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2015 13th International Conference on Document Analysis and Recognition (ICDAR)

DOI: 10.1109/icdar.2015.7333838

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Towards an Automatic On-Line Signature Verifier Using Only One Reference Per Signer

Proceedings article published in 2015 by Moises Diaz, Andreas Fischer, Réjean Plamondon, Miguel A. Ferrer ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

What can be done with only one enrolled real handwritten signature in Automatic Signature Verification (ASV)? Using 5 or 10 signatures for training is the most common case to evaluate ASV. In the scarcely addressed case of only one available signature for training, we propose to use modified duplicates. Our novel technique relies on a fully neuromuscular representation of the signatures based on the Kinematic Theory of rapid human movements and its Sigma-Lognormal model. This way, a real on-line signature is converted into the Sigma-Lognormal model domain. The model parameters are then varied to generate new duplicated signatures.