1Beijing Information Science and Technology University露出 twitter， Beijing

2Beijing Institute of New Technology Applications， Beijing

Email: 757101221@qq.com

Received: Sep. 26th， 2013; revised: Oct. 20th， 2013; accepted: Oct. 29th， 2013

Copyright © 2013 Leiming Cheng et al. This is an open access article distributed under the Creative Commons Attribution License， which permits unrestricted use， distribution， and reproduction in any medium， provided the original work is properly cited.

ABSTRACT：

This paper is aimed at solving the problems that LBP feature contains outlier and the dimension of LBP feature 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 Mahalanobis 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， CASPEAL-R1 and LFW face databases validate the effectiveness of face recognition.

Keywords: Face Recognition; Robust Local Binary Pattern; Robust Function; Mahalanobis Distance

基于鲁棒的局部二值花式东谈主脸识别算法*

程雷鸣1，其木苏荣1，靳  薇2

1北京信息科技大学，北京

2北京市新本事应用商讨所，北京

Email: 757101221@qq.com

摘 要：

空姐大乱交

本文针对LBP算法特征包含outlier和维渡过高的问题提议了一种基于鲁棒的局部二值花式(RobustLBP)的快速灵验的东谈主脸识别算法。RobustLBP算法的念念想是在LBP算法的基础上加上一个Robust函数撤回outlier达到降维的规画。最初通过计较LBP特征各个维度和中心元素的马氏距离行动Robust函数的输入，使得Robust函数不时估算出迫切信息。然后愚弄这些信息求出变换矩阵撤回原始LBP特征的outlier。终末比对降维后特征间的卡方距离杀青东谈主脸识别。在FERET、CAS-PEAL-R1、LFW东谈主脸数据库上的实考诠释本文提议体式在是东谈主脸识别上具有优厚性。

收稿日历：2013年9月26日；修回日历：2013年10月20日；托福日历：2013年10月29日

重要词：东谈主脸识别；鲁棒的局部二值花式；Robust函数；马氏距离露出 twitter