CFP last date
20 May 2024
Reseach Article

A Comparative study for approaches for Hand Sign Language

Published on March 2012 by Pravin R. Futane, R.V. Dharaskar, V. M. Thakare
2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 14
March 2012
Authors: Pravin R. Futane, R.V. Dharaskar, V. M. Thakare
4b31cdb1-8b3c-43c3-a8d8-674a0aa6b1db

Pravin R. Futane, R.V. Dharaskar, V. M. Thakare . A Comparative study for approaches for Hand Sign Language. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 14 (March 2012), 36-39.

@article{
author = { Pravin R. Futane, R.V. Dharaskar, V. M. Thakare },
title = { A Comparative study for approaches for Hand Sign Language },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { March 2012 },
volume = { NCIPET },
number = { 14 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 36-39 },
numpages = 4,
url = { /proceedings/ncipet/number14/5300-1112/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A Pravin R. Futane
%A R.V. Dharaskar
%A V. M. Thakare
%T A Comparative study for approaches for Hand Sign Language
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 0975-8887
%V NCIPET
%N 14
%P 36-39
%D 2012
%I International Journal of Computer Applications
Abstract

The sign language recognition and translation can be achieved which involves static and dynamic gesture recognition in which static gestures can easily be interpreted. But, for Dynamic gestures the sign language can be recognized with motion of the hands or movement of it for which Image based i.e. vision based mechanism can be applied. The Vision based technique involves either capturing the image of action or position or even directly visually recognizing the action. This technique which is very easy to understand as vision based can include both images as well as sequences of actions. Then, the feature i.e. signs action extraction and processing can be done according to type of sign recognized during visual gestures. Then compare with existing gestures and display the message and can be translated into text and speech as well. Also different image preprocessing algorithms can be developed.

References
  1. Pravin R. Futane , R.V. Dharaskar ,“HASTA MUDRA”,An Interpretation of Indian Hand Sign Gestures”, International Conference on Electronics Computer Technology (ICECT 2011), IEEE Xplore 2011, pp Volume V2-377-380.
  2. Paulraj M P, Sazali Yaacob, Hazry Desa, Hema C.R, .et al., “Extraction of Head and Hand Gesture Features for Recognition of Sign Language” International Conference on Electronic Design 2008, ICED 2008, pp.1-6, 2008.
  3. Tadashi Matsuo, Yoshiaki Shirai, Nobutaka Shimada, “Automatic Generation of HMM Topology for Sign Language Recognition”, 19th International Conference on Pattern Recognition, pp.1-4, ICPR 2008.
  4. Mairyam Pahlevanzadeh, Mansour Vafadoost, Majid Shahnazi “Sign Language Recognition”, International Telecommunication Research Center, IEEE-2007.
  5. Masaru Maebatake, Iori Suzuki, “Sign Language Recognition Based on Position and Movement Using Multi-Stream HMM ”, Proceedings of the 2008 Second International Symposium on Universal Communication, pp. 478-481, 2008 .
  6. Stavros Theodorakis, Athanassios Katsamanis, “Product-HMMS For Automatic Sign Language Recognition”, Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1601-1604, 2009.
  7. Pravin R. Futane , R.V. Dharaskar, V. M. Thakare ,”Hand-made Colored Gloves Gesture Recognition”, International Journal of Graphics & Image Processing, Vol 1 issue 2, November 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Recognition Static Signs Analysis Sign language recognition gestures image processing