System that assists the differently abled people

Author:

Prasad Gowri1,S Spandana2,V Poojana2,Kulkarni Shrinidhi U2

Affiliation:

1. Assistant Professor, Information Science Engineering, New Horizon College of Engineering, Bangalore, Karnataka, India

2. Student of Information Science and Engineering, New Horizon College of Engineering, Bangalore, Karnataka, India

Abstract

All human beings are able to see, listen and interact with their external environment naturally. There are some people who are differently abled and unfortunately they do not have the ability to use their senses to the best extent. Such people are dependent on other means of communication like sign language or hand gestures. As this hinders the communication between the challenged person say bed-ridden or even paralysed and the common people, it affects to a great extent in their progress and makes them difficult to achieve their dreams. To bridge this gap in communication there is a need of system of gesture recognition or sign language.

Publisher

Technoscience Academy

Subject

General Medicine

Reference10 articles.

1. Rajat Agarwal, Ankush Mittal, Balasubramanian Raman, “Hand Gesture Recognition using Discrete Wavelet Transform and Support Vector Machine”, Conference on Signal Processing and Integrated Networks, February 2015

2. Ms Kamal Preet Kour, Dr. (Mrs) Lini Mathew, “Literature Survey on Hand Gesture Techniques for Sign Language Recognition”, International Journal of Technical Research & Science, Volume 2 Issue VII, August 2017

3. Neelam K Gilorkar, Manisha M Ingle, “Real Time Detection and Recognition Of Indian and American sign Language Using Sift”, International Journal Of Electronics And Communication Engineering& Technology, Volume 5, Issue 5, May (2014), pp. 11-18

4. Shamaie, Atid and Sutherland, Alistair (2003) “Accurate recognition of large number of hand gestures.”, Iranian Conference on Machine Vision and Image Processing, 13-15 February 2003, Tehran, Iran.

5. Admasu, Yonas, Raimond, Kumudha, “Ethiopian sign language recognition using Artificial Neural Network”, International Conference on Intelligent Systems Design and Applications (ISDA), January 2011

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