ProgramsView all programs
From the news
- Chancellor Amma Addresses the Parliament of World’s Religions
- Amrita Students Qualify for the European Mars Rover Challenge
Publication Type : Journal Article
Publisher : IJCA Special Issue on Recent Trends in Pattern Recognition and Image Analysis
Source : IJCA Special Issue on Recent Trends in Pattern Recognition and Image Analysis, Volume RTPRIA, Number 1, p.40-45 (2013)
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking
Department : Computer Science
Verified : Yes
Year : 2013
Abstract : Deaf and dumb people communicate among themselves using sign languages, but they find it difficult to expose themselves to the outside world. This paper proposes a method to convert the Indian Sign Language (ISL) hand gestures into appropriate text message. In this paper the hand gestures corresponding to ISL English alphabets are captured through a webcam. In the captured frames the hand is segmented and the neural network is used to recognize the alphabet. The features such as angle made between fingers, number of fingers that are fully opened, fully closed or semi closed and identification of each finger are used as input to the neural network. Experimentation done for single hand alphabets and the results are summarized.
Cite this Research Publication : Dr. Padmavathi S., S, S. M., and V, V., “Indian Sign Language Character Recognition using Neural Networks”, IJCA Special Issue on Recent Trends in Pattern Recognition and Image Analysis, vol. RTPRIA, pp. 40-45, 2013.