• Sagar Yogesh Mehta
• Neha Kesarkar
• Oswyn Lewis
• Sushma Khanvilkar

This paper introduces a novel system to recognize Indian Sign Language (ISL) in Real-Time through the mobile application. This system will bridge the communication gap between the hearing, speech impaired and the rest of the society. The existing systems provide low accuracy and may not work in real-time. Our system provides accurate results and works in real-time. ISL signs and gestures will be captured through a phone camera and these gestures/signs will be decrypted into English text. The use of external hardware like sensors, gloves, etc. is not required. In India, there are 15 million people who cannot hear or speak. Also, to avoid the expense required for sensor-based systems, our application will be helpful for impaired people to communicate with society. Since this system is application-based, it can be used in all sectors of society.

Real time, Android application, Indian sign language, Computer vision, Machine learning, K-Nearest Neighbor, Gesture recognition, Grid-based feature extraction

"Hasta mudra abhijñānam - Indian sign language recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.1078-1083, April-2021, Available :http://www.jetir.org/papers/JETIR2104348.pdf

"Hasta mudra abhijñānam - Indian sign language recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp1078-1083, April-2021, Available at : http://www.jetir.org/papers/JETIR2104348.pdf