Machine Learning Techniques for Indian Sign Language Recognition

Abstract

Over the years, communication has played a vital role in exchange of information and feelings in one’s life. Sign language is the only medium through which specially abled people can connect to rest of the world through different hand gestures. With the advances in machine learning techniques, Hand gesture recognition (HGR) became a very important research topic. This paper deals with the classification of single and double handed Indian sign language recognition using machine learning algorithm with the help of MATLAB with 92-100% of accuracy.

Publication
2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC)
Kusumika Dutta
Kusumika Dutta
Assistant Professor

Kusumika Krori Dutta, working as Assistant professor in Electrical and Electronics Engineering Department , MSRIT, Bangalore, India. She completed B.E (Electrical Engg) , M.Sc(Engg) by research and pursuing PhD in investigation on neurological disorder. She believes in lifelong learning and is passionate to explore different socio-cultural needs and their solutions through her indagation. Her love towards research, aided her to invent a mathematical formula of pattern based multiplication and patented many products having social utility

Sunny Arokia Swamy Bellary
Sunny Arokia Swamy Bellary
Engineer/Scientist II

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