Towards human-assisted signature recognition: improving biometric systems through attribute-based recognition
Metadatos
Title:
Towards human-assisted signature recognition: improving biometric systems through attribute-based recognition
Author:
Morocho, Derlin; Morales Moreno, Aythami; Fiérrez, Julián; Vera-Rodríguez, Rubén
Entity:
UAM. Departamento de Tecnología Electrónica y de las Comunicaciones
UAM Author:
Fierrez Aguilar, Julián
; Morales Moreno, Aythami
Publisher:
Institute of Electrical and Electronics Engineers Inc.
Date:
2016-02
Citation:
10.1109/ISBA.2016.7477227
2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA). IEEE, 2016. 7477227
ISBN:
978-1-4673-9728-5
DOI:
10.1109/ISBA.2016.7477227
Funded by:
A.M. is supported by a JdC contract by the Spanish MECD (JCI-2012-12357). This work has been partially supported by projects: Bio-Shield (TEC2012-34881) from Spanish MINECO, BEAT (FP7-SEC-284989) from EU.
Project:
Gobierno de España. TEC2012-34881; info:eu-repo/grantAgreement/EC/FP7/284989
Editor's Version:
http://dx.doi.org/10.1109/ISBA.2016.7477227
Subjects:
Manuals; Databases; Forgery; Biometrics (access control); Crowdsourcing; Training; Telecomunicaciones
Note:
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. D. Morocho, A. Morales, J. Fierrez and R. Vera-Rodriguez, "Towards human-assisted signature recognition: Improving biometric systems through attribute-based recognition," 2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA), Sendai, 2016, pp. 1-6. doi: 10.1109/ISBA.2016.7477227
Rights:
© 2016 IEEE
Abstract:
This work explores human-assisted schemes for
improving automatic signature recognition systems. We
present a crowdsourcing experiment to establish the human
baseline performance for signature recognition tasks and a
novel attribute-based semi-automatic signature
verification system inspired in FDE analysis. We present
different experiments over a public database and a
self-developed tool for the manual annotation of signature
attributes. The results demonstrate the benefits of
attribute-based recognition approaches and encourage to
further research in the capabilities of human intervention
to improve the performance of automatic signature
recognition systems.
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