Face recognition based on illumination restoration

Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, a novel approach is proposed to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image and an iterative algorithm. The restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that our method can achieve a higher recognition rate based on the Yale B and Yale database. Moreover, our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions, (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes manY images with different illuminations, and (3) it does not need to defect accurate positions of some facial feature points and to warp image for alignment, etc.