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Eighth International Conference on Document Analysis and Recognition (ICDAR'05)
On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems
Seoul, Korea
August 31-September 01
ISBN: 0-7695-2420-6
ASCII Text
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Harold Mouchere, Eric Anquetil, Nicolas Ragot, "On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems," Document Analysis and Recognition, International Conference on, pp. 1075, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/ICDAR.2005.176,
author = {Harold Mouchere and Eric Anquetil and Nicolas Ragot},
title = {On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems},
journal ={Document Analysis and Recognition, International Conference on},
volume = {0},
year = {2005},
issn = {1520-5263},
pages = {1075},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2005.176},
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 - On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems
SN - 1520-5263
SP
EP
A1 - Harold Mouchere,
A1 - Eric Anquetil,
A1 - Nicolas Ragot,
PY - 2005
KW - null
VL - 0
JA - Document Analysis and Recognition, International Conference on
ER -
 
Harold Mouchere, IRISA, INSA de Rennes, CEDEX, France
Eric Anquetil, IRISA, INSA de Rennes, CEDEX, France
Nicolas Ragot, IRISA, INSA de Rennes, CEDEX, France
We present an automatic on-line adaptation mechanism to the writer?s handwriting style for the recognition of isolated handwritten characters. The classifier is based on a Fuzzy Inference System (FIS). This FIS is composed of fuzzy prototypes which represent the intrinsic properties of the classes and it uses numeric conclusions. The proposed adaptation mechanism affects both the conclusions of the rules and the fuzzy prototypes of the premises by recentering and re-shaping them. Doing so, the FIS is automatically fitted to the handwriting style of the writer that is currently using the system. This adaptation mechanism has been tested with 8 different writers. The results show the adaptation mechanism is able to improve the recognition rate from 88% to 98.2% in average for the 26 Latin letters.
Citation:
Harold Mouchere, Eric Anquetil, Nicolas Ragot, "On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems," icdar, pp.1075, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
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