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Local Binary Pattern (LBP) algorithm is a classical algorithm in the field of face recognition. It can capture local detail features, but its robustness and recognition rate are easily affected by external environmental changes.In this paper, an improved LBP algorithm which combines Euclidean distance and differential coding is proposed. The improved EDLBP operator is applied to feature extraction and compared with various improved LBP algorithms in different databases.The experimental results show that the correlation between the EDLBP algorithm and the LBP, MBP, LTP and ELBP algorithms is improved in the databases with illumination diversity and texture rotation. When compared to the recognition rate changes obtained using the CUReT database at different training samples, the highest recognition rate of EDLBP algorithm is 55.49%, 23.36% and 2.46% higher than that of LBP, MBP and LTP algorithms respectively. By comparing similarity of the two face images, the EDLBP algorithm is 1.04%, 2.94%, 4.69%, and 5.56% higher than the latest ELBP algorithm.

Research on Improved LBP Algorithm Based on Euclidean Distance and Differential Coding