A Novel Face Recognition Algorithm Based on Robust Local Binary Pattern
Abstract: This paper is aimed at solving the problems that LBP feature contains outlier and the dimension of LBP fea- ture is too high, and a fast and effective face recognition algorithm based on Robust Local Binary Pattern is proposed. The main idea of RobustLBP is setting a Robust function on the basis of original LBP. First, it calculates the Maha- lanobis distance between the mean vector and every dimension as the argument of Robust function and estimates a set of important information by making Robust function convergence. Then, it obtains a transformation matrix which is used to reject outlier of original feature by using the information. Lastly, it compares the Chi-square distance among the features after reducing dimension in order to complete face recognition. Extensive experiments on FERET, CAS- PEAL-R1 and LFW face databases validate the effectiveness of face recognition.
文章引用: 程雷鸣 , 其木苏荣 , 靳 薇 (2013) 基于鲁棒的局部二值模式人脸识别算法。 计算机科学与应用， 3， 344-348. doi: 10.12677/CSA.2013.38060
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