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Sign Language Recognition has emerged as one of the important area ofresearch in Computer Vision. The difficulty faced by the researchers is thatthe instances of signs vary with both motion and appearance. Thus, in thispaper a novel approach for recognizing various alphabets of Indian SignLanguage is proposed where continuous video sequences of the signs have beenconsidered. The proposed system comprises of three stages: Preprocessing stage,Feature Extraction and Classification. Preprocessing stage includes skinfiltering, histogram matching. Eigen values and Eigen Vectors were consideredfor feature extraction stage and finally Eigen value weighted Euclideandistance is used to recognize the sign. It deals with bare hands, thus allowingthe user to interact with the system in natural way. We have considered 24different alphabets in the video sequences and attained a success rate of96.25%.

Recognition of Indian Sign Language in Live Video