TITLE:
An Efficient Framework for Indian Sign Language Recognition Using Wavelet Transform
AUTHORS:
Mathavan Suresh Anand, Nagarajan Mohan Kumar, Angappan Kumaresan
KEYWORDS:
Hand Gesture, Sign Language Recognition, Thresholding, Wavelet Transform, Nearest Neighbour Classifier
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.8,
June
22,
2016
ABSTRACT: Hand gesture recognition
system is considered as a way for more intuitive and proficient human computer
interaction tool. The range of applications includes virtual prototyping, sign
language analysis and medical training. In this paper, an efficient Indian Sign
Language Recognition System (ISLR) is proposed for deaf and dump people using
hand gesture images. The proposed ISLR system is considered as a pattern
recognition technique that has two important modules: feature extraction and
classification. The joint use of Discrete Wavelet Transform (DWT) based feature
extraction and nearest neighbour classifier is used to recognize the sign
language. The experimental results show that the proposed hand gesture
recognition system achieves maximum 99.23% classification accuracy while using
cosine distance classifier.