Fingerprint recognition through circular sampling

The ability to uniquely associate a human fingerprint with an individual ha s become an essential part of personal identification for security purposes and law enforcement. This article presents an approach to fingerprint reco gnition based on circularly sampling the fingerprint around an easily ident ified center of the fingerprint. Three matching metrics are presented and c ompared for matching fingerprints with no peculiarities, a missing area, an d rotation with those in a database. The optimum metric, referred to as the angular density, was seven times better for a self match than for a mismat ch, even when the fingerprint was rotated or altered by erasing some of its area.