Research And Implementation On Face Detectionalgorithm

Face detection means to detecte face from the image or video background in accordance with certain strategy. Because of its important applications in security access control,content-based retrieval,video conferencing,facial expression recognition and other fields,face detection have begun to be a very active research topic on the field of computer vision and pattern recognition in recent years. Based on the extensive reading of literatures,this paper elaborates to the present situation and development of face detection technology,analyzes and summarizes the face detection of the related methods.The study work of this paper mainly includes the following aspects:(1) A method of skin detection algorithm based on the YCbCr color space have been studied. After comparing with several color space,this paper uses brightness and color separation in the YC bCrcolor space for skin color segmentation.Then it is carried out with the method of binarization processing. In order to eliminate the effect of noise,the paper uses the method of the filtering and mathematieal morphology.(2) A method of face detection algorithm based on Adaboost algorithm have been studied. For the disadvantages of Adaboost algorithms: When the detector encounters faces rotated,there always occurs center undetected area.So this paper adds two new feature templates,which improve the detection effect greatly.(3) As skin color detection under complex background image achieves the high false detection rate and the Adaboost algorithm's detection result is not satisfactory in multi-pose and multi-face images. In this paper,a novel face detection method combined skin color detection and Adaboost algorithm based on improved model is porposed. At the front of Adaboost detector , the skin color detection is added. The results of experiment show that the method have achieved the purpose of optimizing the detector.