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A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models
dc.creator | Galar Idoate, Mikel | es_ES |
dc.creator | Derrac, Joaquín | es_ES |
dc.creator | Peralta, Daniel | es_ES |
dc.creator | Triguero, Isaac | es_ES |
dc.creator | Paternain Dallo, Daniel | es_ES |
dc.creator | López Molina, Carlos | es_ES |
dc.creator | García, Salvador | es_ES |
dc.creator | Benítez, José Manuel | es_ES |
dc.creator | Pagola Barrio, Miguel | es_ES |
dc.creator | Barrenechea Tartas, Edurne | es_ES |
dc.creator | Bustince Sola, Humberto | es_ES |
dc.creator | Herrera, Francisco | es_ES |
dc.date.accessioned | 2015-07-23T16:27:19Z | |
dc.date.available | 2017-02-14T00:00:16Z | |
dc.date.issued | 2015 | |
dc.identifier.issn | 0950-7051 | |
dc.identifier.uri | https://hdl.handle.net/2454/17643 | |
dc.description.abstract | This 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.sponsorship | This work was supported by the Research Projects CAB(CDTI), TIN2011-28488, and TIN2013-40765-P.D | en |
dc.format.mimetype | application/pdf | en |
dc.language.iso | eng | en |
dc.publisher | Elsevier | en |
dc.relation.ispartof | Knowledge-Based Systems 81 (2015) 76–97 | en |
dc.rights | © 2015 Elsevier B.V. The manuscript version is made available under the CC BY-NC-ND 4.0 license. | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Fingerprint classification | en |
dc.subject | Feature extraction | en |
dc.subject | Classification | en |
dc.subject | Fingerprint recognition | en |
dc.subject | SMV | en |
dc.subject | Neural networks | en |
dc.subject | Ensembles | en |
dc.subject | Orientation map | en |
dc.subject | Singular points | en |
dc.title | A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models | en |
dc.type | Artículo / Artikulua | es |
dc.type | info:eu-repo/semantics/article | en |
dc.contributor.department | Automática y Computación | es_ES |
dc.contributor.department | Automatika eta Konputazioa | eu |
dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
dc.embargo.terms | 2017-02-14 | |
dc.identifier.doi | 10.1016/j.knosys.2015.02.008 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//TIN2011-28488/ES/ | en |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TIN2013-40765-P/ES/ | en |
dc.relation.publisherversion | https://dx.doi.org/10.1016/j.knosys.2015.02.008 | |
dc.type.version | Versión aceptada / Onetsi den bertsioa | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | en |