Experimental results are presented using a large mug-shot gallery representative of a law enforcement agency's mug-shot database. All results are compared against three state-of-the-art commercial-off-the-shelf face recognition systems. Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. These composites, generated from witness descriptions, are posted in public places and media with the hope that some viewers will provide tips about the identity of the suspect. This method of identifying suspects is slow, tedious, and may not lead to the timely apprehension of a suspect. Hence, there is a need for a method that can automatically and efficiently match facial composites to large police mug-shot databases. Because of this requirement, facial composite recognition is an important topic for biometrics researchers. Although substantial progress has been made in non-forensic facial composite (or viewed composite) recognition over the past decade, very little work has been done using operational composites relevant to law enforcement agencies. Furthermore, no facial composite to mug-shot matching systems have been documented that are readily deployable as standalone software. (Publisher abstract modified)
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