Sign Language Translation
R. Harini, R. Janani, S Keerthana, S Madhubala, S. Venkatasubramanian
Abstract
Sign language is the way of communication for hearing impaired people. There is a challenge for common people to communicate with deaf people which makes this system helpful in assisting them. This project aims at implementing computer vision which can take the sign from the users and convert them into text in real time. The proposed system contains four modules such as: image capturing, preprocessing classification and prediction. By using image processing the segmentation can be done. Sign gestures are captured and processed using OpenCV python library. The captured gesture is resized, converted to grey scale image and the noise is filtered to achieve prediction with high accuracy. The classification and predication are done using convolution neural network.