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A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation
by
I. Abroug Ben Abdelghani,
N. Essoukri Ben Amara
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 49 - Number 8 |
| Year of Publication: 2012 |
| Authors: I. Abroug Ben Abdelghani, N. Essoukri Ben Amara |
10.5120/7648-0739
|
I. Abroug Ben Abdelghani, N. Essoukri Ben Amara . A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation. International Journal of Computer Applications. 49, 8 ( July 2012), 29-34. DOI=10.5120/7648-0739
@article{
10.5120/7648-0739,
author = {
I. Abroug Ben Abdelghani,
N. Essoukri Ben Amara
},
title = { A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation },
journal = {
International Journal of Computer Applications
},
issue_date = { July 2012 },
volume = { 49 },
number = { 8 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = {
29-34
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume49/number8/7648-0739/
},
doi = { 10.5120/7648-0739 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:45:45.166649+05:30
%A I. Abroug Ben Abdelghani
%A N. Essoukri Ben Amara
%T A Neuronal Planar Modeling for Handwriting Signature based on Automatic Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 8
%P 29-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
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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Index Terms
Computer Science
Information Sciences
Keywords