An Illumination Invariant Face Recognition Scheme to Combining Normalized Structural Descriptor with Single Scale Retinex

摘要

Illumination variation is still a challenging issue to address in face recognition. Retinex scheme is effective to face images under small illumination variation, but its performance drop when illumination variation is large. We further analyze the normalized images under large illumination variation and we find that the illumination variation has not been removed thoroughly in these images. Structural similarity is one of image similarity metrics similar to human perception. From SSIM, we extract the structure related component and name it as Normalized Structure Descriptor. It is clear that NSD is robust to illumination variation. We propose a scheme to combining Normalized Structural Descriptor with Single Scale Retinex. In our scheme NSD is extracted from the normalized image from SSR. And the face recognition is performed by the similarity of NSD. The experimental results on the Yale Face Database B and Extended Yale Face Database B show that our approach has performance comparable to state-of-the-art approaches.