Illuminated face normalization technique by using wavelet fusion and local binary patterns

Performance of a face recognition system has not been satisfied due to the illumination variation on facial image. Thus, there were many works that dealing with illumination compensation in face recognition in the past decades. One of the important techniques is to remove the illumination component based on the Illumination Reflectance model. In this paper, a facial image illumination invariant algorithm is devised based on the fusion of wavelet analysis and local binary pattern. The algorithm first removes the coefficients in logarithm wavelet approximation subband to get rid of illumination component. Next, reflectance component of facial image is then enhanced through the mapping of local binary pattern histogram. Finally, two processed images are combined through wavelet image fusion. Experiment results show that the proposed technique is promising in achieving the illumination invariant for facial images.