Pixel selection in a face image based on discriminant features for face recognition

We propose a pixel selection method in a face image based on discriminant features for face recognition. By analyzing the relationship between the pixels in a face image and features extracted from face images, pixels that contain a large amount of discriminative information are selected, while pixels with less discriminative information are discarded. The proposed method orders the pixels based on the discriminative information in face recognition, instead of selecting salient a priori regions. Comparative experiments are performed using the FERET, CMU-PIE and Yale B databases. The experimental results show that the pixel selection results in improved recognition performance, especially under illumination variation.