Wavelet-based illumination normalization for face recognition

The appearance of a face image is severely affected by illumination conditions that hinder the automatic face recognition process. To recognize faces under varying illuminations, we propose a wavelet-based normalization method so as to normalize illuminations. This method enhances the contrast as well as the edges of face images simultaneously, in the frequency domain using the wavelet transform, to facilitate face recognition tasks. It outperforms the conventional illumination normalization method - the histogram equalization that only enhances image pixel gray-level contrast in the spatial domain. With this method, our face recognition system works effectively under a wide range of illumination conditions. The experimental results obtained by testing on the Yale face database B demonstrate the effectiveness of our method with 15.65% improvement, on average, in the face recognition system.