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Article Dans Une Revue Pattern Recognition Année : 2012

On measuring forgery quality in online signatures

Résumé

This work proposes a novel measure to quantify the quality of a skilled forgery sample in the online signature framework. Such a quality measure is constructed by adapting our former Personal Entropy to the context of skilled forgeries production. For validation, we confront our quality measure to several types of skilled forgeries (static, dynamic, professional) captured on different acquisition platforms. Indeed, four databases are exploited: MCYT-100, Philips database, BioSecure data subsets DS2 and DS3. We prove the effectiveness of our quality measure to quantify the quality of all types of skilled forgeries available with regards to the performance of three classifiers: a Dynamic Time Warping, a Hidden Markov models and a Gaussian Mixture Model.

Dates et versions

hal-00663830 , version 1 (27-01-2012)

Identifiants

Citer

Nesma Houmani, Sonia Garcia-Salicetti, Bernadette Dorizzi. On measuring forgery quality in online signatures. Pattern Recognition, 2012, 45 (3), pp.1004-1018. ⟨10.1016/j.patcog.2011.08.019⟩. ⟨hal-00663830⟩
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