Illumination-robust face recognition using retina modeling

International audienceIllumination variations that occur on face images degrade the performances of face recognition systems. In this paper, we propose a novel method of illumination normalization based on retina modeling by combining two adaptive nonlinear functions and a Difference of Gaussians filter. The proposed algorithm is evaluated on the Yale B database, the Feret illumination database by using two face recognition methods: PCA and Local Binary Pattern (LBP). Experimental results show that the proposed method achieves very high recognition rates even for the most challenging illumination conditions. Our algorithm has also a low computational complexit