CAJ | 학술논문

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。
설계료일개기우평과공사감입식조작계통iOS평태하적인검식별계통。통과대기우Haar-like특정적AdaBoost인검검측산법적연구，실현료실시인검검측。제출료일충개진적기우은마이과부모형적인검식별방법，차방법채용기이치압축추취인검도상특정작위관찰서렬，감소료수거적존저량화계산량，해결료감입식계통중유우도상처리수거량대조성적저효。실험결과증명，해계통검측속도쾌，실시성강，식별솔고，가이작위iOS평태상기타류형인검식별응용연건개발적기출。
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.