Raw vs. Processed: How to Use the Raw and Processed Images for Robust Face Recognition under Varying Illumination

Abstract

Many previous image processing methods discard low-frequency components of images to extract illumination invariant for face recognition. However, this method may cause distortion of processed images and perform poorly under normal lighting. In this paper, a new method is proposed to deal with illumination problem in face recognition. Firstly, we define a score to denote a relative difference of the first and second largest similarities between the query input and the individuals in the gallery classes. Then, according to the score, we choose the appropriate images, raw or processed images, to involve the recognition. The experiment in ORL, CMU-PIE and Extended Yale B face databases shows that our adaptive method give more robust result after combination and perform better than the traditional fusion operators, the sum and the maximum of similarities.