【作者】 陈鹏；

【导师】 陈恩庆；

【作者基本信息】 郑州大学 ， 计算机技术（专业学位）， 2013， 硕士

【摘要】 作为生物体特征识别技术,人脸识别技术具有使用方便、难以仿冒、识别精度高、速度快等特点。而传统的人脸识别系统都是在以PC为基础的平台上进行开发的,这样的系统在使用的场合和成本上都有很大的缺陷。而随着嵌入式技术的发展,现在短小精悍、方便实用、成本低廉的嵌入式系统平台的已经具有很强的数据处理能力,嵌入式人脸识别已成为目前研究和应用的趋势。本文设计实现了一种准确性、稳定性较高的嵌入式人脸识别系统,为此主要做了以下几方面的工作：首先搭建了嵌入式系统平台。为了弥补了ARM9运算能力不强,ARM+DSP组合价格偏高的不足,本文选用以ARM11为核心的tiny6410开发板和普通USB摄像头作为系统的硬件平台,并在平台上移植了Linux操作系统、Qt图像化界面库和Opencv计算机视觉库。然后设计实现了基于此嵌入式平台的人脸识别系统。对系统图像采集及格式转换模块,人脸检测模块,人脸图像预处理模块和人脸识别模块所采用的方法和实现过程分别进行了详细介绍,并对系统性能做了测试。测试结果表明系统达到了预期的设计目标。最后针对人脸识别系统中反照片欺诈的问题,论文提出了一种基于眨眼检测的反照片欺诈方法和一种基于视线变化的反照片欺诈方法,并对所提方法进行了测试,初步实现了反照片欺诈的目标。更多还原

【Abstract】 As a biological feature identification technology,face recognition technology has the advantages of convenient use, difficult to counterfeit,high precision and speed etc.. But the traditional face recognition systems are based on PC,this system has a lot of defects in the use of the occasion and cost. With the development of embedded technology.Now small, convenient and practical, low cost embedded system platform has strong data processing ability.Embedded face recognition will become the mainstream of future research.The purpose of this paper is to design a face recognition with high accuracy and stability.For this,article has done the following work. The first is to build a system platform, In order to make up for the less operational capability of ARM9, and lack of high prices ARM+DSP system. This design uses a development board tiny6410based on ARM11and the USB camera as the hardware platform of the system. Then i have transplanted Linux operating system,Qt graphic interface and Opencv computer vision library. And then i introduce the implementation process of the embedded face recognition system.The principle,method and the implementation procedure of mage capture and format conversion module,face detection module,face image preprocessing module and face recognition module is introduced.And design of the whole system is completed.The system was tested,and the test shows that the expected design is achieved.At last for the photo deception problems.The anti-photo detection method which is based on blinking eye detection and the changing of eye vision are raised.And experiment is done and the expected result is obtained.The result shows that the system can distinguish the photo and the real person.更多还原