The topic of face detection derives from that of face recognition, and has emerged as an individual important subject. This thesis is on the realization of a dynamic human face-detection system with very high hit-rate and slow false-alarm-rate. In this paper, a dynamic face-detection system based on haar-like features with the frame difference motion detecting front and the face-color detection post processing in combined color spaces is proposed and accomplished end.The proposed dynamic face detection procedure is divided into three phases:The first one is the adjacent frame based motion-detection, in which the morphology method is employed to extract the motion objects and their edges, returning the rectangular range of motion-part to the haar-like classifier. Because most of non-motion region is removed in this step, the operating speed of the next step is promoted.In the second phase, the concise haar-like feature is used and layers of classifiers are reduced according to the characteristics of the proposed system, which further speeds up the processing rate.In the third phase, the face-color detection in a combinatorial color space of the rgb and YIQ effectively decreases the false-alarm-rate of the system.Experimental results have shown the proposed system can attain 93% hit-rate for common used video sequences, which is higher than that of the normal haar-like feature based classifier. The false-alarm-rate of the proposed system is far lower than that of the haar-like feature based one. The speed of face-detection in the system is 11 frames per second, meeting the requirement. |