In general, the field of face recognition has lots of research that have put interest in order to detect the face and to identify it and also to track it. Many researchers have concentrated on the face identification and detection problem by various approaches. The proposed approach is further very useful and helpful in very huge real time application. Thus the Face Detection, Identification and Tracking mechanism which is proposed here is used to detect the faces in videos in the real time application by using the PRDIT (Proposed Rectangular Detection Identification and tracking) algorithm. Thus the proposed mechanism is very help full in identifying individual persons who are been involved in the action of robbery, murder cases and terror activities. Although in face recognition the algorithm used is of histogram equalization combined with Back propagation neural network in which we recognize an unknown test image by comparing it with the known training set images that are been stored in the database. Also the proposed approach uses skin color extraction as a parameter for face detection. A multi linear training and rectangular face feature extraction are done for training, identifying, detecting and tracking. Thus the proposed technique is very useful in identify a single person from a group of faces. Thus the proposed technique is well suited for all kinds of faces which have a specific complexion varying under certain range. Also we have taken a real life example and simulated the algorithms in IDL Tool successfully. Keywords: PRDIT, histogram equalization, rectangular features.

PRDIT Crime Investigation Face Detection