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Communication Dans Un Congrès Année : 2008

A novel personal entropy measure confronted to online signature verification systems' performance

Résumé

In this paper, we study the relation between a novel personal entropy measure for online signatures, based on local density estimation by a Hidden Markov Model, and the performance of several state-of-the-art classifiers for online signature verification. We show that there is a clear relation between such entropy measure of a person’s signature and behavior of the classifier. We carry out this study on a Dynamic Time Warping classifier, a Gaussian Mixture Model and a Hidden Markov Model as well. Signatures were split by the K-Means algorithm in three categories which are coherent across four different databases of around 100 persons each: BIOMET, MCYT-100, BioSecure data subsets DS2 and DS3. We studied the impact of such categories on classifier’s performance with a larger signature data subset of DS3, of 430 persons
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hal-01375821 , version 1 (03-10-2016)

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Nesma Houmani, Sonia Garcia-Salicetti, Bernadette Dorizzi. A novel personal entropy measure confronted to online signature verification systems' performance. BTAS 2008 : IEEE 2nd International Conference on Biometrics : Theory, Applications and System, Sep 2008, Arlington United States. pp.1 - 6, ⟨10.1109/BTAS.2008.4699362⟩. ⟨hal-01375821⟩
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