【摘要】 介绍一种基于隐马尔可夫模型(hidden Markov module,HMM)的人脸识别系统,该系统对人脸采用普通网络摄像头实时检测,通过皮肤模型进行背景去除,并用改进后的HMM算法进行识别.实验结果表明,改进后的HMM算法能提高原HMM算法的准确率,采用皮肤模板对检测到的人脸进行精确定位后,进一步提高了识别算法的准确度.更多还原

【Abstract】 A newhidden 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 HMMface recognition algorithm.Afast face detection algorithmusing 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.更多还原