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An Approach to Handwriting Recognition using Back-Propagation Neural Network

by Pijush Chakraborty, Paramita Sarkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 13
Year of Publication: 2013
Authors: Pijush Chakraborty, Paramita Sarkar
10.5120/11637-7117

Pijush Chakraborty, Paramita Sarkar . An Approach to Handwriting Recognition using Back-Propagation Neural Network. International Journal of Computer Applications. 68, 13 ( April 2013), 6-12. DOI=10.5120/11637-7117

@article{ 10.5120/11637-7117,
author = { Pijush Chakraborty, Paramita Sarkar },
title = { An Approach to Handwriting Recognition using Back-Propagation Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 13 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number13/11637-7117/ },
doi = { 10.5120/11637-7117 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:43.418933+05:30
%A Pijush Chakraborty
%A Paramita Sarkar
%T An Approach to Handwriting Recognition using Back-Propagation Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 13
%P 6-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwriting Recognition is an important topic in Computer Science. In this paper a procedure is presented to identify characters that are drawn using stylus with the help of Back-Propagation Neural Network. The paper describes the entire procedure from feature extraction to the training of the network. Feature extraction includes pixel grabbing, finding character bounds and down-sampling of the image to 7*5 pixel size. The neural network is trained by supervised learning which includes error calculation using back-propagation approach. After the training is completed the network is ready to identify characters that are drawn in the computer. This same approach given in this paper can be extended to recognize handwritten documents and also for recognizing multilingual characters.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Handwriting Recognition Back-propagation Feed-forward Neural Network Pattern Recognition

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