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Performance Comparison of Devanagari Handwritten Numerals Recognition
by
Mahesh Jangid Kartar Singh,
Renu Dhir,
Rajneesh Rani
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 22 - Number 1 |
| Year of Publication: 2011 |
| Authors: Mahesh Jangid Kartar Singh, Renu Dhir, Rajneesh Rani |
10.5120/2551-3496
|
Mahesh Jangid Kartar Singh, Renu Dhir, Rajneesh Rani . Performance Comparison of Devanagari Handwritten Numerals Recognition. International Journal of Computer Applications. 22, 1 ( May 2011), 1-6. DOI=10.5120/2551-3496
@article{
10.5120/2551-3496,
author = {
Mahesh Jangid Kartar Singh,
Renu Dhir,
Rajneesh Rani
},
title = { Performance Comparison of Devanagari Handwritten Numerals Recognition },
journal = {
International Journal of Computer Applications
},
issue_date = { May 2011 },
volume = { 22 },
number = { 1 },
month = { May },
year = { 2011 },
issn = { 0975-8887 },
pages = {
1-6
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume22/number1/2551-3496/
},
doi = { 10.5120/2551-3496 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:08:15.122003+05:30
%A Mahesh Jangid Kartar Singh
%A Renu Dhir
%A Rajneesh Rani
%T Performance Comparison of Devanagari Handwritten Numerals Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 22
%N 1
%P 1-6
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper an automatic recognition system for isolated Handwritten Devanagari Numerals is proposed and compared the recognition rate with different classifier. We presented a feature extraction technique based on recursive subdivision of the character image so that the resulting sub-images at each iteration have balanced numbers of foreground pixels as possible. Database, provided by Indian Statistical Institute, Kolkata, have 22547 grey scale images written by 1049 persons and obtained 98.98% highest accuracy with SVM classifier. Results are compared with KNN and Quadratic classifier.
References
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Keywords