Deaf Sign Interpreter Service
Shivanand V. Manjaragi, Patil, Revati, Chaitra Shende, Aruna Gadakeri, Sourab Nagare · Zenodo (CERN European Organization for Nuclear Research) · 2021
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 paper aims at implementing computer vision which can take the sign from the users and convert them into text in real time. The proposed methodology contains four modules such as: image capturing, pre-processing classification and prediction. This system uses a camera, which captures various gestures of the hand. Next, the captured image is pre-processed, the edges are determined an edge detection algorithm. Finally, a template-matching algorithm identifies the sign and display the text. As the output is text, one can easily interpret the meaning of a particular sign. This also curtails the difficulty to communicate with the deaf. The system is implemented by using OpenCV-Python. The system uses various libraries and finally translates the sign gestures to text with accuracy.