Illumination normalization for edge-based face recognition using the fusion of RGB normalization and gamma correction

In this paper, an illumination normalization technique for edge-based face recognition on face images with non-uniform illumination conditions, is proposed. The proposed illumination normalization technique fuses the merits of color (Red, Green and Blue) normalization (Nrgb) and gamma correction (GC) for color images. By the fusion of these methods the image becomes independent of the change in face images due to illumination direction. In that way, the presence of false edges in gradient faces is reduced. Experimental results on Georgia Tech Face database with illumination problem shows that the proposed technique improved significantly recognition accuracy in comparison to histogram equalization (HE), logarithm transform (LT) and gamma correction (GC).