Altered fingerprint identification and classification using SP detection and fuzzy classification

Abstract

Fingerprint recognition is one of the most commonly used biometric technology. Even if fingerprint temporarily changes (cuts, bruises) it reappears after the finger heals. Criminals started to be aware of this and try to fool the identification systems applying methods from ingenious to very cruel. It is possible to remove, alter, or even fake fingerprints (made of glue, latex, silicone), by burning the fingertip skin (fire, acid, other corrosive material), by using plastic surgery (changing the skin completely, causing change in pattern—portions of skin are removed from a finger and grafted back in different positions, like rotation or “Z” cuts, transplantations of an area from other parts of the body like other fingers, palms, toes, and soles). This paper presents a new algorithm for altered fingerprints detection based on fingerprint orientation field reliability. The map of the orientation field reliability has peaks in the singular point locations. These peaks are used to analyze altered fingerprints because, due to alteration, more peaks as singular points appear with lower amplitudes.