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2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies
Position Invariant Optical Character Recognition through Symmetry Features
Trivandrum, Kerala, India
December 28-December 29
ISBN: 978-0-7695-3915-7
ASCII Text
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Sam Holland, Richard Neville, "Position Invariant Optical Character Recognition through Symmetry Features," Advances in Computing, Control, and Telecommunication Technologies, International Conference on, pp. 313-315, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, 2009.
 
 
BibTex
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@article{ 10.1109/ACT.2009.84,
author = {Sam Holland and Richard Neville},
title = {Position Invariant Optical Character Recognition through Symmetry Features},
journal ={Advances in Computing, Control, and Telecommunication Technologies, International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3915-7},
pages = {313-315},
doi = {http://doi.ieeecomputersociety.org/10.1109/ACT.2009.84},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Advances in Computing, Control, and Telecommunication Technologies, International Conference on
TI - Position Invariant Optical Character Recognition through Symmetry Features
SN - 978-0-7695-3915-7
SP313
EP315
A1 - Sam Holland,
A1 - Richard Neville,
PY - 2009
KW - position
KW - invariance
KW - probabilistic
KW - neural
KW - network
KW - symmetry
KW - generalized
KW - transform
KW - character
KW - recognition
VL - 0
JA - Advances in Computing, Control, and Telecommunication Technologies, International Conference on
ER -
 
We propose an effective method to achieve position invariance in the application of Optical Character Recognition (OCR). We normalise the position of all inputs based on their symmetry features. The Generalized Symmetry Transform (GST) is used to determine the symmetry features prior to classification by a Probabilistic Neural Network (PNN). We used the United States Postal Service (USPS) data set to measure performance.
Index Terms:
position, invariance, probabilistic, neural, network, symmetry, generalized, transform, character, recognition
Citation:
Sam Holland, Richard Neville, "Position Invariant Optical Character Recognition through Symmetry Features," act, pp.313-315, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, 2009
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