Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/37786
DC FieldValueLanguage
dc.contributor.authorDiaz, Moisesen_US
dc.contributor.authorChanda, S.en_US
dc.contributor.authorFerrer, Miguel A.en_US
dc.contributor.authorBanerjee, C. K.en_US
dc.contributor.authorMajumdar, A.en_US
dc.contributor.authorCarmona-Duarte, Cristinaen_US
dc.contributor.authorAcharya, P.en_US
dc.contributor.authorPal, U.en_US
dc.date.accessioned2018-06-05T08:01:04Z-
dc.date.available2018-06-05T08:01:04Z-
dc.date.issued2017en_US
dc.identifier.isbn9781509009817
dc.identifier.issn2167-6445en_US
dc.identifier.urihttp://hdl.handle.net/10553/37786-
dc.description.abstractHandwritten signature datasets are really necessary for the purpose of developing and training automatic signature verification systems. It is desired that all samples in a signature dataset should exhibit both inter-personal and intra-personal variability. A possibility to model this reality seems to be obtained through the synthesis of signatures. In this paper we propose a method based on motor equivalence model theory to generate static Bengali signatures. This theory divides the human action to write mainly into cognitive and motor levels. Due to difference between scripts, we have redesigned our previous synthesizer [1,2], which generates static Western signatures. The experiments assess whether this method can approach the intra and inter-personal variability of the Bengali-100 Static Signature DB from a performance-based validation. The similarities reported in the experimental results proof the ability of the synthesizer to generate signature images in this script. � 2016 IEEEen_US
dc.languageengen_US
dc.relation.ispartofProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHRen_US
dc.sourceProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR[ISSN 2167-6445],v. 0 (7814037), p. 42-47en_US
dc.subject330405 Sistemas de reconocimiento de caracteresen_US
dc.subject.otherDocument analysisen_US
dc.subject.otherHandwriting signaturesen_US
dc.subject.otherOff-line signaturesen_US
dc.subject.otherSynthetic signaturesen_US
dc.titleMultiple generation of Bengali static signaturesen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conference15th International Conference on Frontiers in Handwriting Recognition, ICFHR 2016
dc.identifier.doi10.1109/ICFHR.2016.0021
dc.identifier.scopus85012884210
dc.contributor.authorscopusid36760594500
dc.contributor.authorscopusid7005580236
dc.contributor.authorscopusid55636321172
dc.contributor.authorscopusid57193318006
dc.contributor.authorscopusid57193308205
dc.contributor.authorscopusid57209616277
dc.contributor.authorscopusid57193311586
dc.contributor.authorscopusid57200742116
dc.description.lastpage47-
dc.description.firstpage42-
dc.relation.volume0
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.date.coverdateJulio 2016
dc.identifier.conferenceidevents121041
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptIDeTIC: 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.deptIDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.orcid0000-0003-3878-3867-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.orcid0000-0002-4441-6652-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameDiaz Cabrera, Moises-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
crisitem.author.fullNameCarmona Duarte, María Cristina-
crisitem.event.eventsstartdate23-10-2016-
crisitem.event.eventsenddate26-10-2016-
Appears in Collections:Actas de congresos
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