A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

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dc.contributor.authorGalar Idoate, Mikel
dc.contributor.authorDerrac, Joaquín
dc.contributor.authorPeralta, Daniel
dc.contributor.authorTriguero, Isaac
dc.contributor.authorPaternain Dallo, Daniel
dc.contributor.authorLópez Molina, Carlos
dc.contributor.authorGarcía, Salvador
dc.contributor.authorBenítez, José Manuel
dc.contributor.authorPagola Barrio, Miguel
dc.contributor.authorBarrenechea Tartas, Edurne
dc.contributor.authorBustince Sola, Humberto
dc.contributor.authorHerrera, Francisco
dc.contributor.departmentAutomática y Computaciónes_ES
dc.contributor.departmentAutomatika eta Konputazioaeu
dc.date.accessioned2015-07-23T16:27:19Z
dc.date.available2017-02-14T00:00:16Z
dc.date.issued2015
dc.description.abstractThis paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.en
dc.description.sponsorshipThis work was supported by the Research Projects CAB(CDTI), TIN2011-28488, and TIN2013-40765-P.Den
dc.embargo.lift2017-02-14
dc.embargo.terms2017-02-14
dc.format.mimetypeapplication/pdfen
dc.identifier.doi10.1016/j.knosys.2015.02.008
dc.identifier.issn0950-7051
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/17643
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofKnowledge-Based Systems 81 (2015) 76–97en
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN//TIN2011-28488/ES/
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TIN2013-40765-P/ES/
dc.relation.publisherversionhttps://dx.doi.org/10.1016/j.knosys.2015.02.008
dc.rights© 2015 Elsevier B.V. The manuscript version is made available under the CC BY-NC-ND 4.0 license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectFingerprint classificationen
dc.subjectFeature extractionen
dc.subjectClassificationen
dc.subjectFingerprint recognitionen
dc.subjectSMVen
dc.subjectNeural networksen
dc.subjectEnsemblesen
dc.subjectOrientation mapen
dc.subjectSingular pointsen
dc.titleA survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning modelsen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery44c7a308-9c21-49ef-aa03-b45c2c5a06fd

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