Nabeel Nazir
Muhammed Nihal
Arundath
Aiswarya P

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.