关键词: 人脸识别, 光照, 局部二值模式, 支持向量机, 视网膜皮层

Abstract: With serious sidelight, it is difficult for the traditional algorithm to eliminate shadows. To improve the illumination compensation effect, a logarithmic transformation function was presented. In order to improve the performance of face recognition, by taking this problem as a classic pattern classification problem, a new method combining Local Binary Pattern (LBP) and Support Vector Machine (SVM) was proposed. One-against-one was used to convert multi-class problem to two-class problem, that can be used by SVM. Simulation experiments were conducted on the database of CMU PIE, AR, CAS-PEAL and one face database collected by the authors. The results show that lighting effects can be well eliminated and the proposed method performs better than the traditional ones.

Key words: face recognition, lighting, Local Binary Pattern (LBP), Support Vector Machine (SVM), Retinex