关键词: 光照不变量, 多特征融合, 主成分分析, 人脸识别

Abstract: Extracting illumination invariants from face image is an effective way to improve the robust-illumination performance of incomplete training sample face recognition. The previous algorithms extracting the high frequency characteristics of face image from different angles as illumination invariants can’t get integral essential feature of face and have some limitations. In this paper, from the perspective of feature level and decision level fusion, a complex illumination face recognition method based on multi-feature fusion is proposed. The proposed algorithm can utilize the different advantages of several illumination invariants and improve the robust-illumination performance of face recognition under complex lighting environment. The experimental results on the Yale B + and the uncontrolled lighting face database show that the proposed algorithm is effective.

Key words: illumination invariants, multi-feature fusion, principal component analysis, face recognition