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In this paper, a historical briefing of face recognition is presented. Some psychological aspects of the subject and models considered for face perception are also presented. A model of automated face recognition, based on algorithm designated eigenfaces is considered and presented in details. Applications of the face recognition algorithm for computer forensics are presented, especially for recognizing people in crime scenes. With the purpose of recognizing people with half-occluded faces, concealed with masks or other devices found normally in crime scenes, the concepts of eigenfaces are extended to engage new algorithms called eigeneyes, eigenmouth and eigennose.

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This article describes several user localization methods currently used to support locationbased services (LBS) in GSM and WCDMA mobile networks. Nowadays, many high-technology crimes rely on mobile stations (MS) and existing telecommunication networks. One way of combating fraud and other illegal activities is to perfect techniques for localizing MS almost in real time. The precision of this process varies with method and depending on whether the MS is outdoors or indoors, but generally speaking ranges from tens to hundreds of meters. Using their "mPosition" system, Nokia has achieved even greater precision in MS localization. These methods can also be used in WLAN networks.