|Title:||Towards an automatic on-line signature verifier using only one reference per signer||Authors:||Diaz, Moises
Ferrer, Miguel A.
|UNESCO Clasification:||3307 Tecnología electrónica||Keywords:||Hidden Markov models
Integrated circuit modeling
|Issue Date:||2015||Journal:||Proceedings of the International Conference on Document Analysis and Recognition, ICDAR||Conference:||13th IAPR International Conference on Document Analysis and Recognition (ICDAR)
13th International Conference on Document Analysis and Recognition, ICDAR 2015
|Abstract:||What can be done with only one enrolled real hand-written 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.||URI:||http://hdl.handle.net/10553/45487||ISBN:||9781479918058||ISSN:||1520-5363||DOI:||10.1109/ICDAR.2015.7333838||Source:||Proceedings of the International Conference on Document Analysis and Recognition, ICDAR[ISSN 1520-5363],v. 2015-November (7333838), p. 631-635|
|Appears in Collections:||Actas de congresos|
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