Generation of enhanced synthetic off-line signatures based on real on-line data
Entity
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesPublisher
IEEEDate
2014-09Citation
10.1109/ICFHR.2014.87
2014 14th International Conference on Frontiers in Handwriting Recognition (ICFHR). IEEE, 2014. 482 - 487
ISSN
2167-6445ISBN
978-1-4799-4335-7DOI
10.1109/ICFHR.2014.87Funded 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/FP7/284989Editor's Version
http://dx.doi.org/10.1109/ICFHR.2014.87Subjects
Signature synthesis; Signature verification; Texture Measurement; Biometric recognition; TelecomunicacionesNote
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 - 487Rights
© 2014 IEEEAbstract
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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Google Scholar:Díaz-Cabrera, Moisés
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Gómez-Barrero, Marta
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Morales Moreno, Aythami
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Ferrer, Miguel Ángel
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Galbally Herrero, Javier
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