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Automatic Recognition of Handwritten Bengali Broken Characters (BBC): Simulating Human Pattern Matching

by Manas Ranjan Nayak, Saswat Nayak, Yetirajam Manas, Sangeeta Bhanja Chaudhuri, Subhagata Chattopadhyay
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 9
Year of Publication: 2012
Authors: Manas Ranjan Nayak, Saswat Nayak, Yetirajam Manas, Sangeeta Bhanja Chaudhuri, Subhagata Chattopadhyay
10.5120/9578-4055

Manas Ranjan Nayak, Saswat Nayak, Yetirajam Manas, Sangeeta Bhanja Chaudhuri, Subhagata Chattopadhyay . Automatic Recognition of Handwritten Bengali Broken Characters (BBC): Simulating Human Pattern Matching. International Journal of Computer Applications. 59, 9 ( December 2012), 27-32. DOI=10.5120/9578-4055

@article{ 10.5120/9578-4055,
author = { Manas Ranjan Nayak, Saswat Nayak, Yetirajam Manas, Sangeeta Bhanja Chaudhuri, Subhagata Chattopadhyay },
title = { Automatic Recognition of Handwritten Bengali Broken Characters (BBC): Simulating Human Pattern Matching },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 9 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 27-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number9/9578-4055/ },
doi = { 10.5120/9578-4055 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:03:45.346667+05:30
%A Manas Ranjan Nayak
%A Saswat Nayak
%A Yetirajam Manas
%A Sangeeta Bhanja Chaudhuri
%A Subhagata Chattopadhyay
%T Automatic Recognition of Handwritten Bengali Broken Characters (BBC): Simulating Human Pattern Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 9
%P 27-32
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an automatic detection of handwritten Bengali Broken Characters (BBC) using a feed forward neural network (FFNN). It simulates the Human Visual System (HVS) the way human eye matches the patterns of the broken characters to a meaningful character and identifies it. Here the challenge is to detect and retrieve handwritten character which has been distorted up to 90%. The database consists of fifty bangle characters, each with twenty samples. Each character is presented as an image, which has been preprocessed, segmented and the features are then extracted. A new method has been proposed in this paper. It uses FFNN to calculate the mismatch for the recognition of a character, where it is observed that the distorted characters show very low mismatch with the original characters. For example, characters up to 70% distortions are found to be retrieved effectively.

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Index Terms

Computer Science
Information Sciences

Keywords

Image processing Neural network Feature extraction Distorted Bengali characters

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