An improved Weber-face-based method for face recognition under uncontrolled illumination conditions

The paper presents a new face recognition system robust to illumination variations and moderate occlusion. Two main contributions are discussed. First, we introduce an approach based on contrast equalisation (CE) to improve the traditional Weber-face (WF) technique and make it more robust. Second, we use the local binary patterns (LBP) and local phase quantisation (LPQ) descriptors to make the Weber-face method more resilient to variations in illumination by exploiting both spatial and frequency domains information. By combining the two descriptors, enhanced facial features are obtained showing more discriminating power for variable lighting conditions as well as occlusion. The concept of complementing the WF model with spatial-frequency descriptors is novel and shown to result in a robust system resilient to changing lighting conditions, variations in pose, and occlusion. The method was compared to a number of existing techniques over three public databases. The proposed algorithm outperformed existing techniques under challenging environments.