Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52643
Title: Off-line signature stability by optical flow: Feasibility study of predicting the verifier performance
Authors: Diaz, Moises 
Ferrer, Miguel A. 
Pirlo, G.
Giannico, G.
Henríquez, P. 
Impedovo, D.
UNESCO Clasification: 330412 Dispositivos de control
Keywords: handwriting recognition
pattern recognition
support vector machines
Issue Date: 2016
Project: Síntesis de muestras biométricas para aplicaciones de salud y seguridad 
Journal: Proceedings - International Carnahan Conference on Security Technology 
Conference: 49th Annual IEEE International Carnahan Conference on Security Technology, ICCST 2015 
Abstract: 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
Source: Proceedings - International Carnahan Conference on Security Technology[ISSN 1071-6572],v. 2015-January (7389707), p. 341-345
Appears in Collections:Actas de congresos
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