Fingerprint Recognition

Fingerprint recognition can be used for biometric identification and authentication.

It is possible to trick some fingerprint scanners into recognising false fingerprints, created using various moulds. Higher specification fingerprint scanners implement heat sensors, pulse sensors, and blood oxygenation sensors to prevent false fingerprints being seen as real.

Fingerprint recognition involves complex algorithms, which compare the type of fingerprint and it's features. Fingerprint features can be divided into macro and micro.

Macro features are large, and can be seen by the naked eye.

• Ridge patterns
• Ridge pattern area
• Core point
• Delta point
• Type lines
• Ridge count

Micro features are made of Minutia points, which are compared by type, orientation, spatial frequency, curvature and position.

Last updated on 26 January 2009, at 14:04.