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SAFE features for matching fingermarks by neighbourhoods of single minutiae
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4929-1262
2014 (English)In: 2014 14th International Symposium on Communications and Information Technologies (ISCIT), Piscataway, N.J.: IEEE Press, 2014, 181-185 p., 7011896Conference paper, Published paper (Refereed)
Abstract [en]

Symmetry Assessment by Finite Expansion (SAFE) is a novel description of image information by means of Generalized Structure Tensor. It represents orientation data in neighbourhood of key points projected onto the space of harmonic functions creating a geometrically interpretable feature of low dimension. The proposed feature has built in quality metrics reflecting accuracy of the extracted feature and ultimately the quality of the key point. The feature vector is orientation invariant in that it is orientation steerable with low computational cost. We provide experiments on minutia key points of forensic fingerprints to demonstrate its usefulness. Matching is performed based on minutia in regions with high orientation variance, e.g. in proximity of core points. Performance of single matching minutia equals to 20% EER and Rank-20 CMC 69% on the only publicly available annotated forensic fingerprint SD27 database.

Further, we complement SAFE descriptors of orientation maps with SAFE descriptors of frequency features in a similar manner. In case of combined features the performance is improved further to 19% EER and 74% Rank-20 CMC. © 2014 IEEE.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2014. 181-185 p., 7011896
Keyword [en]
forensic fingerprint, latent, SD27, biometrics, structure tensor, feature extraction, orientation map
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-26585DOI: 10.1109/ISCIT.2014.7011896ISI: 000380543700040Scopus ID: 2-s2.0-84922895765ISBN: 978-1-4799-4416-3 (print)OAI: oai:DiVA.org:hh-26585DiVA: diva2:749718
Conference
14th International Symposium on Communications and Information Technologies (ISCIT 2014), Incheon, South Korea, September 24-26, 2014
Available from: 2014-09-25 Created: 2014-09-25 Last updated: 2017-09-27Bibliographically approved

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mikaelyan14min(1467 kB)138 downloads
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