fingerprint technology

A fingerprint is an impression of the friction ridges on all parts of the finger.Fingerprint identification is the process of comparing questioned and known friction skin ridge impressions from fingers to determine if the impressions are from the same finger. The flexibility of friction ridge skin means that no two finger prints are ever exactly alike (never identical in every detail), even two impressions recorded immediately after each other. Fingerprint identification occurs when an expert determines that two friction ridge impressions originated from the same finger to the exclusion of all others. Friction ridges can be recorded digitally using a technique called Live-Scan.

Fingerprint capture and detection - Fingerprint image acquisition is considered the most critical step of an automated fingerprint authentication system, as it determines the final fingerprint image quality, which has drastic effects on the overall system performance. There are different types of fingerprint readers on the market, but the basic idea behind each capture approach is to measure in some way the physical difference between ridges and valleys. All the proposed methods can be grouped in two major families: solid-state fingerprint readers and optical fingerprint readers. The procedure for capturing a fingerprint using a sensor consists of rolling or touching with the finger onto a sensing area, which according to the physical principle in use (capacitive, optical, thermal, acoustic, etc.) captures the difference between valleys and ridges.

Fingerprint matching techniques can be placed into two categories: minutae-based and correlation based. Minutiae-based techniques first find minutiae points and then map their relative placement on the finger. However, there are some difficulties when using this approach. It is difficult to extract the minutiae points accurately when the fingerprint is of low quality. Also this method does not take into account the global pattern of ridges and furrows. The correlation-based method is able to overcome some of the difficulties of the minutiae-based approach. However, it has some of its own shortcomings. Correlation-based techniques require the precise location of a registration point and are affected by image translation and rotation.

Classifying fingerprints - There are complex classification systems that further break down patterns to plain arches or tented arches. Loops may be radial or ulnar, depending on the side of the hand the tail points towards. Whorls also have sub-group classifications including plain whorls, accidental whorls, double loop whorls, peacock's eye, accidental, composite, and central pocket loop whorls.