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Enhanced Hand Gesture Recognition System

by Yogita Bhardwaj, Sukhdip Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 4
Year of Publication: 2015
Authors: Yogita Bhardwaj, Sukhdip Singh
10.5120/ijca2015906375

Yogita Bhardwaj, Sukhdip Singh . Enhanced Hand Gesture Recognition System. International Journal of Computer Applications. 127, 4 ( October 2015), 34-36. DOI=10.5120/ijca2015906375

@article{ 10.5120/ijca2015906375,
author = { Yogita Bhardwaj, Sukhdip Singh },
title = { Enhanced Hand Gesture Recognition System },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 4 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number4/22720-2015906375/ },
doi = { 10.5120/ijca2015906375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:19:01.365619+05:30
%A Yogita Bhardwaj
%A Sukhdip Singh
%T Enhanced Hand Gesture Recognition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 4
%P 34-36
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper implements a hand gesture recognition technique by using the SIFT based feature extraction. The matching point threshold has been calculated by using the neural network on the basis of the input gesture and the training. The paper implements the work by using the MATLAB and analyzes the results on the various sign of ASL. The system shows the accuracy of 93.3% i.e. improved by approx. &% as compared to the existing 85.9%. The system discussed in the paper is also robust as it shows the accurate results on the manipulated gestures.

References
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Index Terms

Computer Science
Information Sciences

Keywords

ASL Hand Gesture SIFT Neural network Threshold.

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