Indian Sign Language Recognition Using Ensemble Based Classifier Combination
Ashok Kumar Sahoo, Pradeepta Kumar Sarangi, Chandra Shekhar Yadav · Macromolecular Symposia · 2022
Abstract Indian Sign Language (ISL) is an alternate to written and direct communication language used in India and Indian subcontinent. It is commonly used by deaf and mute people who cannot speak and hear. The ISL is a new sign language as compared to other sign languages used in developed countries. There is a need for automatic recognition of any sign language including ISL due to its application aspects in current times. The automation of ISL will helpful to both communities (those who can interact only through ISL and those who do not know ISL at all), because in many places the unblessed people facing difficulty in communicating like at airports, railway stations, banks, hospitals, and other places. In this paper, the authors have tried to develop an automatic conversion from ISL signs to text in the domain of digits. The system requires a digital camera to capture the ISL signs and the underlying software will interpret the meaning of the image. To develop such a system, pattern recognition concept including image processing techniques have been used. Important features from the ISL signs are extracted using Histogram Oriented Gradient (HOG) technique. To classify the input images, two classification techniques have been used in the experiments namely Tree Bagger and Fit Ensemble.