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Eighth International Conference on Document Analysis and Recognition (ICDAR'05)
Benefit of multiclassifier systems for Arabic handwritten words recognition
Seoul, Korea
August 31-September 01
ISBN: 0-7695-2420-6
ASCII Text
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FARAH Nadir, ENNAJI Abdelatif, KHADIR Tarek, SELLAMI Mokhtar, "Benefit of multiclassifier systems for Arabic handwritten words recognition," Document Analysis and Recognition, International Conference on, pp. 222-226, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICDAR.2005.57,
author = {FARAH Nadir and ENNAJI Abdelatif and KHADIR Tarek and SELLAMI Mokhtar},
title = {Benefit of multiclassifier systems for Arabic handwritten words recognition},
journal ={Document Analysis and Recognition, International Conference on},
volume = {0},
year = {2005},
issn = {1520-5263},
pages = {222-226},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2005.57},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Document Analysis and Recognition, International Conference on
TI - Benefit of multiclassifier systems for Arabic handwritten words recognition
SN - 1520-5263
SP222
EP226
A1 - FARAH Nadir,
A1 - ENNAJI Abdelatif,
A1 - KHADIR Tarek,
A1 - SELLAMI Mokhtar,
PY - 2005
KW - null
VL - 0
JA - Document Analysis and Recognition, International Conference on
ER -
 
FARAH Nadir, Universite Badji Mokhtar - Annaba- BP, France
ENNAJI Abdelatif, Universite Badji Mokhtar - Annaba- BP, France
KHADIR Tarek, Universite Badji Mokhtar - Annaba- BP, France
SELLAMI Mokhtar, Universite Badji Mokhtar - Annaba- BP, France

In order to improve the results of single classijiers, the study of multiple classifier systems has become an area of intensive research in pattern recognition. In this paper, two types of features are fed to a number of Artificial Neural Networks (ANN).

Then, their respective responses are combined for the recognition of handwritten Arabic literal words. Different parallel combination schemes are presented, including the use of an ANN as a meta classrfier. Their results are then com~ared and conclusions on the most suitable approach are drawn.

Citation:
FARAH Nadir, ENNAJI Abdelatif, KHADIR Tarek, SELLAMI Mokhtar, "Benefit of multiclassifier systems for Arabic handwritten words recognition," icdar, pp.222-226, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
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