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http://dx.doi.org/10.1109/3477.485888

has been cited by the following article:

• 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.