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Video Audio Interface for recognizing gestures of Indian sign Language
E.Kiran Kumar, S.R.C.Kishore , P.V.V.Kishore, P.Rajesh Kumar
Pages - 479 - 503     |    Revised - 01-09-2011     |    Published - 05-10-2011
Volume - 5   Issue - 4    |    Publication Date - September / October 2011  Table of Contents
Sign language, Wavelet transform, Image Fusion, Elliptical Fourier Descriptors, Principle Component Analysis, Fuzzy Inference System
We proposed a system to robotically recognize gestures of sign language from a video stream of the signer. The developed system converts words and sentences of Indian sign language into voice and text in English. We have used the power of image processing techniques and artificial intelligence techniques to achieve the objective. To accomplish the task we used powerful image processing techniques such as frame differencing based tracking, edge detection, wavelet transform, image fusion techniques to segment shapes in our videos. It also uses Elliptical Fourier descriptors for shape feature extraction and principal component analysis for feature set optimization and reduction. Database of extracted features are compared with input video of the signer using a trained fuzzy inference system. The proposed system converts gestures into a text and voice message with 91 percent accuracy. The training and testing of the system is done using gestures from Indian Sign Language (INSL). Around 80 gestures from 10 different signers are used. The entire system was developed in a user friendly environment by creating a graphical user interface in MATLAB. The system is robust and can be trained for new gestures using GUI.
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Mr. E.Kiran Kumar
Dadi Institute of Engineering and Technology - India
Mr. S.R.C.Kishore
Pydah College of Engineering - India
Mr. P.V.V.Kishore
Andhra University - India
Dr. P.Rajesh Kumar
Andhra University - India