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7th IEEE International Conference on Computer and Information Technology (CIT 2007)
Using Contour Analysis to Improve Feature Extraction in Thai Handwritten Character Recognition Systems
Aizu-Wakamatsu City, Fukushima, Japan
October 16-October 19
ISBN: 0-7695-2983-6
ASCII Text
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Jarernsri L. Mitrpanont, Urairat Limkonglap, "Using Contour Analysis to Improve Feature Extraction in Thai Handwritten Character Recognition Systems," Computer and Information Technology, International Conference on, pp. 668-673, 7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007.
 
 
BibTex
x
 
@article{ 10.1109/CIT.2007.103,
author = {Jarernsri L. Mitrpanont and Urairat Limkonglap},
title = {Using Contour Analysis to Improve Feature Extraction in Thai Handwritten Character Recognition Systems},
journal ={Computer and Information Technology, International Conference on},
volume = {0},
year = {2007},
isbn = {0-7695-2983-6},
pages = {668-673},
doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2007.103},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer and Information Technology, International Conference on
TI - Using Contour Analysis to Improve Feature Extraction in Thai Handwritten Character Recognition Systems
SN - 0-7695-2983-6
SP668
EP673
A1 - Jarernsri L. Mitrpanont,
A1 - Urairat Limkonglap,
PY - 2007
VL - 0
JA - Computer and Information Technology, International Conference on
ER -
 
Jarernsri L. Mitrpanont, Mahidol University, Bangkok 10400, THAILAND
Urairat Limkonglap, Mahidol University, Bangkok 10400, THAILAND
This research proposes an approach to the analysis of contour characteristics for the feature extraction process of an off-line Thai handwritten character recognition system (THW-CR). The system aims at increasing the accuracy of both feature extraction rate and character recognition rate. We introduce the contour to capture the movement of features. The propose modules are the feature representation and the feature conflict resolution rules. With our proposed approach, the experiment shows the results increase reasonably. The maximum Feature Extraction Rate (FER) reached 97.73%. Meanwhile, the highest Character Recognition Rate (CRR) reached 95.35%. Additionally, the result of the overall evaluation showed that the THW-CR system generated reliable results for improving the accuracy of the feature extraction rate and the character recognition rate compared with the previous research by 3.62% and 8.33%, respectively.
Citation:
Jarernsri L. Mitrpanont, Urairat Limkonglap, "Using Contour Analysis to Improve Feature Extraction in Thai Handwritten Character Recognition Systems," cit, pp.668-673, 7th IEEE International Conference on Computer and Information Technology (CIT 2007), 2007
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