Update Strategies for HMM-Based Dynamic Signature Biometric Systems

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dc.contributor.author Tolosana Moranchel, Rubén
dc.contributor.author Vera-Rodríguez, Rubén
dc.contributor.author Ortega-García, Javier
dc.contributor.author Fiérrez, Julián
dc.contributor.other UAM. Departamento de Tecnología Electrónica y de las Comunicaciones es_ES
dc.date.accessioned 2016-11-17T15:10:05Z
dc.date.available 2016-11-17T15:10:05Z
dc.date.issued 2015
dc.identifier.citation 2015 IEEE International Workshop on Information Forensics and Security (WIFS). IEEE, 2015. 7368583 en_US
dc.identifier.isbn 978-1-4673-6802-5
dc.identifier.uri http://hdl.handle.net/10486/675194
dc.description Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. [R. Tolosana, R. Vera-Rodriguez, J. Ortega-Garcia and J. Fierrez, "Update strategies for HMM-based dynamic signature biometric systems," Information Forensics and Security (WIFS), 2015 IEEE International Workshop on, Rome, 2015, pp. 1-6. doi: 10.1109/WIFS.2015.7368583 en_US
dc.description.abstract Biometric authentication on devices such as smart- phones and tablets has increased significantly in the last years. One of the most acceptable and increasing traits is the handwrit- ing signature as it has been used in financial and legal agreements scenarios for over a century. Nowadays, it is frequent to sign in banking and commercial areas on digitizing tablets. For these reasons, it is necessary to consider a new scenario where the number of training signatures available to generate the user template is variable and besides it has to be taken into account the lap of time between them (inter-session variability). In this work we focus on dynamic signature verification. The main goal of this work is to study system configuration update strategies of time functions-based systems such as Hidden Markov Model (HMM) and Gaussian Mixture Models (GMM). Therefore, two different cases have been considered. First, the usual case of having an HMM-based system with a fixed configuration (i.e. Baseline System). Second, an HMM-based and GMM-based sys- tems whose configurations are optimized regarding the number of training signatures available to generate the user template. The experimental work has been carried out using an extended version of the Signature Long-Term database taking into account skilled and random or zero-effort forgeries. This database is comprised of a total of 6 different sessions distributed in a 15-month time span. Analyzing the results, the Proposed Systems achieve an average absolute improvement of 4.6% in terms of EER(%) for skilled forgeries cases compared to the Baseline System whereas the average absolute improvement for the random forgeries cases is of 2.7% EER. These results show the importance of optimizing the configuration of the systems compared to a fixed configuration system when the number of training signatures available to generate the user template increases. en_US
dc.description.sponsorship This work was supported in part by the Project Bio-Shield (TEC2012-34881), in part by Cecabank e-BioFirma Contract, in part by the BEAT Project (FP7-SEC-284989) and in part by Catedra UAM-Telefonica. en_US
dc.format.extent 7 pag. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.rights © 2015 IEEE en_US
dc.subject.other Biometrics en_US
dc.subject.other Dynamic signature en_US
dc.subject.other GMM en_US
dc.subject.other HMM en_US
dc.subject.other Signature Long-Term database en_US
dc.subject.other System configuration update en_US
dc.subject.other Time functions-based system en_US
dc.title Update Strategies for HMM-Based Dynamic Signature Biometric Systems en_US
dc.type conferenceObject en
dc.subject.eciencia Telecomunicaciones es_ES
dc.relation.publisherversion http://dx.doi.org/10.1109/WIFS.2015.7368583
dc.identifier.doi 10.1109/WIFS.2015.7368583
dc.identifier.publicationfirstpage 7368583
dc.relation.eventdate November 16-19, 2015 en_US
dc.relation.eventplace Rome (Italy) en_US
dc.relation.eventtitle IEEE International Workshop on Information Forensics and Security, WIFS 2015 en_US
dc.relation.projectID Gobierno de España. TEC2012-34881 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/284989 en
dc.type.version info:eu-repo/semantics/acceptedVersion en
dc.contributor.group Análisis y Tratamiento de Voz y Señales Biométricas (ING EPS-002) es_ES
dc.rights.accessRights openAccess en
dc.authorUAM Fierrez Aguilar, Julián (261834)
dc.authorUAM Tolosana Moranchel, Rubén (271218)

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