Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/105801
Título: Improving on-line signature skillfulness
Autores/as: Ferrer Ballester, Miguel Ángel 
Diaz Cabrera, Moises 
Carmona Duarte, María Cristina 
Plamondon, Rejean
Clasificación UNESCO: 3325 Tecnología de las telecomunicaciones
Palabras clave: Automatic Signature Verification
Sigma-Lognormal model
Forged signatures
Fecha de publicación: 2018
Conferencia: 1st International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018)
Resumen: One of the biggest challenges in on-line signature verification is the detection of counterfeited signatures. Recently, novel schemes based on the kinematic theory of rapid human movements and its associated Sigma-Lognormal model has been proposed to improve the detection of on-line skilled forgeries. But for a more realistic and reliable estimation of the forgery detection rate, we would need more challenging on-line forgeries than those included in current databases. To get better on-line skilled forgeries, this paper aimed at leveraging the Sigma-Lognormal model to improve the skill of any online forged signature. Specifically, we propose to replace the original velocity profile of any on-line signature by a synthetic Sigma-Lognormal profile. The new profile emulates a genuine-like velocity profiles without modifying the original ballistic trajectory. Experimental results were performed with the 132 on-line users of publicly BiosecureID database. It is shown that the detection rate of forgeries is significantly worsened when the velocity profile is replaced by the synthetic one. A countermeasure to detect this kind of improved fake signatures is also proposed.
URI: http://hdl.handle.net/10553/105801
ISBN: 1-895193-06-0
Fuente: Proceedings of 1st International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018)
Colección:Actas de congresos
miniatura
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