Artificial neural network based method for Indian sign language recognition - Adithya, V.; Vinod, P. R.; Gopalakrishnan, Usha (2013 IEEE Conference on Information and Communication Technologies, 2013)
Sign Language is a language which uses hand gestures, facial expressions and body movements for communication. A sign language consists of either word level signs or fingerspelling. It is the only communication mean for the deaf-dumb community. But the hearing people never try to learn the sign language. So the deaf people cannot interact with the normal people without a sign language interpreter. This causes the isolation of deaf people in the society. So a system that automatically recognizes the sign language is necessary. The implementation of such a system provides a platform for the interaction of hearing disabled people with the rest of the world without an interpreter. In this paper, we propose a method for the automatic recognition of fingerspelling in Indian sign language. The proposed method uses digital image processing techniques and artificial neural network for recognizing different signs.