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dc.contributor.authorAmeller, Marco Antonioes_ES
dc.contributor.authorGonzález, María Angélicaes_ES
dc.date.accessioned2016-11-04T09:27:55Z
dc.date.available2016-11-04T09:27:55Z
dc.date.issued2016-01-10es_ES
dc.identifier.citationADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 5 (2016)es_ES
dc.identifier.issn2255-2863es_ES
dc.identifier.urihttp://hdl.handle.net/10366/131644
dc.description.abstractIn order to identify subjects in a convenient and efficient way one must use some special feature that makes it possible to discriminate between persons. Some of the features are biometric in nature, such as iris texture, hand shape, the human face, and of course finger prints. These play an important role in many automatic identification systems, since every person is believed to have a unique set of fingerprints. Before a fingerprint image can be looked up in a database, it has to be classified into one of 5 types in order to reduce processing times.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherEdiciones Universidad de Salamanca (EspaÑa)es_ES
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputaciónes_ES
dc.subjectInformóticaes_ES
dc.subjectComputinges_ES
dc.subjectInformation Technologyes_ES
dc.titleMinutiae filtering using ridge-valley methodes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivs 3.0 Unported
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