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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1
HMM-Based Online Handwriting Recognition System for Telugu Symbols
Curitiba, Parana, Brazil
September 23-September 26
ISBN: 0-7695-2822-8
ASCII Text
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V. Babu, L. Prasanth, R. Sharma, G.V. Rao, A. Bharath, "HMM-Based Online Handwriting Recognition System for Telugu Symbols," Document Analysis and Recognition, International Conference on, vol. 1, pp. 63-67, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007.
 
 
BibTex
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@article{ 10.1109/ICDAR.2007.132,
author = {V. Babu and L. Prasanth and R. Sharma and G.V. Rao and A. Bharath},
title = {HMM-Based Online Handwriting Recognition System for Telugu Symbols},
journal ={Document Analysis and Recognition, International Conference on},
volume = {1},
year = {2007},
issn = {1520-5363},
pages = {63-67},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.132},
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 - HMM-Based Online Handwriting Recognition System for Telugu Symbols
SN - 1520-5363
SP63
EP67
A1 - V. Babu,
A1 - L. Prasanth,
A1 - R. Sharma,
A1 - G.V. Rao,
A1 - A. Bharath,
PY - 2007
VL - 1
JA - Document Analysis and Recognition, International Conference on
ER -
 
V. Babu, Sri Sathya Sai Institute of Higher Learning, India
L. Prasanth, Sri Sathya Sai Institute of Higher Learning, India
R. Sharma, Sri Sathya Sai Institute of Higher Learning, India
G.V. Rao, Sri Sathya Sai Institute of Higher Learning, India
A. Bharath, Hewlett-Packard Labs
In this paper we present an online handwritten symbol recognition system for Telugu, a widely spoken language in India. The system is based on Hidden Markov Models (HMM) and uses a combination of time-domain and frequency-domain features. The system gives top-1 accuracy of 91.6% and top-5 accuracy of 98.7% on a dataset containing 29,158 train samples and 9,235 test samples. We also introduce a cost-effective and natural data collection procedure based on ACECAD? Digimemo? and describe its usage in building a Telugu handwriting dataset.
Citation:
V. Babu, L. Prasanth, R. Sharma, G.V. Rao, A. Bharath, "HMM-Based Online Handwriting Recognition System for Telugu Symbols," icdar, vol. 1, pp.63-67, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007
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