. It has broad application prospects. in this paper, we apply wavelet transform to human face image preprocessing in order to reduce the impact of expression change on face recognition. then we follow PCA method, mapping the original face image to Eigen-faces axis which mutually orthogonal to achieve dimensionality reduction of eigen. Finally we use support vector machine classification model to identify the projection vector of human face image in the eigen faces axis. the experiment results on the ORL and Yale face databases show that the method is feasible.