Abstract
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 detect accurate positions of some facial feature points and to warp the image for alignment, etc.
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