Face Recognition Using Wavelet Transform, Fast Fourier Transform and Discrete Cosine Transform

Abstract

This paper describes two methods for face recognition problem with an image database (D.B). The two methods are based on face-based approach. The first method combines the wavelet transform (WT) and fast Fourier transform (FFT), while the second method, combine the WT and discrete cosine transform (DCT). Using the virtue of WT we extract the most insensitive features to facial expression variations. The first method is proven to be very efficient with face images of different features, illuminations and small occlusion. The second method has proven to be good with the above variations of first method together with face images of different: scales, poses and rotated images (/spl plusmn/20). Two D.Bs are used to perform our work. The Yale D.B and Olivetti D.B. The two introduced methods are compared to two known methods, the template method and the eigenface method on the same D.Bs.