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Using Box Approach in Persian Handwritten Digits Recognition
by
Omid Rashnodi,
Hedieh Sajedi,
Mohammad Saniee Abadeh
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 32 - Number 3 |
| Year of Publication: 2011 |
| Authors: Omid Rashnodi, Hedieh Sajedi, Mohammad Saniee Abadeh |
10.5120/3882-5428
|
Omid Rashnodi, Hedieh Sajedi, Mohammad Saniee Abadeh . Using Box Approach in Persian Handwritten Digits Recognition. International Journal of Computer Applications. 32, 3 ( October 2011), 1-8. DOI=10.5120/3882-5428
@article{
10.5120/3882-5428,
author = {
Omid Rashnodi,
Hedieh Sajedi,
Mohammad Saniee Abadeh
},
title = { Using Box Approach in Persian Handwritten Digits Recognition },
journal = {
International Journal of Computer Applications
},
issue_date = { October 2011 },
volume = { 32 },
number = { 3 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = {
1-8
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume32/number3/3882-5428/
},
doi = { 10.5120/3882-5428 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:09.832340+05:30
%A Omid Rashnodi
%A Hedieh Sajedi
%A Mohammad Saniee Abadeh
%T Using Box Approach in Persian Handwritten Digits Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 3
%P 1-8
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper, appropriate feature set based on the box approach has been proposed to achieve higher recognition accuracy and decreasing the recognition time of Persian numerals. In classification phase, support vector machine (SVM) with linear kernel has been employed as the classifier. Feature sets consists of 163 dimensions, which are the average angle and distance pixels which are equal to one in each box the box approach. The scheme has been evaluated on 60,000 handwritten samples of Persian numerals. Using 60,000 samples for training, scheme was tested on other 20,000 samples and 98.945% correct recognition rate was obtained.
References
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Index Terms
Computer Science
Information Sciences
Keywords