DocumentCode :
618448
Title :
Artificial neural network based method for Indian sign language recognition
Author :
Adithya, V. ; Vinod, P.R. ; Gopalakrishnan, Uma
Author_Institution :
Dept. of Comput. Eng., Coll. of Eng. Chengannur, Chengannur, India
fYear :
2013
fDate :
11-12 April 2013
Firstpage :
1080
Lastpage :
1085
Abstract :
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.
Keywords :
handicapped aids; neural nets; sign language recognition; Indian sign language recognition; artificial neural network; deaf-dumb community; facial expression; fingerspelling automatic recognition; hand gesture; Assistive technology; Feature extraction; Gesture recognition; Image color analysis; Shape; Transforms; Vectors; Artificial neural network; Central moments; Distance transform; Fourier descriptors; Hand segmentation; Indian sign language; Projections;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information & Communication Technologies (ICT), 2013 IEEE Conference on
Conference_Location :
JeJu Island
Print_ISBN :
978-1-4673-5759-3
Type :
conf
DOI :
10.1109/CICT.2013.6558259
Filename :
6558259
Link To Document :
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