On-line signature recognition through the combination of real dynamic data and synthetically generated static data
Entidad
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesEditor
Elsevier BVFecha de edición
2015-09Cita
10.1016/j.patcog.2015.03.019
Pattern Recognition 48.9 (2015): 2921-2934
ISSN
0031-3203 (print); 1873-5142 (online)DOI
10.1016/j.patcog.2015.03.019Financiado por
M. D.-C. is supported by a PhD fellowship from the ULPGC and M.G.-B. is supported by a FPU fellowship from the Spanish MECD. This work has been partially supported by projects: MCINN TEC2012-38630- C04-02, Bio-Shield (TEC2012-34881) from Spanish MINECO, BEAT (FP7-SEC-284989) from EU, CECABANK and Cátedra UAM-TelefónicaProyecto
info:eu-repo/grantAgreement/EC/FP7/284989Versión del editor
http://dx.doi.org/10.1016/j.patcog.2015.03.019Materias
Biometric performance evaluation; Off-line signature verification; On-line and off-line signature fusion; On-line signature verification; Signature synthesis; TelecomunicacionesNota
This is the author’s version of a work that was accepted for publication in Pattern Recognition . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition , 48, 9 (2005) DOI: 10.1016/j.patcog.2015.03.019Derechos
© 2015 Elsevier B.V. All rights reservedEsta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Resumen
On-line signature verification still remains a challenging task within biometrics. Due to their behavioral nature (opposed
to anatomic biometric traits), signatures present a notable variability even between successive realizations. This
leads to higher error rates than other largely used modalities such as iris or fingerprints and is one of the main reasons
for the relatively slow deployment of this technology. As a step towards the improvement of signature recognition
accuracy, the present paper explores and evaluates a novel approach that takes advantage of the performance boost
that can be reached through the fusion of on-line and off-line signatures. In order to exploit the complementarity of the
two modalities, we propose a method for the generation of enhanced synthetic static samples from on-line data. Such
synthetic off-line signatures are used on a new on-line signature recognition architecture based on the combination
of both types of data: real on-line samples and artificial off-line signatures synthesized from the real data. The new
on-line recognition approach is evaluated on a public benchmark containing both real versions (on-line and off-line) of
the exact same signatures. Different findings and conclusions are drawn regarding the discriminative power of on-line
and off-line signatures and of their potential combination both in the random and skilled impostors scenarios.
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Google Scholar:Galbally Herrero, Javier
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Díaz-Cabrera, Moisés
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Ferrer, Miguel Ángel
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Gómez-Barrero, Marta
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Morales Moreno, Aythami
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Fiérrez Aguilar, Julián
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