Vision Based Sign Language Recognition: a Survey
Sadhana Bhimrao Bhagat, Dinesh Vitthalrao Rojatkar · Journal of Emerging Technologies and Innovative Research · 2017
The Sign language is very important for people who have speaking and hearing deficiency generally called Deaf and Mute. It is the only mode of communication for such people to convey their message and it become very important for people to understand their language. This paper proposes algorithm or method for an application which would help in recognizing the different signs which is called Indian Sign Language. The method has been developed with respect to the single user. The real time images will be captured first and then it stored in the directory and on recently captured image and feature expulsion will take place to identify which sign has been articulated by the user through SIFT(scale invariance Fourier transform) algorithm. The comparison will be performed in arrear and then after comparison the result will be produced in accordance through matched key point from the input image to the image stored for a specific letter already in the directory or the database the output for the following can be seen in below sections. There are twenty six signs in Indian Sign Language corresponding to each alphabet out which the proposed algorithm provided with 95% accurate result for nine alphabets with their images captured at every possible angle and distance.