Face recognition with the robust feature extracted by the generalized Foley-Sammon transform

Abstract

This paper introduces a novel Gabor Generalized Foley-Sammon Transform (GGFST) method for face recognition (FR). The GGFST method can directly apply the generalized Foley-Sammon transform (GFST) method that has the best separable ability in a global sense to the high-dimensional augmented Gabor feature vectors derived from the Gabor wavelet representation of face images. This method has three novelties: 1) the GGFST method is robust to facial variations; 2) the GGFST method can overcome the limitations of traditional FR approaches by incorporating some middle methods as the preprocessing steps for dimension reduction so as to discard some significant discriminatory information; and 3) the GGFST method has the best separable ability in a global sense. The comparative experiments on the ORL database show that the GGFST method is more effective than the previous methods.