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Reseach Article

Article:A Study on the Effect of Outliers in Devanagari Character Recognition

by O.V. Ramana Murthy, M. Hanmandlu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 10
Year of Publication: 2011
Authors: O.V. Ramana Murthy, M. Hanmandlu
10.5120/3937-5183

O.V. Ramana Murthy, M. Hanmandlu . Article:A Study on the Effect of Outliers in Devanagari Character Recognition. International Journal of Computer Applications. 32, 10 ( October 2011), 10-17. DOI=10.5120/3937-5183

@article{ 10.5120/3937-5183,
author = { O.V. Ramana Murthy, M. Hanmandlu },
title = { Article:A Study on the Effect of Outliers in Devanagari Character Recognition },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 10 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 10-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number10/3937-5183/ },
doi = { 10.5120/3937-5183 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:55.215348+05:30
%A O.V. Ramana Murthy
%A M. Hanmandlu
%T Article:A Study on the Effect of Outliers in Devanagari Character Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 10
%P 10-17
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Devanagari is the basic script for many languages of India, including their National language Hindi. Unlike the Latin script used for the English language, it does not have upper case or lowercase. It has only one case of writing. Moreover each alphabet contains more curves than straight lines. Hence handwritten Devanagari character recognition is a challenging task. To capture different handwritten styles of each alphabet, different approaches have been proposed. In this work, we investigate a simple filtering technique on the features. Support Vector Machine (SVM) was used as classifier. It has been applied on two benchmark Devanagari databases and results show an improvement of as much as 5-10%. This improvement is found to be consistent with different sizes of the database. It was studied on pixel density features and GIST features separately. GIST features were found to be more effective and like having the potency of self-containing filtering.

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Index Terms

Computer Science
Information Sciences

Keywords

Outliers Support Vector Machine Character recognition pixel density features GIST features