Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/45497
Title: Cognitive Inspired Model to Generate Duplicated Static Signature Images
Authors: Diaz-Cabrera, Moises 
Ferrer, Miguel A. 
Morales, Aythami
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Hidden Markov models
Signature verification ,
Biometric recognition
Issue Date: 2014
Journal: Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Conference: 14th International Conference on Frontiers in Handwriting Recognition (ICFHR) 
14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 
Abstract: The handwriting signature is one of the most popular behavioral biometric traits for person recognition. Such recognition systems capture the personal signing behaviour and its variability based on a limited number of enrolled signatures. In this paper a cognitive inspired model based on motor equivalence theory is developed to duplicate off-line signatures from one real on-line seed. This model achieves duplicated signatures with a natural variability. It is validated with an off-line signature verifier based on texture features and a SVM classifier. The results manifest the complementarity of the duplicated signatures and the utility of the model.
URI: http://hdl.handle.net/10553/45497
ISBN: 9781479943340
ISSN: 2167-6445
DOI: 10.1109/ICFHR.2014.18
Source: Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR[ISSN 2167-6445],v. 2014-December (6980997), p. 61-66
Appears in Collections:Actas de congresos
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