Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46129
DC FieldValueLanguage
dc.contributor.authorDas, Abhijiten_US
dc.contributor.authorSuwanwiwat, Hemmaphanen_US
dc.contributor.authorFerrer, Miguel A.en_US
dc.contributor.authorPal, Umapadaen_US
dc.contributor.authorBlumenstein, Michaelen_US
dc.date.accessioned2018-11-23T01:39:18Z-
dc.date.available2018-11-23T01:39:18Z-
dc.date.issued2018en_US
dc.identifier.issn2047-4938en_US
dc.identifier.urihttp://hdl.handle.net/10553/46129-
dc.description.abstractThis study focuses on a comprehensive study of Automatic Signature Verification (ASV) for off-line Thai signatures; an investigation was carried out to characterise the challenges in Thai ASV and to baseline the performance of Thai ASV employing baseline features, being Local Binary Pattern, Local Directional Pattern, Local Binary and Directional Patterns combined (LBDP), and the baseline shape/feature-based hidden Markov model. As there was no publicly available Thai signature database found in the literature, the authors have developed and proposed a database considering real-world signatures from Thailand. The authors have also identified their latent challenges and characterised Thai signature-based ASV. The database consists of 5,400 signatures from 100 signers. Thai signatures could be bi-script in nature, considering the fact that a single signature can contain only Thai or Roman characters or contain both Roman and Thai, which poses an interesting challenge for script-independent SV. Therefore, along with the baseline experiments, the investigation on the influence and nature of bi-script ASV was also conducted. From the equal error rates and Bhattacharyya distance, the score achieved in the experiments indicate that the Thai SV scenario is a script-independent problem. The open research area on this subject of research has also been addressed.en_US
dc.languageengen_US
dc.publisher2047-4938
dc.relation.ispartofIET Biometricsen_US
dc.sourceIET Biometrics[ISSN 2047-4938],v. 7, p. 615-627en_US
dc.subject3307 Tecnología electrónicaen_US
dc.subject.otherhandwriting recognitionen_US
dc.subject.otherhidden Markov modelsen_US
dc.subject.otherfeature extractionen_US
dc.subject.otherimage textureen_US
dc.titleThai automatic signature verification system employing textural featuresen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1049/iet-bmt.2017.0218
dc.identifier.scopus85056076237-
dc.identifier.isi000465417800015
dc.contributor.authorscopusid7403596707-
dc.contributor.authorscopusid55603101700-
dc.contributor.authorscopusid55636321172-
dc.contributor.authorscopusid57200742116-
dc.contributor.authorscopusid56243577200-
dc.description.lastpage627en_US
dc.description.firstpage615en_US
dc.relation.volume7en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid3164655
dc.contributor.daisngid4673900
dc.contributor.daisngid233119
dc.contributor.daisngid25227
dc.contributor.daisngid110880
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Das, A
dc.contributor.wosstandardWOS:Suwanwiwat, H
dc.contributor.wosstandardWOS:Ferrer, MA
dc.contributor.wosstandardWOS:Pal, U
dc.contributor.wosstandardWOS:Blumenstein, M
dc.date.coverdateNoviembre 2018
dc.identifier.ulpgces
dc.description.sjr0,366
dc.description.jcr2,092
dc.description.sjrqQ2
dc.description.jcrqQ3
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptIDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptSeñales y Comunicaciones-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
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