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A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 49 - Number 8
Year of Publication: 2012
|
10.5120/7648-0739 |
Abroug Ben I Abdelghani and Essoukri Ben N Amara. Article: A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation. International Journal of Computer Applications 49(8):29-34, July 2012. Full text available. BibTeX
@article{key:article,
author = {I. Abroug Ben Abdelghani and N. Essoukri Ben Amara},
title = {Article: A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {49},
number = {8},
pages = {29-34},
month = {July},
note = {Full text available}
}
Abstract
This paper deals with offline handwriting signature verification. We propose a planar neuronal model of signature image. Planar models are generally based on delimiting homogenous zones of images; we propose in this paper an automatic segmentation approach into bands of signature images. Signature image is modeled by a planar neuronal model with horizontal secondary models and a vertical principal model. The proposed method has been tested on two databases. The first is the one we have collected; it includes 6000 signatures corresponding to 60 writers. The second is the public GPDS-300 database including 16200 signature corresponding to 300 persons. The achieved results are promising.
References
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