Face recognition approach based on 2D discrete fractional Fourier transform

The fractional Fourier transform (FRFT) has the mixed time and frequency characteristics of signals. And FRFT is a powerful and effective tool for time-varying and nonstationary signal processing. To address face recognition problem, an approach based on 2D discrete fractional Fourier transform (2D-DFRFT) is proposed in this paper. First of all, the 2D-DFRFT of a facial image is computed. Then Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA) are combined to perform discriminative feature extraction. Then the nearest neighbor (NN) classifier is applied to perform face recognition, based on Euclidean distance. Experimental results on ORL face database indicate that the proposed approach obtains good recognition effects.