基于Andriod移动设备嵌入式机器视觉的人脸识别

基于Andriod移动设备嵌入式机器视觉的人脸识别

二○一三届毕业设计

基于Andriod移动设备嵌入式机器视觉的人脸识别

系统设计

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完成时间：2013年6月16日

二〇一三年七月

摘要

人脸识别是在图像或视频流中进行人脸的检测和定位，其中包括人脸在图像或视频流中的所在位置、大小、形态、个数等信息，近年来由于计算机运算速度的飞速发展使得图像处理技术在许多领域得到了广泛应用，其中包含智能监控、安全交易、更安全更友好的人机交互等。如今在许多公司或研究所已经作为一门独立的课题来研究探索。

近年来，随着移动互联网的发展，智能手机平台获得了长足的发展。然而，手机钱包、手机远程支付等新应用的出现使得手机平台的安全性亟待加强。传统的密码认证存在易丢失、易被篡改等缺点，人脸识别不容易模仿、篡改和丢失，因而适用于手机安全领域中的应用。

本论文在分析国内外人脸识别研究成果的基础上，由摄像头采集得到人脸图像，在高性能嵌入式系统平台上，采用JAVA高级语言进行编程，对检测得到的图像进行人脸检测、特征定位、人脸归一化、特征提取和特征识别。在Android平台上实现了基于图像的人脸识别功能。

本文主要的研究内容：首先对当前人脸识别技术的研究现状和常用的人脸检测和人脸识别方法做了扼要的介绍，然后着重介绍了Adaboost人脸检测算法和通过LBP直方图匹配的人脸识别算法，最后基于这两种人脸检测和人脸识别的算法，在Android平台上通过移植OpenCV并进行编程从而实现了移动设备的人脸识别功能。关键词：Android，OpenCV，人脸识别，Eclipse

Abstract

The face recognition is to face detection and location in the image or video stream, including the location of the face in the image or video stream, the size, shape, and then number of information in recent years due to the rapid

computing speed makes the development of image processing technology has been widely applied in many fields, which includes intelligent monitoring, secure transactions, safer and more friendly and human-computer interaction. Today, as

a separate subject many companies or research are to study and explore.

In recent years，smart phone platforms achieve rapid development according toprosperous of 3G wireless technology．The applications，like mobile payment，remote transaction，make our life easier but bring more safety issues too．Traditional safety certification uses password as authentication method．which is 1iable to falsification and forgetfulness．Facial feature Call overcome the disadvantages brought by traditional methods，So it is fit for safety applications on smart phone platform．

Based on the research results of the analysis of face recognition at home and abroad in this paper, We obtained the facial images obtained by the camera and then used Senior JAVA language to program for face detection, feature

localization , face normalization, feature extraction and pattern recognition in in high-performance embedded system platform. It implemented the face

recognition function based on images on the Android platform.

The research contents in this paper are as follows: first introduced the

current status of the face recognition technology and the common face detection

and face recognition methods briefly, and then focused on the Adaboost face detection algorithm and face recognition algorithm of matching people through

LBP histogram. At last, it enabled the face recognition function of mobile devices

by transplanting OpenCV and programing on the Android platform based on

these two face detection and face recognition algorithm.

KEYWORDS: Android，OpenCV，face recognition，Eclipse