Illumination Robust Face Recognition Using Spatial Expansion Local Histogram Equalization and Locally Linear Regression Classification
Pei-Chun Chang, Yong‐Sheng Chen, Chang-Hsing Lee, Cheng‐Chang Lien, Chin‐Chuan Han · 2018 3rd International Conference on Computer and Communication Systems (ICCCS) · 2018
Robust face recognition under illumination variations is a critical problem in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial expansion local histogram equalization (SELHE), is proposed to enhance face images due to illumination variations. First, a face image is divided into several non-overlapped blocks. Then, local histogram equalization with spatial expansion is proposed to enhance the contrast of each local image block. Local linear regression classification will then be used to recognize the enhanced image blocks. Experiments performed on the Yale B and Yale B extended databases have shown that the proposed approach yields promising recognition accuracy.