Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/41711
Título: Dynamic signature verification system based on one real signature
Autores/as: Diaz, Moises 
Fischer, Andreas
Ferrer, Miguel A. 
Plamondon, Rejean
Clasificación UNESCO: 120325 Diseño de sistemas sensores
Palabras clave: Rapid Human Movements
Feature-Extraction
Kinematic Theory
Online
Recognition, et al.
Fecha de publicación: 2018
Publicación seriada: IEEE Transactions on Cybernetics 
Resumen: The dynamic signature is a biometric trait widely used and accepted for verifying a person's identity. Current automatic signature-based biometric systems typically require five, ten, or even more specimens of a person's signature to learn intrapersonal variability sufficient to provide an accurate verification of the individual's identity. To mitigate this drawback, this paper proposes a procedure for training with only a single reference signature. Our strategy consists of duplicating the given signature a number of times and training an automatic signature verifier with each of the resulting signatures. The duplication scheme is based on a sigma lognormal decomposition of the reference signature. Two methods are presented to create human-like duplicated signatures: the first varies the strokes' lognormal parameters (stroke-wise) whereas the second modifies their virtual target points (target-wise). A challenging benchmark, assessed with multiple state-of-the-art automatic signature verifiers and multiple databases, proves the robustness of the system. Experimental results suggest that our system, with a single reference signature, is capable of achieving a similar performance to standard verifiers trained with up to five signature specimens.
URI: http://hdl.handle.net/10553/41711
ISSN: 2168-2267
DOI: 10.1109/TCYB.2016.2630419
Fuente: IEEE Transactions on Cybernetics [ISSN 2168-2267], v. 48 (1), p. 228-239
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