关键词: 人脸识别, Gabor滤波器, 局部三值模式, 自适应阈值算子

Abstract: In this paper, a new method for face description and recognition is proposed, which is based on feature fusion of Gabor and Local Ternary Pattern（LTP）, and in this new algorithm, the paper alse improves the local ternary pattern and presents a new Local Adaptive Ternary Pattern with an adaptive threshold（LATP）. First, the normalized face image is decomposed by multi-scale and multi-orientation Gabor filters to extract a series of Gabor magnitude maps. Then, Local Adaptive Ternary Pattern（LATP） is used to operate on each extracted Gabor magnitude map to extract the local neighbor pattern and the face image is described by the weighted histogram sequence of all extracted local neighbor patterns, and the weight is determined by information entropy. Finally, the histograms of train images and test images are matched by the chi-square distance. The experiment is conducted on the ORL and Yale face databases. The test results show that the new method has better adaptability under expression changes and illumination variations and has more strong robustness under noise jamming.

Key words: face recognition, Gabor filters, local ternary pattern, adaptive threshold