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Reseach Article

Century Identification and Recognition of Ancient Tamil Character Recognition

by S.Rajakumar, Dr.V.Subbiah Bharathi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 26 - Number 4
Year of Publication: 2011
Authors: S.Rajakumar, Dr.V.Subbiah Bharathi
10.5120/3090-4237

S.Rajakumar, Dr.V.Subbiah Bharathi . Century Identification and Recognition of Ancient Tamil Character Recognition. International Journal of Computer Applications. 26, 4 ( July 2011), 32-35. DOI=10.5120/3090-4237

@article{ 10.5120/3090-4237,
author = { S.Rajakumar, Dr.V.Subbiah Bharathi },
title = { Century Identification and Recognition of Ancient Tamil Character Recognition },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 26 },
number = { 4 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 32-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume26/number4/3090-4237/ },
doi = { 10.5120/3090-4237 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:58.030952+05:30
%A S.Rajakumar
%A Dr.V.Subbiah Bharathi
%T Century Identification and Recognition of Ancient Tamil Character Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 26
%N 4
%P 32-35
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recognition of ancient Tamil hand written characters from inscriptions is difficult. Ancient Tamil characters are different from current century’s Tamil character. This paper concentrates on the century identification of ancient Tamil characters and converting them into current century’s form using MATLAB. In this paper, a method for recognizing Tamil characters from stone inscriptions, called the contour-let transform, which has been recently introduced, is adopted. From previous research works, it’s noticed that Wavelet transforms are not capable of reconstructing curved images perfectly. The contour-let transform offers a solution to remedy to this insufficiency. Contour-let transform is a 3D approach technique whereas wavelet transform is a 2D technique. The characters from the input image are recognized through clustering mechanism. Further the noise present in the image is removed by fuzzy median filters. Neural networks are employed to train the image and compare the data with the current century’s character. Hence a more accurate recognition of Ancient Tamil characters from stone inscriptions is obtained.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Contour-let transform Wavelet transform Fuzzy median filters Neural network Clustering