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Singular point detection algorithm based on the transition line of the fingerprint orientation image

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dc.contributor.author Mathekga, Mmamolatelo E
dc.contributor.author Msiza, IS
dc.date.accessioned 2010-04-18T13:57:26Z
dc.date.available 2010-04-18T13:57:26Z
dc.date.issued 2009-11
dc.identifier.citation Mathekga, ME and Msiza, IS 2009. Singular point detection algorithm based on the transition line of the fingerprint orientation image. 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009, pp 1-6 en
dc.identifier.isbn 978-0-7992-2356-9
dc.identifier.uri http://hdl.handle.net/10204/4046
dc.description 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009 en
dc.description.abstract A new algorithm for identifying and locating singular points on a fingerprint image is presented. This algorithm is based on properties of the fingerprint orientation image, including a feature defined as a transition line. The transition line is shown to provide an efficient means of both tracking and classifying singular points without having to search through the entire fingerprint image. The algorithm is shown to be precise and its performance is evaluated using three measures, namely, the detection accuracy (DA), the detection time (DT) and a Humanversus-Algorithm (HvA) score. Using a dataset from the Fingerprint Verification Competition 2002 (FVC 2002), the performance of the algorithm is: DA = 89.6 %, DT = 0.48 s and HvA = 0.92. en
dc.language.iso en en
dc.subject Transition line en
dc.subject Algorithm en
dc.subject Orientation image en
dc.subject Delta en
dc.subject Detection accuracy en
dc.subject Detection time en
dc.subject Humanversus- Algorithm en
dc.subject Fingerprint verification competition 2002 en
dc.subject Singular point detection en
dc.title Singular point detection algorithm based on the transition line of the fingerprint orientation image en
dc.type Conference Presentation en
dc.identifier.apacitation Mathekga, M. E., & Msiza, I. (2009). Singular point detection algorithm based on the transition line of the fingerprint orientation image. http://hdl.handle.net/10204/4046 en_ZA
dc.identifier.chicagocitation Mathekga, Mmamolatelo E, and IS Msiza. "Singular point detection algorithm based on the transition line of the fingerprint orientation image." (2009): http://hdl.handle.net/10204/4046 en_ZA
dc.identifier.vancouvercitation Mathekga ME, Msiza I, Singular point detection algorithm based on the transition line of the fingerprint orientation image; 2009. http://hdl.handle.net/10204/4046 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Mathekga, Mmamolatelo E AU - Msiza, IS AB - A new algorithm for identifying and locating singular points on a fingerprint image is presented. This algorithm is based on properties of the fingerprint orientation image, including a feature defined as a transition line. The transition line is shown to provide an efficient means of both tracking and classifying singular points without having to search through the entire fingerprint image. The algorithm is shown to be precise and its performance is evaluated using three measures, namely, the detection accuracy (DA), the detection time (DT) and a Humanversus-Algorithm (HvA) score. Using a dataset from the Fingerprint Verification Competition 2002 (FVC 2002), the performance of the algorithm is: DA = 89.6 %, DT = 0.48 s and HvA = 0.92. DA - 2009-11 DB - ResearchSpace DP - CSIR KW - Transition line KW - Algorithm KW - Orientation image KW - Delta KW - Detection accuracy KW - Detection time KW - Humanversus- Algorithm KW - Fingerprint verification competition 2002 KW - Singular point detection LK - https://researchspace.csir.co.za PY - 2009 SM - 978-0-7992-2356-9 T1 - Singular point detection algorithm based on the transition line of the fingerprint orientation image TI - Singular point detection algorithm based on the transition line of the fingerprint orientation image UR - http://hdl.handle.net/10204/4046 ER - en_ZA


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