Multi-View Face Database Recognition Using Phase Congruency and SVM Classifier

Abstract

In this paper, we present a face recognition method based on the combination of the LoG-Gabor wavelets (GW) and the phase congruency (PC) method. The phase congruency feature images were obtained by applying phase congruency model to these multi-view face images with log-Gabor wavelets filters over 5 scales and 8 orientations, and then the mean and standard deviation of the image output are computed. The obtained feature vectors are fed up into support vector classifier for classification. Experiments on The UMIST face database that is a multi-view database show that the advantages of our proposed approach. The experiment also shows that, the system is competent for face recognition, the accuracy reach to about 92.8%, and is insensitive to multi-view face.