Improving radial triangulation-based forensic palmprint recognition according to point pattern comparison by relaxation

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Show simple item record Wang, Ruifang Ramos, Daniel Fiérrez, Julián
dc.contributor.other UAM. Departamento de Tecnología Electrónica y de las Comunicaciones es_ES 2015-03-20T13:14:03Z 2015-03-20T13:14:03Z 2012
dc.identifier.citation 2012 5th IAPR International Conference on Biometrics, ICB. IEEE, 2012. 427 - 432 en_US
dc.identifier.isbn 978-1-4673-0396-5 (print) en_US
dc.identifier.isbn 978-1-4673-0397-2 (online) en_US
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. Wang, D. Ramos, J. Fiérrez, "Improving radial triangulation-based forensic palmprint recognition according to point pattern comparison by relaxation" in 5th IAPR International Conference Biometrics (ICB), New Delhi (India), 2012, 427 - 432 en_US
dc.description.abstract Forensic palmprint recognition, which mainly deals with high-resolution palmprints and latent-to-full palmprint comparison, has aroused research highlights because of the increased use of the evidence of palmprints in forensics. There are some in-depth works on high-resolution palmprint preprocessing (i.e., segmentation and enhancement) and feature extraction. However, few works on latent-to-full palmprint comparison have been done. Recently, radial triangulation-based latent-to-full palmprint comparison algorithm was proposed as it has been proposed for forensic likelihood ratio computation using fingerprints, and proved to have identification usability and efficiency for palmprint comparison. In this work, we generalize point pattern comparison by relaxation to minutiae-based palmprint recognition and improve the latent-to-full palmprint comparison algorithm based on radial triangulation. Firstly, local minutiae comparison is modified according to novel point pattern comparison method and global minutiae comparison is based on centroid distribution. Then logistic regression learning is used for comparison score computation. Performance of the proposed algorithm is evaluated on forensic databases including 22 latent palmprints from real cases and 8680 full palmprints from criminal investigation field. Experimental results show the improvement on identification accuracy and efficiency of our approach. A rank-1 identification rate of 69% is achieved, compared with 63% of previous radial triangulation-based. en_US
dc.description.sponsorship The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement number 238803; the DGUI of Comunidad Autónoma de Madrid and Universidad Autónoma de Madrid via grant CCG10-UAM/TIC-5792; Departamento de Identificación of Guardia Civil Española. en_US
dc.format.extent 7 pág. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher IEEE en_US
dc.rights © 2012 IEEE en_US
dc.subject.other Computer forensics en_US
dc.subject.other Feature extraction en_US
dc.subject.other Fingerprint identification en_US
dc.subject.other Image enhancement en_US
dc.subject.other Image segmentation en_US
dc.subject.other Palmprint recognition en_US
dc.subject.other Regression analysis en_US
dc.title Improving radial triangulation-based forensic palmprint recognition according to point pattern comparison by relaxation en_US
dc.type conferenceObject en
dc.type bookPart en
dc.subject.eciencia Telecomunicaciones es_ES
dc.identifier.doi 10.1109/ICB.2012.6199788
dc.identifier.publicationfirstpage 427
dc.identifier.publicationlastpage 432
dc.relation.eventdate March 29-April 1, 2012 en_US
dc.relation.eventnumber 5
dc.relation.eventplace New Delhi (India) en_US
dc.relation.eventtitle 5th IAPR International Conference on Biometrics, ICB 2012 en_US
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/238803 en
dc.type.version info:eu-repo/semantics/acceptedVersion en 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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