Local Relation Map: A Novel Illumination Invariant Face Recognition Approach

Abstract

In this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete Cosine Transform (DCT) are discarded to eliminate the effect caused by noise. Based on the local characteristics of the human face, a simple but effective illumination invariant feature local relation map is proposed. Experimental results on the Yale B, Extended Yale B and CMU PIE demonstrate the outperformance and lower computational burden of the proposed method compared to other existing methods. The results also demonstrate the validity of the proposed face model and the assumption on noise.