1 M.E ( Electronics & Telecommunication Second year) G.H.Raisoni C.E.M. Amravati 2 Assistant Professor ( Electronics & Telecommunication ) G.H.Raisoni C.E.M. Amravati
Kunal A. Wankhade, Gauri N. Zade · 2014
In the world of sign language, and gestures, a lot of research work has been done over the past three decades. This has brought about a gradual transition from isolated to continuous, and static to dynamic gesture recognition for operations on a limited vocabulary. In present scenario, human machine interactive systems facilitate communication between the deaf, and hearing people in real world situations. In order to improve the accuracy of recognition, many researchers have deployed methods such as HMM, Artificial Neural Networks, and Kinect platform. Effective algorithms for segmentation, classification, pattern matching and recognition have evolved. The main purpose of this paper is to analyze these methods and to effectively compare them, which will enable the reader to reach an optimal solution. This creates both, challenges and opportunities for sign language recognition related research