Publication

Abstract : To provide a means of communication between the audibly challenged people and rest of the world we need a sign language recognition system that would recognize the signs/gestures and convert them into a form which could be understood by the common people. The sign language recognition (SLR) system acts as a sign language translator which would identify a specific set of gestures and map them to their corresponding meaning as text data/audio files. The work mainly includes 3 sections. 1) Segmentation 2) Feature extraction and 3) Classification of gestures. In this research work we have been proposed an efficient method for recognizing the asymmetrical hand gestures in Indian sign language for audibly challenged people. The efficiency of the proposed method is verified on a dataset consisting of 600 images. The results indicates that the proposed system recognize the hand gestures successfully with 97% of recognition rate.