Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/52643
Título: Off-line signature stability by optical flow: Feasibility study of predicting the verifier performance
Autores/as: Diaz, Moises 
Ferrer, Miguel A. 
Pirlo, G.
Giannico, G.
Henríquez, P. 
Impedovo, D.
Clasificación UNESCO: 330412 Dispositivos de control
Palabras clave: handwriting recognition
pattern recognition
support vector machines
Fecha de publicación: 2016
Proyectos: Síntesis de muestras biométricas para aplicaciones de salud y seguridad 
Publicación seriada: Proceedings - International Carnahan Conference on Security Technology 
Conferencia: 49th Annual IEEE International Carnahan Conference on Security Technology, ICCST 2015 
Resumen: Prediction of performance in Off-line Automatic Signature Verification (ASV) per signer is one of the important topics regarding to automatic verification. It could be hypothesized that the performance of a signer is related to its global stability. This way, the more stable the signer signatures, the smaller the area of its feature space is, being more difficult to get inside for an impostor. In this paper we assess the feasibility to predict the performance of a signer through his/her global stability. As in a real scenario, only the enrolled signatures are used to calculate the stability of the signer. Similarly, only these signatures are used to train two completely different off-line ASVs. Then, the performance and the stability per signer are compared. Our results suggest that there is a certain relationship between the global stability of the enrolled signatures and the performance in terms of Equal Error Rate.
URI: http://hdl.handle.net/10553/52643
ISBN: 9781479986910
ISSN: 1071-6572
DOI: 10.1109/CCST.2015.7389707
Fuente: Proceedings - International Carnahan Conference on Security Technology[ISSN 1071-6572],v. 2015-January (7389707), p. 341-345
Colección:Actas de congresos
miniatura
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