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Handwritten Devanagari Lipi using Support Vector Machine

by Shailendra Kumar Shrivastava, Pratibha Chaurasia
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 20
Year of Publication: 2012
Authors: Shailendra Kumar Shrivastava, Pratibha Chaurasia
10.5120/6220-8785

Shailendra Kumar Shrivastava, Pratibha Chaurasia . Handwritten Devanagari Lipi using Support Vector Machine. International Journal of Computer Applications. 43, 20 ( April 2012), 20-25. DOI=10.5120/6220-8785

@article{ 10.5120/6220-8785,
author = { Shailendra Kumar Shrivastava, Pratibha Chaurasia },
title = { Handwritten Devanagari Lipi using Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 20 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number20/6220-8785/ },
doi = { 10.5120/6220-8785 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:55.047159+05:30
%A Shailendra Kumar Shrivastava
%A Pratibha Chaurasia
%T Handwritten Devanagari Lipi using Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 20
%P 20-25
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The handwritten recognition is a one of the basic biometric recognition technique. Different technique and features are used for the faithful recognition characters. In this paper we have proposed a SVM (support vector machine) based technique for Devanagari character recognition. The Devanagari characters have very correlation to each other. This feature of the Devanagari lipi make difficult to faithful recognition. The energy features of segment characters are used for the classification. The more no. of segmentation improves the recognition rate. The different recognition rates with no. of segment are used in this paper. The recognition rate is also developed on the kernel of SVM. The result of different kernel is also given in this paper.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Support Vector Machine Devnagiri Lipi Recognition Pre-processing Feature Extraction Classification Post Processing

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