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Local Features for Enhancement and Minutiae Extraction in Fingerprints
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0002-4929-1262
2008 (English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 17, no 3, p. 354-363Article in journal (Refereed) Published
Abstract [en]

Accurate fingerprint recognition presupposes robust feature extraction which is often hampered by noisy input data. We suggest common techniques for both enhancement and minutiae extraction, employing symmetry features. For enhancement, a Laplacian-like image pyramid is used to decompose the original fingerprint into sub-bands corresponding to different spatial scales. In a further step, contextual smoothing is performed on these pyramid levels, where the corresponding filtering directions stem from the frequency-adapted structure tensor (linear symmetry features). For minutiae extraction, parabolic symmetry is added to the local fingerprint model which allows to accurately detect the position and direction of a minutia simultaneously. Our experiments support the view that using the suggested parabolic symmetry features, the extraction of which does not require explicit thinning or other morphological operations, constitute a robust alternative to conventional minutiae extraction. All necessary image processing is done in the spatial domain using 1-D filters only, avoiding block artifacts that reduce the biometric information. We present comparisons to other studies on enhancement in matching tasks employing the open source matcher from NIST, FIS2. Furthermore, we compare the proposed minutiae extraction method with the corresponding method from the NIST package, mindtct. A top five commercial matcher from FVC2006 is used in enhancement quantification as well. The matching error is lowered significantly when plugging in the suggested methods. The FVC2004 fingerprint database, notable for its exceptionally low-quality fingerprints, is used for all experiments.

Place, publisher, year, edition, pages
New York: IEEE Press, 2008. Vol. 17, no 3, p. 354-363
Keywords [en]
Differential scale space, fidelity, fingerprint restoration, image enhancement, image pyramid, linear symmetry, minutiae extraction, orientation tensor, parabolic symmetry, symmetry features
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-1358DOI: 10.1109/TIP.2007.916155ISI: 000253272300009Scopus ID: 2-s2.0-40749102899Local ID: 2082/1737OAI: oai:DiVA.org:hh-1358DiVA, id: diva2:238576
Note

Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Image Processing. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Halmstad's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Available from: 2008-04-25 Created: 2008-04-25 Last updated: 2018-03-23Bibliographically approved

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Fronthaler, HartwigKollreider, KlausBigun, Josef

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