• Shraddha Suresh Bhaware
• Madhuri S. Wakode

Sign language is the language used by deaf and dumb people. This language involves complex hands movements, facial expressions and body postures. Sign language is not a common to each community in the world. This sign language is different for every country. Grammar rules are different for each sign language. When normal people try to communicate with deaf and dumb people they cannot communicate because of lack of language knowledge using their language with the people who are unaware of the language’s grammar. So it is required to develop an interpreter that must be interactive and automatic. People want something more natural like to interpret dynamic signs. Our proposed system is based on 3D CNN model which is simple to understand and likewise simple to implement. Gesture recognition using computer vision involves image processing techniques, and works fine for static gestures but fails for dynamic gestures. CNN based system can interpret video directly without any complex algorithm or equipment. The main purpose of this survey is to give a nearly full image of how Machine Learning and Image Processing techniques are used in Sign Language Recognition to improve the performance.

Image Processing, Indian Sign Language, Action Recognition, Machine Learning

"A Survey on Dynamic and Real Time Hand Gesture Recognition for Indian Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.990-994, June-2019, Available :http://www.jetir.org/papers/JETIR1906F02.pdf

"A Survey on Dynamic and Real Time Hand Gesture Recognition for Indian Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp990-994, June-2019, Available at : http://www.jetir.org/papers/JETIR1906F02.pdf