Research on Face Recognition Method Under Uncontrolled Illumination Variation

Abstract

Abstract: A new face recognition algorithm is proposed with high recognition rate under uncontrolled illumination conditions. The new algorithm process face images in advance using Weber local descriptor, which means that the processed image is insensitive to illumination changing. An improved linear discriminant analysis algorithm is adopt for feature extracting, finally, nearest neighbor classifier based on Euclidean distance is applied to classify. The new algorithm is tested on Yale and The Extended Yale Database B face database respectively, in comparison with classic face recognition algorithms, the performance of the proposed method is superior to other's under uncontrolled illumination variation and the speed of the proposed method can fully meet the requirements of real-time face recognition.

Key words: weber's law, feature extracting, face recognition, fisher linear discriminant analysis

CLC Number:

TP391.41

Kong Rui, Zhang Bing. Research on Face Recognition Method Under Uncontrolled Illumination Variation[J]. Journal of System Simulation, 2016, 28(3): 689-695.

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