  Sign Language Recognition has emerged as one of the important area of
research in Computer Vision. The difficulty faced by the researchers is that
the instances of signs vary with both motion and appearance. Thus, in this
paper a novel approach for recognizing various alphabets of Indian Sign
Language is proposed where continuous video sequences of the signs have been
considered. The proposed system comprises of three stages: Preprocessing stage,
Feature Extraction and Classification. Preprocessing stage includes skin
filtering, histogram matching. Eigen values and Eigen Vectors were considered
for feature extraction stage and finally Eigen value weighted Euclidean
distance is used to recognize the sign. It deals with bare hands, thus allowing
the user to interact with the system in natural way. We have considered 24
different alphabets in the video sequences and attained a success rate of
96.25%.
