A Novel Approach For Face Recognition Using Fusion Of Local Gabor Patterns

For face recognition, Gabor features are effectively used. But, only a few approaches used Gabor phase features and they are performing worse than the Gabor magnitude features. To determine the potential of Gabor phase and its fusion with magnitude for face recognition, in this paper, we have proposed local Gabor XOR pattern (LGXP) operator, which encode Gabor phase. Then we introduce block-based Fisher’s linear discriminant (BFLD) for reduce dimensionality of proposed operator and at same time discriminative power also get enhanced. At last, by using BFLD we fuse Gabor phase and Gabor magnitude for face recognition. We evaluate our method for FERET database. Also, we perform comparative experimental studies of different local patterns.