On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine

Marc Fuentes; Sonia Garcia-Salicetti; Bernadette Dorizzi

doi:10.1109/IWFHR.2002.1030918

On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine

Marc Fuentes
, Sonia Garcia-Salicetti
, Bernadette Dorizzi

CNRS SAMOVAR UMR 5157

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

We propose in this work to perform on-line signature verification by the fusion of two complementary verification modules. The first one considers a signature as a sequence of points and models the genuine signatures of a given signer by a Hidden Markov Model (HMM). Forgeries are used to compute a decision threshold. In the second module, global parameters of a signature are the inputs of a two-classes neural network trained for each signer on both the genuine and "other" signatures (genuine signatures of other signers). Fusion of the scores given by these two experts through a Support Vector Machine (SVM), allows improving the results over those of each module, on Philips' Database.

langue originale	Anglais
titre	Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002
Editeur	IEEE Computer Society
Pages	253-258
Nombre de pages	6
ISBN (imprimé)	0769516920, 9780769516929
Les DOIs	https://doi.org/10.1109/IWFHR.2002.1030918
état	Publié - 1 janv. 2002
Modification externe	Oui
Evénement	8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002 - Ontario, ON, Canada Durée: 6 août 2002 → 8 août 2002

Série de publications

Nom	Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR
ISSN (imprimé)	1550-5235

Une conférence

Une conférence	8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002
Pays/Territoire	Canada
La ville	Ontario, ON
période	6/08/02 → 8/08/02

Accès au document

10.1109/IWFHR.2002.1030918

Autres fichiers et liens

Lien vers la publication dans Scopus

Contient cette citation

Fuentes, M., Garcia-Salicetti, S., & Dorizzi, B. (2002). On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine. Dans Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002 (p. 253-258). (Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR). IEEE Computer Society. https://doi.org/10.1109/IWFHR.2002.1030918

Fuentes, Marc ; Garcia-Salicetti, Sonia ; Dorizzi, Bernadette. / On line signature verification : Fusion of a Hidden Markov Model and a neural network via a support vector machine. Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002. IEEE Computer Society, 2002. p. 253-258 (Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR).

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title = "On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine",

abstract = "We propose in this work to perform on-line signature verification by the fusion of two complementary verification modules. The first one considers a signature as a sequence of points and models the genuine signatures of a given signer by a Hidden Markov Model (HMM). Forgeries are used to compute a decision threshold. In the second module, global parameters of a signature are the inputs of a two-classes neural network trained for each signer on both the genuine and {"}other{"} signatures (genuine signatures of other signers). Fusion of the scores given by these two experts through a Support Vector Machine (SVM), allows improving the results over those of each module, on Philips' Database.",

author = "Marc Fuentes and Sonia Garcia-Salicetti and Bernadette Dorizzi",

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doi = "10.1109/IWFHR.2002.1030918",

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note = "8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002 ; Conference date: 06-08-2002 Through 08-08-2002",

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Fuentes, M, Garcia-Salicetti, S & Dorizzi, B 2002, On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine. Dans Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002. Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR, IEEE Computer Society, p. 253-258, 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002, Ontario, ON, Canada, 6/08/02. https://doi.org/10.1109/IWFHR.2002.1030918

On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine. / Fuentes, Marc; Garcia-Salicetti, Sonia; Dorizzi, Bernadette.
Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002. IEEE Computer Society, 2002. p. 253-258 (Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

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N2 - We propose in this work to perform on-line signature verification by the fusion of two complementary verification modules. The first one considers a signature as a sequence of points and models the genuine signatures of a given signer by a Hidden Markov Model (HMM). Forgeries are used to compute a decision threshold. In the second module, global parameters of a signature are the inputs of a two-classes neural network trained for each signer on both the genuine and "other" signatures (genuine signatures of other signers). Fusion of the scores given by these two experts through a Support Vector Machine (SVM), allows improving the results over those of each module, on Philips' Database.

AB - We propose in this work to perform on-line signature verification by the fusion of two complementary verification modules. The first one considers a signature as a sequence of points and models the genuine signatures of a given signer by a Hidden Markov Model (HMM). Forgeries are used to compute a decision threshold. In the second module, global parameters of a signature are the inputs of a two-classes neural network trained for each signer on both the genuine and "other" signatures (genuine signatures of other signers). Fusion of the scores given by these two experts through a Support Vector Machine (SVM), allows improving the results over those of each module, on Philips' Database.

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Fuentes M, Garcia-Salicetti S, Dorizzi B. On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine. Dans Proceedings - 8th International Workshop on Frontiers in Handwriting Recognition, IWFHR 2002. IEEE Computer Society. 2002. p. 253-258. (Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR). doi: 10.1109/IWFHR.2002.1030918

On line signature verification: Fusion of a Hidden Markov Model and a neural network via a support vector machine

Résumé

Série de publications

Une conférence

Accès au document

Autres fichiers et liens

Empreinte digitale

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