High-performance Two-stage Face Recognition Algorithm for Reduced Illumination Effect

Face recognition, which is a method of identifying a person in a digital image, is widely applied to biometric-based authentication systems. A significant decrease in recognition rate is caused by extracted features that are affected by illumination. In an attempt to resolve this problem, in this paper, we present a two-stage algorithm, namely, a local binary pattern (LBP) followed by the algorithm Fisherface. As the first step of this work, a face image is converted to an LBP, which is then projected onto a low-dimensional feature space using Fisherface for subsequent classification and recognition. As a result, the outperformance of this work is demonstrated by a recognition rate of up to 96.45%, a figure far beyond 67.97% using the LBP histogram (LBPH), 84.69% using Fisherface, and 93.09% using the support vector machine (SVM) algorithm.