Integrating rare minutiae in generic fingerprint matchers for forensics

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dc.contributor.author Krish, Ram P.
dc.contributor.author Fiérrez, Julián
dc.contributor.author Ramos, Daniel
dc.contributor.other UAM. Departamento de Tecnología Electrónica y de las Comunicaciones es_ES
dc.date.accessioned 2016-12-07T18:28:15Z
dc.date.available 2016-12-07T18:28:15Z
dc.date.issued 2015-11-16
dc.identifier.citation 2015 IEEE International Workshop on Information Forensics and Security (WIFS). IEEE, 2015. 7368557 en_US
dc.identifier.isbn 978-1-4673-6802-5
dc.identifier.uri http://hdl.handle.net/10486/675867
dc.description Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. R. P. Krish, J. Fierrez and D. Ramos, "Integrating rare minutiae in generic fingerprint matchers for forensics," 2015 IEEE International Workshop on Information Forensics and Security (WIFS), Rome, 2015, pp. 1-6. doi: 10.1109/WIFS.2015.7368557 en_US
dc.description.abstract Automated Fingerprint Identification Systems (AFIS) are commonly used by law enforcement agencies to narrow down the possible suspects from a criminal database. AFIS do not use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. Latent fingerprints obtained from crime scenes are usually partial in nature which results to only very few number of reliable minutiae. Comparing a partial minutiae pattern to a full minutiae pattern is a difficult problem. Towards solving this challenge, we propose a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in typical minutiae-based matchers. The method we propose in this work can be combined with any existing minutiae-based matcher. We first compute a quantitative measure based on least squares between latent and tenprint minutiae points, with rare minutia feature as reference point. Then the similarity score of the reference minutiae-based matcher is modified based on the least square quantitative measure. The modified similarity score thus obtained incorporates the contribution of rare minutia features. We use a realistic forensic fingerprint casework database in our experiments which contains rare minutia features obtained from Guardia Civil, the Spanish law enforcement agency. Experiments are conducted using two reference minutiae-based matchers, namely: NIST-Bozorth3 and VeriFinger. We report a significant improvement in the rank identification accuracies when the reference minutiae matchers are augmented with our proposed algorithm based on rare minutia features. en_US
dc.description.sponsorship R.K. was supported by a Marie Curie Fellowship under project BBfor2 (FP7-ITN-238803) from EU. This work has also been partially supported by Spanish Guardia Civil, project Bio-Shield (TEC2012-34881) from Spanish MINECO, and project BEAT (FP7-SEC-284989) from EU. en_US
dc.format.extent 7 pag. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.rights © 2015 IEEE en_US
dc.subject.other Algorithms en_US
dc.subject.other Feature extraction en_US
dc.subject.other Law enforcement en_US
dc.subject.other Automated fingerprint identification system en_US
dc.subject.other Feature extraction algorithms en_US
dc.subject.other Fingerprint features en_US
dc.subject.other Fingerprint matcher en_US
dc.subject.other Identification accuracy en_US
dc.subject.other Latent fingerprint en_US
dc.subject.other Law-enforcement agencies en_US
dc.subject.other Quantitative measures en_US
dc.subject.other Crime en_US
dc.title Integrating rare minutiae in generic fingerprint matchers for forensics en_US
dc.type conferenceObject en
dc.subject.eciencia Telecomunicaciones es_ES
dc.relation.publisherversion http://dx.doi.org/10.1109/WIFS.2015.7368557
dc.identifier.doi 10.1109/WIFS.2015.7368557
dc.identifier.publicationfirstpage 7368557
dc.relation.eventdate November 16-19, 2015 en_US
dc.relation.eventplace Rome (Italy) en_US
dc.relation.eventtitle IEEE International Workshop on Information Forensics and Security, WIFS 2015 en_US
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/238803 en
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/284989 en
dc.relation.projectID Gobierno de España. TEC2012-34881 es_ES
dc.type.version info:eu-repo/semantics/acceptedVersion en
dc.contributor.group Análisis y Tratamiento de Voz y Señales Biométricas (ING EPS-002) es_ES
dc.rights.accessRights openAccess en
dc.authorUAM Fierrez Aguilar, Julián (261834)


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