深圳大学学报（理工版）2008，Vol.25Issue(1)：71-75,5.
基于皮肤模板和改进HMM的自动人脸识别系统
Automatic face recognition based on skin masking and improved HMM
摘要
Abstract
A new hidden Markov module (HMM) based face recognition system is presented in this paper. Face images were extracted automatically from live videos captured by a Creative WebCam,and faces were recognized in real time using an improved HMM face recognition algorithm. A fast face detection algorithm using boosted Haar-like features was applied initially to detect faces regions from the video stream. The detected face region was further refined by a skin color masking module to achieve more accurate face position. To improve the accuracy of HMM based face recognition algorithm, discrete wavelet transform, instead of discrete cosine transform, was used to extract observation sequences for HMM. Experiments were conducted using two face databases:the ORL database and the Nottingham color face image database. The results on both databases show that the proposed method can improve the accuracy by more than six percents. Further improvement has been observed when a skin masking module is used to refine the detected face region.关键词
人脸识别/人脸检测/彩色图像处理/生物特征识别/隐马尔可夫模型Key words
face recognition/face detection/color image processing/biometrics/hidden Markov model分类
信息技术与安全科学引用本文复制引用
沈琳琳,明仲..基于皮肤模板和改进HMM的自动人脸识别系统[J].深圳大学学报（理工版）,2008,25(1):71-75,5.基金项目
国家自然科学基金资助项目(60673122) （60673122）
深圳大学科研启动基金资助项目(200746) （200746）
