loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06)
A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps
Arlington, Virginia
November 13-November 15
ISBN: 0-7695-2728-0
ASCII Text
x 
 
Alex Cronin, John A. Fitzgerald, Tahar Kechadi, "A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps," Tools with Artificial Intelligence, IEEE International Conference on, pp. 693-700, 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICTAI.2006.13,
author = {Alex Cronin and John A. Fitzgerald and Tahar Kechadi},
title = {A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {0},
year = {2006},
issn = {1082-3409},
pages = {693-700},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2006.13},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps
SN - 1082-3409
SP693
EP700
A1 - Alex Cronin,
A1 - John A. Fitzgerald,
A1 - Tahar Kechadi,
PY - 2006
KW - Handwriting Recognition
KW - Self-Organizing Maps
KW - Fuzzy Logic
KW - Multiple Classifier Systems.
VL - 0
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
Alex Cronin, University College Dublin, Ireland
John A. Fitzgerald, University College Dublin, Ireland
Tahar Kechadi, University College Dublin, Ireland
In this paper we present a hybrid approach to handwritten symbol recognition based on two different methods and principles. A fuzzy rules based recogniser and a Self-Organizing Map recogniser are combined to form our hybrid system. These two systems complement each other well, firstly because their feature extraction techniques differ greatly, and secondly because one is a model-based and the other is a discriminative classifier. Each system generates a ranked list of outputs with associated confidence values, and these outputs are combined to produce a single result. The approach has achieved high recognition rates in testing on digits and lowercase characters from the UNIPEN database.
Index Terms:
Handwriting Recognition, Self-Organizing Maps, Fuzzy Logic, Multiple Classifier Systems.
Citation:
Alex Cronin, John A. Fitzgerald, Tahar Kechadi, "A Hybrid Recogniser for Handwritten Symbols Based on Fuzzy Logic and Self-Organizing Maps," ictai, pp.693-700, 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06), 2006
Usage of this product signifies your acceptance of the Terms of Use.