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Approximately 80% of [[vendor]]s base their [[algorithm]]s on the [[extraction]] of [[minutia(e) point]]s relating to breaks in the [[ridge]]s of the fingertips. Other [[algorithm]]s are based on extracting [[ridge pattern]]s. |
Approximately 80% of [[vendor]]s base their [[algorithm]]s on the [[extraction]] of [[minutia(e) point]]s relating to breaks in the [[ridge]]s of the fingertips. Other [[algorithm]]s are based on extracting [[ridge pattern]]s. |
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| + | == Source == |
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| + | * [[GAO]], [[Information Security: Challenges in Using Biometrics]] 7 (GAO-03-1137T) (Sept. 9, 2003) ([http://www.gao.gov/new.items/d031137t.pdf full-text]). |
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== See also == |
== See also == |
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Revision as of 03:41, 31 December 2010
Overview
Fingerprint recognition is one of the best known and most widely used biometric technologies. Automated systems have been commercially available since the early 1970s, and there are currently more than 75 fingerprint recognition technology companies. Until recently, it was used primarily in law enforcement applications.
Historical background
Fingerprints have been used to identify individuals since the mid-1800s. Manual fingerprint identification systems were based on classifying prints according to general characteristics, such as predominant patterns of loops, whorls, or arches in the tiny fingerprint ridges, plus patterns of branches and terminations of the ridges (called minutiae). Fingerprint file data were obtained by using special ink and a ten-print card; fingerprint cross-checking with local and national records was done manually.
The cross-checking process began to be automated in the late 1960s and by 1983 the Federal Bureau of Investigation (FBI) had converted all criminal fingerprint searches from manual to automated operations.
How it works
Fingerprint recognition technology extracts features from impressions made by the distinct ridges on the fingertips. The fingerprints can be either flat or rolled. A flat print captures only an impression of the central area between the fingertip and the first knuckle; a rolled print captures ridges on both sides of the finger.
An image of the fingerprint is captured by a scanner, enhanced, and converted into a template. Scanner technologies can be optical, silicon, or ultrasound technologies. Ultrasound, while potentially the most accurate, has not been demonstrated in widespread use. Optical scanners are the most commonly used. During enhancement, “noise” caused by such things as dirt, cuts, scars, and creases or dry, wet, or worn fingerprints is reduced, and the definition of the ridges is enhanced. Template size ranges from 250 bytes up to 1,000 bytes, depending on which vendor’s proprietary algorithm the system uses.
Approximately 80% of vendors base their algorithms on the extraction of minutia(e) points relating to breaks in the ridges of the fingertips. Other algorithms are based on extracting ridge patterns.
Source
- GAO, Information Security: Challenges in Using Biometrics 7 (GAO-03-1137T) (Sept. 9, 2003) (full-text).