ios平台下人脸识别系统实现研究.pdf

204 2013 ，49（22） Computer Engineering and Applications 计算机工程与应用 iOS 平台下人脸识别系统实现研究 刘彦伯，韩家新 LIU Yanbo, HAN Jiaxin 西安石油大学 计算机学院，西安 710065 School of Computer, Xi ’an Shiyou University, Xi ’an 710065, China LIU Yanbo, HAN Jiaxin. Research of development of face recognition system based on iOS platform. Computer Engi- neering and Applications, 2013, 49（22）：204-207. Abstract ：A face recognition system based on Apple company ’s embedded operating system-iOS is proposed. Through the re- search of AdaBoost face detection algorithm based on Haar-like features, the real-time face detection is achieved. An improved method of face recognition based on hidden markov model is put forward. This method uses singular value compression to sub- tract the character of the face image, which not only reduces the amount of data storage and computational complexity but also solves the inefficient caused by processing large number of data of image in embedded system. The experiment result shows that rapid detection, high real-time performance and high recognize rate can be acquired in this method, which can be used as the base of other types of face recognition application software system in iOS platform. Key words ：iOS platform; face detection; singular value compression; hidden Markov model; face recognition 摘 要：设计了一个基于苹果公司嵌入式操作系统iOS 平台下的人脸识别系统。通过对基于Haar-like特征的AdaBoost 人脸 检测算法的研究，实现了实时人脸检测。提出了一种改进的基于隐马尔科夫模型的人脸识别方法，此方法采用奇异值压缩 抽取人脸图像特征作为观察序列，减少了数据的存储量和计算量，解决了嵌入式系统中由于图像处理数据量大造成的低 效。实验结果证明，该系统检测速度快，实时性强，识别率高，可以作为iOS 平台上其他类型人脸识别应用软件开发的基础。 关键词：iOS 平台；人脸检测；奇异值压缩；隐马尔科夫模型；人脸识别 文献标志码：A 中图分类号：TP391 doi ：10.3778/j.issn.1002-8331.1203-0338 1 引言 于奇异值压缩的隐马尔科夫模型人脸识别方法能够很好 当今社会，随着计算机的集成性和移动互联网的高速 地减少数据的存储量和计算量，使得人脸识别这类复杂的 发展和应用，智能移动设备开始走进我们的日常生活。越 算法能够在嵌入式环境中更好地运行。 来越多的人开始接触并拥有智能移动设备。所谓的智能 移动设备就是指智能手机，平板电脑，以及一些有着高性