Illumination-insensitive features for face recognition

Yong Cheng, Liangbao Jiao, Xuehong Cao, Zuoyong Li

Abstract: Illumination variation is one of the most challenging problems for robust face recognition. In this paper, after investigating the ratio relationship between two neighboring pixels in a digital image, we proposed two illumination-insensitive features, i.e., the non-directional local reflectance normalization (NDLRN) and the fused multi-directional local reflectance normalization (fMDLRN), which not only effectively reduce illumination difference among facial images under different illumination conditions, but also preserve the facial details. Experimental results show that NDLRN and fMDLRN can significantly alleviate the adverse effect of complex illumination on face recognition.