Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2005: (UTC) administrator
Metadata Last Update2020: (UTC) administrator
Citation KeyMaranaJain:2005:RiFiMa
TitleRidge-based fingerprint matching sing Hough Transform
Access Date2021, Nov. 27
Number of Files1
Size614 KiB
Context area
Author1 Marana, Aparecido Nilceu
2 Jain, Anil K.
Affiliation1 UNESP – Faculdade de Ciências – Departamento de Computação – Bauru – SP – Brazil
2 Michigan State University – College of Engineering – East Lansing – Michigan - USA
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2005-07-05 21:20:39 :: nilceu -> banon ::
2005-07-07 19:48:57 :: banon -> nilceu ::
2008-07-17 14:10:59 :: nilceu -> banon ::
2008-08-26 15:17:01 :: banon -> administrator ::
2009-08-13 20:37:44 :: administrator -> banon ::
2010-08-28 20:01:17 :: banon -> administrator ::
2020-02-19 03:19:08 :: administrator -> :: 2005
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsFingerprint matching
Hough transform
AbstractDespite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSU-VERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge-based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%.
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