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Reseach Article

Boltay Hath for Indian Sign Language Recognition

by Sarbjeet Kaur, V. K. Banga
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 1
Year of Publication: 2014
Authors: Sarbjeet Kaur, V. K. Banga

Sarbjeet Kaur, V. K. Banga . Boltay Hath for Indian Sign Language Recognition. International Journal of Applied Information Systems. 7, 1 ( April 2014), 1-7. DOI=10.5120/ijais14-451103

@article{ 10.5120/ijais14-451103,
author = { Sarbjeet Kaur, V. K. Banga },
title = { Boltay Hath for Indian Sign Language Recognition },
journal = { International Journal of Applied Information Systems },
issue_date = { April 2014 },
volume = { 7 },
number = { 1 },
month = { April },
year = { 2014 },
issn = { 2249-0868 },
pages = { 1-7 },
numpages = {9},
url = { },
doi = { 10.5120/ijais14-451103 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2023-07-05T18:54:24.669248+05:30
%A Sarbjeet Kaur
%A V. K. Banga
%T Boltay Hath for Indian Sign Language Recognition
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 7
%N 1
%P 1-7
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

In this research work it is discussed that how a gesture recognition system for alphabetical hand gestures is built. The main motive was to develop a system that can simplify the way that the normal human being interact with the deaf and dump people without the need of interpretator . This system also provides the easy way of humans interaction with computers. This system is designed using MATLAB instead of neural network. In this system Eigen vector and Eigen value techniques only in MATLAB are used. The basis of our method is a fast detection process to obtain the meaningful hand region from the whole image, which is able to deal with a large number of hand gestures against different indoor backgrounds and lighting condition, and a recognition process that identifies the hand gestures from the images of the normalized hand. Experiments show that the system can achieve a 99% recognition rate and is suitable for real-time applications.

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Index Terms

Computer Science
Information Sciences


Hand gestures human computer interaction Graphical user interface MATLAB.