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Devnagari Handwriting Recognition using STANN

by Richa Sharma, Saurav Chandra, Sanjeev Kumar Yadav
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 19
Year of Publication: 2013
Authors: Richa Sharma, Saurav Chandra, Sanjeev Kumar Yadav
10.5120/12178-8273

Richa Sharma, Saurav Chandra, Sanjeev Kumar Yadav . Devnagari Handwriting Recognition using STANN. International Journal of Computer Applications. 70, 19 ( May 2013), 42-46. DOI=10.5120/12178-8273

@article{ 10.5120/12178-8273,
author = { Richa Sharma, Saurav Chandra, Sanjeev Kumar Yadav },
title = { Devnagari Handwriting Recognition using STANN },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 19 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number19/12178-8273/ },
doi = { 10.5120/12178-8273 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:19.122983+05:30
%A Richa Sharma
%A Saurav Chandra
%A Sanjeev Kumar Yadav
%T Devnagari Handwriting Recognition using STANN
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 19
%P 42-46
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Several approaches to recognize the handwritten characters and numerals such as online cursive handwriting and numerals recognition have been proposed. Most of them are based on neural network approaches. In this paper, a technique for continuous recognition of handwritten Devanagari characters is proposed. This approach employs a method based on Spatio-Temporal Artificial Neural Network (STANN). The proposed method is efficient in the field of online handwriting recognition because of the property of STANN to detection of spikes of the continuous input signals. The method is based on different steps of recognition. The results of signals are extracted from the input handwritten characters where the spikes signals are generated by the continuous signals of the input character. A new algorithm using STANN is proposed with results in this paper.

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Index Terms

Computer Science
Information Sciences

Keywords

STANN (Spatio-Temporal Artificial Neural Network) Preprocessing Spiking Neural Network Spike Detection

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