Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/77397
Campo DC Valoridioma
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-
Colección:Artículos
miniatura
Adobe PDF (7,2 MB)
Vista resumida

Citas SCOPUSTM   

30
actualizado el 17-nov-2024

Citas de WEB OF SCIENCETM
Citations

20
actualizado el 17-nov-2024

Visitas

185
actualizado el 24-ago-2024

Descargas

468
actualizado el 24-ago-2024

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.