A Robust Processing Chain for Face Recognition under Varying Illumination

Abstract

Abstract In order to make face recognition more reliable under varying illumination, a robust processing chain is presented in this paper. Most of the illumination normalization methods treat all face images in the same way without considering the specific illumination condition of each probe image. For the nearly well-lit face images, they may be misclassified after illumination normalization. But they can be correctly classified without illumination normalization. To address this problem, the illumination quality index (IQI) of face image is proposed. According to the IQI of a probe face image, it can be detemvned whether the illumination normalization should be applied to it. In the proposed processing chain, the probe face image needing no illumination normalization will directly be used for recognition using normalized correlation. Otherwise a new illumination normalization approach, based on the Retinex theory and the total variation under L2 norm (TVL2) constraint model, is conducted on it. The pro...