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Reseach Article

A Survey on Handwritten Character Recognition Techniques for Various Indian Languages

by Krupa Dholakia
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 1
Year of Publication: 2015
Authors: Krupa Dholakia
10.5120/20114-2159

Krupa Dholakia . A Survey on Handwritten Character Recognition Techniques for Various Indian Languages. International Journal of Computer Applications. 115, 1 ( April 2015), 17-21. DOI=10.5120/20114-2159

@article{ 10.5120/20114-2159,
author = { Krupa Dholakia },
title = { A Survey on Handwritten Character Recognition Techniques for Various Indian Languages },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 1 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number1/20114-2159/ },
doi = { 10.5120/20114-2159 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:53:36.548670+05:30
%A Krupa Dholakia
%T A Survey on Handwritten Character Recognition Techniques for Various Indian Languages
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 1
%P 17-21
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwritten character recognition is always an interesting area of pattern recognition for research in the field of image processing. Many researchers have presented their work in this area and still research is undergoing to achieve high accuracy. This paper is mainly concerned for the people who are working on the character recognition and review of work to recognize handwritten character for various Indian languages. The objective of this paper is to describe the set of preprocessing, segmentation, feature extraction and classification techniques.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Handwritten character Preprocessing Segmentation Feature extraction Classification.