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Handwritten Marathi Consonants Recognition using Multilevel Classification

Published on August 2016 by C. H. Patil, S. M. Mali
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National Conference on Digital Image and Signal Processing
Foundation of Computer Science USA
NCDISP2016 - Number 2
August 2016
Authors: C. H. Patil, S. M. Mali
89897bb2-7a74-467c-88b6-41e4651842f7

C. H. Patil, S. M. Mali . Handwritten Marathi Consonants Recognition using Multilevel Classification. National Conference on Digital Image and Signal Processing. NCDISP2016, 2 (August 2016), 21-30.

@article{
author = { C. H. Patil, S. M. Mali },
title = { Handwritten Marathi Consonants Recognition using Multilevel Classification },
journal = { National Conference on Digital Image and Signal Processing },
issue_date = { August 2016 },
volume = { NCDISP2016 },
number = { 2 },
month = { August },
year = { 2016 },
issn = 0975-8887,
pages = { 21-30 },
numpages = 10,
url = { /proceedings/ncdisp2016/number2/25856-1641/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Digital Image and Signal Processing
%A C. H. Patil
%A S. M. Mali
%T Handwritten Marathi Consonants Recognition using Multilevel Classification
%J National Conference on Digital Image and Signal Processing
%@ 0975-8887
%V NCDISP2016
%N 2
%P 21-30
%D 2016
%I International Journal of Computer Applications
Abstract

This paper presents approach for the recognition of handwritten Marathi consonants. In order to recognize handwritten Marathi consonants, a database of handwritten Marathi consonants is developed to carry recognition experiments. Problem of handwritten Marathi consonant recognition is simplified using multilevel classificationwhich improves recognition rate. Total 36 Marathi consonants are transformed using instance simplification technique into six sub classesdepending on special property of consonants. Suitable features are extracted from different sub classes and further classification is carried out using SVM and k-NN classifiers. We have used database of 7920 characters for testing and found recognition accuracy 78. 27% using SVM classifier and 73. 29% using k-NN classifier.

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Index Terms

Computer Science
Information Sciences

Keywords

Marathi Consonents Multilevel Classification Svm Knn Pattern Recognition.