SIGN LANGUAGE DETECTION USING CNN AND OPEN-CV

Abstract

Sign language is common and efficient way of communicating among hard hearing people and normal people. Regular people have no difficulty in recognizing and decoding the essence of sign language communicated by hearing impaired individuals, it is likely that they must have an interpreter for sign language communication. People with hearing and speech abnormalities use the Sign Language to communicate their message to other people. Sign Language has grown as one of the great areas of computer vision research and study. Researchers in sign language recognition used various input tools for recording hand gestures, such as data gloves, web camera, depth camera, colour camera, Microsoft's Kinect sensor etc. In this study, hand gesture recognition for American Sign Language with Convolutional Neural Networks using OPEN-CV is proposed and to collect the data in-build webcam of laptop can be used to reduce cost of the model.