Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/37175
Campo DC Valoridioma
dc.contributor.authorDiaz, Moisesen_US
dc.contributor.authorFerrer, Miguel A.en_US
dc.contributor.authorSabourin, Roberten_US
dc.date.accessioned2018-05-25T12:54:20Z-
dc.date.available2018-05-25T12:54:20Z-
dc.date.issued2016en_US
dc.identifier.isbn978-1-5090-4847-2en_US
dc.identifier.issn1051-4651en_US
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/37175-
dc.description.abstractAs an emerging issue, multi-script signature verification is a recent challenge for current Automatic Signature Verification (ASV) systems. Relevant differences are presented in the morphology and lexicon of the signature images written in different scripts, such as used symbols, shape of the signatures, legibility, etc. These peculiarities could reduce the success of ASV systems, especially those which were originally designed for only one kind of script. However, one common feature among scripts in ASV is the fact that the greater the number of signatures that are used for training, the better the expected performance. In this work, we propose a method inspired by observations from the neuromotor equivalence theory to artificially enlarge the signature images used to train a state-of-the-art static signature classifier. Experimental results are obtained by using three static signature datasets derived from completely different scripts: Western, Bengali and Devanagari. Our results suggest that the cognitive-inspired model, which aims to duplicate static signatures, tends toward intra-class variability of signatures written in different scripts; the model's beneficial impact is seen in signature verification tests.-
dc.languageengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofProceedings - International Conference on Pattern Recognitionen_US
dc.sourceProceedings - International Conference on Pattern Recognition [ISSN 1051-4651], v. 0 (7899791), p. 1147-1152en_US
dc.subject120304 Inteligencia artificial-
dc.subject3307 Tecnología electrónica-
dc.subject.otherVerification-
dc.subject.otherRecognition-
dc.subject.otherMechanisms-
dc.subject.otherOnline-
dc.subject.otherArt-
dc.titleApproaching the intra-class variability in multi-script static signature evaluationen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference23rd International Conference on Pattern Recognition, ICPR 2016en_US
dc.identifier.doi10.1109/ICPR.2016.7899791en_US
dc.identifier.scopus85019153706-
dc.identifier.isi000406771301026-
dc.contributor.authorscopusid36760594500-
dc.contributor.authorscopusid55636321172-
dc.contributor.authorscopusid56251129500-
dc.description.lastpage1152en_US
dc.description.firstpage1147en_US
dc.relation.volume0en_US
dc.investigacionIngeniería y Arquitectura-
dc.type2Actas de congresosen_US
dc.contributor.daisngid29956019-
dc.contributor.daisngid233119-
dc.contributor.daisngid82197-
dc.description.numberofpages6en_US
dc.identifier.eisbn978-1-5090-4847-2-
dc.utils.revision-
dc.contributor.wosstandardWOS:Diaz, M-
dc.contributor.wosstandardWOS:Ferrer, MA-
dc.contributor.wosstandardWOS:Sabourin, R-
dc.date.coverdateEnero 2016en_US
dc.identifier.conferenceidevents121058-
dc.identifier.ulpgc-
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate04-12-2016-
crisitem.event.eventsenddate08-12-2016-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Física-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0003-3878-3867-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameDíaz Cabrera, Moisés-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
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