Generation of enhanced synthetic off-line signatures based on real on-line data
Metadatos
Title:
Generation of enhanced synthetic off-line signatures based on real on-line data
Author:
Díaz-Cabrera, Moisés; Gómez-Barrero, Marta; Morales Moreno, Aythami; Ferrer, Miguel Ángel; Galbally Herrero, Javier
Entity:
UAM. Departamento de Tecnología Electrónica y de las Comunicaciones
UAM Author:
Galbally Herrero, Javier
; Morales Moreno, Aythami
Publisher:
IEEE
Date:
2014-09
Citation:
10.1109/ICFHR.2014.87
2014 14th International Conference on Frontiers in Handwriting Recognition (ICFHR). IEEE, 2014. 482 - 487
ISSN:
2167-6445
ISBN:
978-1-4799-4335-7
DOI:
10.1109/ICFHR.2014.87
Funded by:
This work has been partially supported by projects: MICINN TEC2012-38630-C04-02, Contexts (S2009/TIC-1485) from CAM, Bio-Shield (TEC2012-34881) from Spanish MINECO, TABULA RASA (FP7-ICT-257289) and BEAT (FP7-SEC-284989) from EU, and Cátedra UAM-Telefónica.
Project:
Comunidad de Madrid. S2009/TIC-1485/CONTEXTS; info:eu-repo/grantAgreement/EC/FP7/257289; info:eu-repo/grantAgreement/EC/FP7/284989
Editor's Version:
http://dx.doi.org/10.1109/ICFHR.2014.87
Subjects:
Signature synthesis; Signature verification; Texture Measurement; Biometric recognition; 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. M. Díaz-Cabrera, M. Gómez-Barrero, A. Morales, M. A. Ferrer, J. Galbally, "Generation of Enhanced Synthetic Off-Line Signatures Based on Real On-Line Data" in 14th International Conference on Frontiers in Handwriting Recognition (ICFHR), Heraklion (Greece), 2014, 482 - 487
Rights:
© 2014 IEEE
Abstract:
One of the main challenges of off-line signature verification is the absence of large databases. A possible alternative to overcome this problem is the generation of fully synthetic signature databases, not subject to legal or privacy concerns. In this paper we propose several approaches to the synthesis of off-line enhanced signatures from real dynamic information. These synthetic samples show a performance very similar to the one offered by real signatures, even increasing their discriminative power under the skilled forgeries scenario, one of the biggest challenges of handwriting recognition. Furthermore, the feasibility of synthetically increasing the enrolment sets is analysed, showing promising results.
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