Extraction Of Head And Face Boundaries For Face Detection Application Face detection is an importent first step to many advanced computer vision, biometrics and multimedia applications such as face tracking, face recognition and video surveillance. In this paper, a faster face detection system is proposed and the method of extracking head and face boundaries along with its facial features has been utilized. Initially, boundary tracking is employed to extract the head and face boundaries from the image. This boundary tracking is done with the help of BW (Black and White) tracking function. Facial features are extracted using gabor filter algorithm. The neural network employed for face detection is based on multi layer neurons architecture while is a feed forword network. This approch is even applicable for detecting faces in cluster images. Experimental results show that the proposed approach can perfrom the extraction human head, face boundaries and detection of face succesfully. The proposed technique can be applied for images with single face as well as nultiple faces and the faces are detected succesfully with high detection rate when compared to the adaboost technique of face detection.