Illumination-Robust Face Recognition Approach Using Enhanced Preprocessing and Feature Extraction

Abstract

This paper presents an enhanced facial preprocessing and feature extraction technique for an illuminationrobust face recognition system. Overall, the proposed face recognition system consists of a novel preprocessing descriptor, an illumination-robust feature descriptor, and a fusion module as sequential steps. In particular, the proposed system introduces an enhanced center-symmetric local binary pattern as preprocessing descriptor and a differential two-dimensional principal component analysis as feature descriptor to achieve performance improvement. To verify the proposed system, performance evaluation was carried out using various binary pattern descriptors and recognition algorithms on the extended Yale B database. As a result, the proposed system showed the best recognition accuracy of 99.03% compared to other approaches, and we confirmed that the proposed approach is effective for practical face recognition systems. © Copyright 2016 by American Scientific Publishers All rights reserved.