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A Neural Network based Real Time Hand Gesture Recognition System

by Tasnuva Ahmed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 4
Year of Publication: 2012
Authors: Tasnuva Ahmed
10.5120/9535-3971

Tasnuva Ahmed . A Neural Network based Real Time Hand Gesture Recognition System. International Journal of Computer Applications. 59, 4 ( December 2012), 17-22. DOI=10.5120/9535-3971

@article{ 10.5120/9535-3971,
author = { Tasnuva Ahmed },
title = { A Neural Network based Real Time Hand Gesture Recognition System },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 4 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number4/9535-3971/ },
doi = { 10.5120/9535-3971 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:05:14.055388+05:30
%A Tasnuva Ahmed
%T A Neural Network based Real Time Hand Gesture Recognition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 4
%P 17-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Hand Gesture is habitually used in every day life style. It is so natural way to communicate. Hand gesture recognition method is widely used in the application area of Controlling mouse and/or keyboard functionality, mechanical system, 3D World, Manipulate virtual objects, Navigate in a Virtual Environment, Human/Robot Manipulation and Instruction Communicate at a distance. This paper introduces a real time hand gesture recognition system. This system consists of three stages: image acquisition, feature extraction, and recognition. In the first stage input image of hand gestures are acquiesced by digital camera in approximate frame rate. In second stage a rotation, translation, scaling and orientation invariant feature extraction method has been introduce to extract the feature of the input image based on moment feature extraction method. Finally, a neural network is used to recognize the hand gestures. The performance of the system tested on real data. Based on the experimental results, we noted that this system shows satisfactory performance in hand gesture recognition.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Hand gesture Moment feature extraction method Multilayer feed forward neural network

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