Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/77397
DC FieldValueLanguage
dc.contributor.authorGuerra Segura, Elyoenai-
dc.contributor.authorOrtega-Pérez, Aysse-
dc.contributor.authorTravieso González, Carlos Manuel-
dc.date.accessioned2021-02-01T08:29:44Z-
dc.date.available2021-02-01T08:29:44Z-
dc.date.issued2021-
dc.identifier.issn0957-4174-
dc.identifier.otherScopus-
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/74418-
dc.description.abstractSignature verification is a widely explored field due to its high acceptance and its compromise between security and comfort. Recently, different techniques have appeared to improve the capture, processing, and classification of signatures. In this work, authors present a novel and robust in-air signature verification system, which applies the use of Leap Motion controller to characterize in-air strokes, due to its stability and good performance for this task, as it will be demonstrated. Therefore, a database has been built for developing the experiments, which is composed of 100 users, with 10 genuine and 10 forgery samples per user. The implemented system is tested against two tests of impostor samples, zero effort attacks and active impostors. The second type of attacks are developed by different users, who showed very good abilities with the sensor. The classification is done by a Least Square Support Vector Machine. The equal error rate was 0.25% and 1.20%, respectively. The proposed system achieves very good results in comparison with the state-of-the-art one, which suggests that in-air signature processing gives an opportunity to increase systems’ security.-
dc.languageeng-
dc.relation.ispartofExpert Systems with Applications-
dc.sourceExpert Systems with Applications[ISSN 0957-4174],n. 165-
dc.subject3307 Tecnología electrónica-
dc.subject.otherLeap Motion controller-
dc.subject.otherIn-air signatures-
dc.subject.other3D signature verification/recognition-
dc.subject.other3D signature processing-
dc.subject.otherMachine learning-
dc.titleIn-air signature verification system using Leap Motion-
dc.typeinfo:eu-repo/semantics/article-
dc.typeArticle-
dc.identifier.doi10.1016/j.eswa.2020.113797-
dc.identifier.scopus85089418512-
dc.identifier.isi000608479600011-
dc.contributor.authorscopusid57204219746-
dc.contributor.authorscopusid57218530197-
dc.contributor.authorscopusid6602376272-
dc.identifier.eissn1873-6793-
dc.relation.volume165-
dc.investigacionIngeniería y Arquitectura-
dc.type2Artículo-
dc.contributor.daisngid8984371-
dc.contributor.daisngid42764433-
dc.contributor.daisngid42304971-
dc.description.numberofpages14-
dc.utils.revision-
dc.contributor.wosstandardWOS:Guerra-Segura, E-
dc.contributor.wosstandardWOS:Ortega-Perez, A-
dc.contributor.wosstandardWOS:Travieso, CM-
dc.date.coverdateMarzo 2021-
dc.identifier.ulpgc-
dc.contributor.buulpgcBU-TEL-
dc.description.sjr2,07
dc.description.jcr8,665
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
dc.description.miaricds11,0
item.grantfulltextopen-
item.fulltextCon texto completo-
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.orcid0000-0002-4621-2768-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameGuerra Segura, Elyoenai-
crisitem.author.fullNameTravieso González, Carlos Manuel-
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