文档来源为:从网络收集整理.word版本可编辑.欢迎下载支持.编号：审定成绩：重庆邮电大学毕业设计（论文）设计（论文）题目：改进LBP的人脸识别算法研究学院名称：软件工程学院学生姓名：肖霖生专业：软件工程班级：1301106学号：19指导教师：周丽芳答辩组负责人：填表时间：2015年5 月重庆邮电大学教务处制摘要在各种生物特征识别方法中，自动人脸识别有其自身特殊的优势，因而在生物识别中有着重要的地位。

经过三十多年的发展，人脸识别技术取得了长足的进步，目前最好的人脸识别系统在理想情况下已经能够取得可以接受的识别性能，并已经出现了若干人脸识别系统。

但由于人脸识别问题的复杂性和客观条件的多重影响，人脸识别应用系统仍然面临着许多需要解决的关键问题。

人脸特征提取是人脸识别的关键，关系到分类识别算法的选取与识别正确率，从一定意义上讲，它关系到自动人脸识别系统的有效性。

局部二值模式(LBP全称)是一种灰度范围内的纹理描述方式，它从一种纹理局部近邻定义中衍生出来，最初是为了辅助性地度量局部图像对比度提出。

近年来，研究者们成功地将其用于人脸特征描述和识别，并取得了显著的效果。

然而，LBP算子本身还不够完善，因为像素值之间对比度的考虑缺失，令一些重要的纹理特征被丢失了，在这里我们提出一种名为LMCP的方法，这个方法通过预处理，减少了纹理特征的丢失，从而有效的解决LBP原算子对像素间对比度缺乏考虑的这个问题，从而完善了LBP原算子在这方面的不足。

累赘的描述太多关键的没说到英文的也要改【关键词】：人脸识别 LBP 光照正常化对比度分层ABSTRACTAutomatic Face Recognition (AFR) holds an important position in various biometrics techniques for its superiority. With more than 30 years’development, AFR has made great achievements. The state-of-the-art AFR system can perform identification successfully under well-controlled environment, and many commercial AFR systems have appeared. However, due to the complexity and uncertainty of face recognition, there are still many key problems to be resolved for further application of AFR. Feature extraction is the crux of face recognition problem, which directly related to the selection of the classification algorithm and the accuracy of the system.The local binary pattern (LBP) operator is defined as a gray-scale invariant texture measure, derived from a general definition of texture in a local neighborhood. It was first introduced as a complementary measure for local image contrast. Recently, the LBP has been successfully applied to face recognition as texture descriptor and excellent result has achieved. However, there are still many limitations in the basic LBP operator and the LBP-based face recognition algorithm. To resolve these problems, the dissertation is devoted to the investigation on LBP and its application in face recognition. However, LBP operator itself is not perfect, because the contrast between the pixel values considered missing, to make some important texture are lost, where we propose a method called LMCP, this method by pretreatment reduced loss of texture, so as to effectively solve the original operator of the LBP-pixel contrast between the lack of consideration of this issue, and thus improve the original LBP operator is insufficient in this regard.【Key words】Face Recognition Local Binary PatternNormalization of illumination Contrast stratified目录摘要 ........................................................................................................................................... - 0 - ABSTRACT ................................................................................................................................. - 0 - 第一章绪论.............................................................................................................................. - 3 - 第一节课题的研究背景及意义........................................................................................ - 3 -一、生物识别技术.................................................................................................... - 3 -二、生物识别的过程................................................................................................ - 4 -第二节人脸识别技术概况................................................................................................ - 5 -一、人脸识别技术国内外现状................................................................................ - 5 -二、人脸识别的难点和研究意义............................................................................ - 6 -第三节人脸识别算法分类................................................................................................ - 7 - 第四节本文的研究内容及组织........................................................................................ - 7 -一、本文主要研究内容............................................................................................ - 7 -二、本文组织安排.................................................................................................... - 8 - 第二章 LBP 算子基本原理及应用............................................................................................ - 9 - 第一节 LBP 算子概述........................................................................................................ - 9 -一、纹理概述............................................................................................................ - 9 -二、 LBP 算子............................................................................................................ - 9 -第二节 LBP 的特点.......................................................................................................... - 12 - 第三节 LBP 算子的发展和演化...................................................................................... - 12 -一、 LGBP.................................................................................................................. - 13 -二、 LTP.................................................................................................................... - 13 -第四节小结...................................................................................................................... - 15 - 第三章 LMCP方法..................................................................................................................... - 15 - 第一节 LBP方法的缺点................................................................................................... - 15 - 第二节获取LMCP特征.................................................................................................... - 16 - 第三节将LMCP特征用于人脸识别................................................................................ - 17 -弄的和你上面的目录一样你的重点是这个不是LBP第四节图像与处理.......................................................................................................... - 18 - 第四章实验与结果分析.......................................................................................................... - 20 - 第一节引言...................................................................................................................... - 20 - 第二节人脸库.................................................................................................................. - 20 - 第三节实验环境,步驟及参数设置................................................................................ - 21 -一、实验环境.......................................................................................................... - 21 -二、实验方法.......................................................................................................... - 22 -第四节实验...................................................................................................................... - 22 -一、基于Yale人脸库的实验................................................................................ - 22 -二、基于ORL人脸库的实验.................................................................................. - 24 -第五节结果与分析.......................................................................................................... - 26 - 第五章总结与致谢.................................................................................................................. - 27 -第一章绪论第一节课题的研究背景及意义一、生物识别技术身份鉴定是人类社会日常生活中的基本活动之一，人们几乎每时每刻都需要证明自己的身份。