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Reseach Article

Recognition of Gujarati Numerals using Hybrid Approach and Neural Networks

Published on May 2013 by Baheti M. J., Kale K. V.
International Conference on Recent Trends in Engineering and Technology 2013
Foundation of Computer Science USA
ICRTET - Number 5
May 2013
Authors: Baheti M. J., Kale K. V.
b849d846-3700-4dce-82c9-8d807b6da2d1

Baheti M. J., Kale K. V. . Recognition of Gujarati Numerals using Hybrid Approach and Neural Networks. International Conference on Recent Trends in Engineering and Technology 2013. ICRTET, 5 (May 2013), 7-12.

@article{
author = { Baheti M. J., Kale K. V. },
title = { Recognition of Gujarati Numerals using Hybrid Approach and Neural Networks },
journal = { International Conference on Recent Trends in Engineering and Technology 2013 },
issue_date = { May 2013 },
volume = { ICRTET },
number = { 5 },
month = { May },
year = { 2013 },
issn = 0975-8887,
pages = { 7-12 },
numpages = 6,
url = { /proceedings/icrtet/number5/11791-1356/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Engineering and Technology 2013
%A Baheti M. J.
%A Kale K. V.
%T Recognition of Gujarati Numerals using Hybrid Approach and Neural Networks
%J International Conference on Recent Trends in Engineering and Technology 2013
%@ 0975-8887
%V ICRTET
%N 5
%P 7-12
%D 2013
%I International Journal of Computer Applications
Abstract

The handwriting recognition is the scheme of converting text symbolized in the spatial form of graphical symbols into its figurative depiction. Handwritten characters have been the most accredited technique of collecting, storing and transmitting information all the way through the centuries. To give the proper ability to the machine it requires studying the image-form of data which forms a special pattern to be interpreted. Designing and building machines that can recognize patterns remains one of the thrust areas in the field of computer sciences. A lot of work has been done in this field, but still the problem is not answered in its full density. A good text recognizer has many commercial and practical applications, e. g. from finding data in digitized book to computerization of any organization, like post office, which involve manual task of interpreting text. In this paper, we have presented a hybrid approach for recognition of Gujarati handwritten numerals using neural networks as classifier and achieved a good recognition rate for noisy numerals.

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Index Terms

Computer Science
Information Sciences

Keywords

Gujarati Numerals Neural Networks Handwriting Recognition