论文总字数：30392字

摘 要

随着安全入口控制和金融贸易方面应用需要的快速增长，生物统计识别方法在现实生活中得到广泛应用。人脸识别因其在安全验证系统、信用卡验证、医学、档案管理、视频会议、人机交互等方面有着巨大应用前景,已成为前模式识别和人工智能领域的研究热点之一。

合照图像快速定位人脸并识别其二维码毕设题目主要识别合照中人的脸部，同时给出指定人物的二维码，毕设题目包括样本训练，合照图像中的人脸识别，关注人物图像的人脸二维码生成模块。

毕设使用C 编程开发，图像处理平台采用OpenCV第三方库，二维码的生成使用的是LibQRcord库，用到的IDE平台是Visual Studio 2010。毕设题目实现的是合照图像快速定位人脸并识别其二维码。通过采用高斯平滑来消除图像的噪声，在进行二值化，二值化主要采用局域阈值方法，通过PCA算法提取特征值，识别匹配等操作。把定位后的人脸矩形限定的区域输入给LibQRcode，生成与人脸对应的二维码。毕设题目在win10系统下进行了人脸识别准确率测试，可以识别并匹配清晰且端正的人脸。

关键词：人脸识别；直方图对比度增强；人脸归一化；PCA算法；二维码

The Design and Implementation of Quick Positioning Faces and Identifying Their QRCodes

Abstract

With the rapid growth of application requirements for security access control and financial trade, a wide range of technologies are used in biometric identification methods. Face recognition has become a research hotspot in the field of pre-pattern recognition and artificial intelligence because of its huge application prospects in security verification system, credit card verification, medical science, file management, video conferencing, and human-computer interaction.

The combined image quickly locates the face and identifies its two-dimensional code. The completed topic mainly identifies the face of the person in the composition. At the same time, the two-dimensional code of the specified person is given. The topic of the film includes the sample training, and the face recognition in the combined image. Focusing on the image of human face QR code generation module

This book is set up using C programming and development, image processing platform uses OpenCV third-party library, the generation of two-dimensional code is used libqrcode library, the IDE platform used is Visual Studio 2010. The function of the completed topic is the preprocessing of the face, and the completion of the topic uses the histogram contrast enhancement and face normalization. By using Gaussian smoothing to eliminate the noise of the image, the binarization is performed. The binarization mainly uses the local threshold method, and the PCA algorithm extracts the eigenvalues, identifies the matching and other operations. The area defined by the positioned face rectangle is input to LibQRcode, and a two-dimensional code corresponding to the face is generated. Complete the topic under the win10 system for face recognition accuracy test, can identify and match clear and correct face.

Keywords: face recognition; histogram contrast enhancement; face normalization; PCA algorithm; QRcode

目 录

摘 要 I

Abstract II

目 录 III

第一章 绪论 1

1.1合照图像快速定位人脸并识别其二维码设计与实现的研究背景 1

1.2合照图像快速定位人脸并识别其二维码的研究意义 1

1.3 课题研究的现状 2

1.3.1国外的发展概况 2

1.3.2国内的发展概况 3

1.4毕业设计的章节安排 3

第二章 系统的开发环境 5

2.1 Visual Studio 2010概述 5

2.2 OpenCV函数包 5

2.2.1 OpenCV简介 5

2.2.2 OpenCV配置 6

第三章 相关支撑算法简介 8

3.1 人脸图像的预处理 8

3.1.1 人脸图像灰度处理 8

3.1.2 人脸图像平滑去噪 9

3.1.3人脸图像的归一化处理 11

3.2 人脸识别的相关理论 14

3.2.1 人脸特征提取 14

3.2.2 特征的匹配与分类 15

3.3 人脸识别的常用训练与测试模式 16

3.3.1 训练模式 16

3.2.2 测试模式 16

3.4 人脸识别的主流数据库 17

3.5 人脸识别的评价标准 17

3.5.1 识别准确率 17

3.5.2 识别时间 18

3.6 基于PCA的人脸识别方法 18

3.6.1 概述 18

3.6.2 特征脸算法 18

第四章 实现、测试和结果分析 22

4.1人脸识别代码设计 22

4.2实验结果展示 30

第五章 总结与展望 35

5.1总结 35

5.2展望 36

参考文献 37

致 谢 39

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