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Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns

by Abdul Rahiman M, Aswathy Shajan, Rajasree M S
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 11
Year of Publication: 2010
Authors: Abdul Rahiman M, Aswathy Shajan, Rajasree M S
10.5120/1250-1664

Abdul Rahiman M, Aswathy Shajan, Rajasree M S . Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns. International Journal of Computer Applications. 8, 11 ( October 2010), 19-23. DOI=10.5120/1250-1664

@article{ 10.5120/1250-1664,
author = { Abdul Rahiman M, Aswathy Shajan, Rajasree M S },
title = { Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 11 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number11/1250-1664/ },
doi = { 10.5120/1250-1664 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:05.527472+05:30
%A Abdul Rahiman M
%A Aswathy Shajan
%A Rajasree M S
%T Article:An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 11
%P 19-23
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An efficient and robust algorithm for recognition of handwritten Malayalam characters is proposed in this study. Malayalam, also known as Kairali, is one of the four major Dravidian languages of Southern India. It consists of basically 15 vowels and 36 consonants. The existence of lot of their combinations and connected characters, the recognition poses a gargantuan challenge in front of us. Till now Malayalam lacks an efficient OCR which meets all conditions. The intertwined characters are very complex owing to the non-adherent styles in which they may be presented. Here we propose an algorithm which uses the inveterate characteristic features to recognize these characters with perceptive accuracy by utilizing the intensity variations in the way in which they may be written. This algorithm recognizes the antediluvian script of Malayalam characters which are connected in nature. Here the input is a 24-bit bmp image which can be enscribed using the Light pen. The output is editable version of the recognized Malayalam characters. In our study we have classified the connected characters into 3 categories. The algorithm is tested for 3 sets of samples ranging 402 letters in noiseless environment and produces accuracy of 92%.

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Index Terms

Computer Science
Information Sciences

Keywords

Malayalam Optical Character recognition Feature Extraction Connected character Intensity Variations HLH Patterns

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