DocumentCode :
3767278
Title :
Indian sign language translator using gesture recognition algorithm
Author :
Purva C. Badhe;Vaishali Kulkarni
Author_Institution :
Biomedical Engineering Department, D.J.S.C.O.E. Mumbai University, Mumbai, Maharashtra, India
fYear :
2015
Firstpage :
195
Lastpage :
200
Abstract :
Sign Language is a natural language which deaf community uses for communication. Sign Language (SL) is a subset of gestures or signs made with fingers, hands, arms, eyes, and head, face etc. Each gesture in SL has a meaning assigned to it. Understanding SL is nothing but understanding the meaning of these gestures. There exists a problem in communication when a person who completely relies on this gestural SL for communication tries to converse with a person who does not understand the SL. Every country has its own developed SL. In India, this language is called as "Indian Sign Language (ISL). This paper aims to develop an algorithm that will translate the ISL into English. This paper has implemented a system named as "Indian Sign Language (ISL) Translator using Gesture recognition algorithm". The system translates gestures made in ISL into English. The gestures that have been translated include numbers, alphabets and few phrases. The algorithm first performs data acquisition, then the pre-processing of gestures is performed to track hand movement using a combinational algorithm, and recognition is done using template matching. The database used for implementation has been self-created and includes total 130,000 videos; out of which 72,000 videos were used to create the system database and remaining 58,000 videos have been tested for checking the performance of the system. The accuracy of this system is as high as 97.5%.
Keywords :
"Gesture recognition","Assistive technology","Feature extraction","Databases","Videos","Image color analysis","Tracking"
Publisher :
ieee
Conference_Titel :
Computer Graphics, Vision and Information Security (CGVIS), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/CGVIS.2015.7449921
Filename :
7449921
Link To Document :
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