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Registration of fingerprints by complex filtering and by 1D projections of orientation images
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
2005 (English)In: Audio- and video-based biometric person authentication: 5th International Conference, AVBPA, Hilton Rye Town, N.Y. USA, July 20-22 2005 : proceedings / [ed] Takeo Kanade, Anil Jain, Nalini K Ratha (eds), Berlin: Springer Berlin/Heidelberg, 2005, Vol. LNCS-3546, 171-183 p.Conference paper, Published paper (Refereed)
Abstract [en]

When selecting a registration method for fingerprints, the choice is often between a minutiae based or an orientation field based registration method. In selecting a combination of both methods, instead of selecting one of the methods, we obtain a one modality multi-expert registration system. If the combined methods are based on di#erent features in the fingerprint, e.g. the minutiae points respective the orientation field, they are uncorrelated and a higher registration performance can be expected compared to when only one of the methods are used. In this paper two registration methods are discussed that do not use minutiae points, and are therefore candidates to be combined with a minutiae based registration method to build a multi-expert registration system for fingerprints with expected high registration performance. Both methods use complex orientations fields but produce uncorrelated results by construction. One method uses the position and geometric orientation of symmetry points, i.e. the singular points (SPs) in the fingerprint to estimate the translation respectively the rotation parameter in the Euclidean transformation. The second method uses 1D projections of orientation images to find the transformation parameters. Experimental results are reported.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2005. Vol. LNCS-3546, 171-183 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3546
Keyword [en]
Computer Science, Artificial Intelligence
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:hh:diva-14927DOI: 10.1007/11527923_18ISI: 000231117100018ISBN: 978-3-540-27887-0 ISBN: 3-540-27887-7 OAI: oai:DiVA.org:hh-14927DiVA: diva2:408395
Conference
Audio- and Video-Based Biometric Person Authentication, 5th International Conference, AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005
Available from: 2011-04-04 Created: 2011-04-04 Last updated: 2012-10-16Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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Output format
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  • asciidoc
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