光电子快报(英文版), 2018, 14 (2): 143, Published Online: Sep. 17, 2018  

A novel fusion method of improved adaptive LTP and two-directional two-dimensional PCA for face feature extraction

Author Affiliations
1 Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Tele-communications, Chongqing 400065, China
2 Engineering Research Center for Information Accessibility and Service Robots, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Abstract
In this paper, under different illuminations and random noises, focusing on the local texture feature’s defects of a face image that cannot be completely described because the threshold of local ternary pattern (LTP) cannot be calculated adaptively, a local three-value model of improved adaptive local ternary pattern (IALTP) is proposed. Firstly, the dif-ference function between the center pixel and the neighborhood pixel weight is established to obtain the statistical characteristics of the central pixel and the neighborhood pixel. Secondly, the adaptively gradient descent iterative function is established to calculate the difference coefficient which is defined to be the threshold of the IALTP opera-tor. Finally, the mean and standard deviation of the pixel weight of the local region are used as the coding mode of IALTP. In order to reflect the overall properties of the face and reduce the dimension of features, the two-directional two-dimensional PCA ((2D)2PCA) is adopted. The IALTP is used to extract local texture features of eyes and mouth area. After combining the global features and local features, the fusion features (IALTP+) are obtained. The experi-mental results on the Extended Yale B and AR standard face databases indicate that under different illuminations and random noises, the algorithm proposed in this paper is more robust than others, and the feature’s dimension is smaller. The shortest running time reaches 0.329 6 s, and the highest recognition rate reaches 97.39%.

LUO Yuan, WANG Bo-yu, ZHANG Yi, ZHAO Li-ming. A novel fusion method of improved adaptive LTP and two-directional two-dimensional PCA for face feature extraction[J]. 光电子快报(英文版), 2018, 14(2): 143.

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