A Survey of Sign Recognition Approaches for Indian Sign Language

Authors

  • Twinkal H. Panchal  M.E. Student (Information Technology Department), L.D. College of Engineering, Gujarat Technological University, Ahmedabad, Gujarat, India
  • Pradip R. Patel  Assistant Professor (Information Technology Department), L.D. College of Engineering, Gujarat Technological University, Ahmedabad, Gujarat, India

Keywords:

Indian Sign Language, Gesture acquisition, Hand Gesture Recognition, Segmentation, Feature Extraction

Abstract

Sign Language (SL) is a communication tool for deaf & dumb people. It is a subset of gestures made with fingers, hands, and face etc. Each gesture in SL has a particular meaning & that is assigned to it. Deaf person directly not communicate with the normal person because normal person never try to learn the sign language. To solve this problem, there exists a need of system that can recognize gesture. Different country has different sign languages. For India, this is called as “Indian Sign Language (ISL)”. Only little research work has been carried out in this area for ISL. Several methods have been used to recognize of ISL alphabets and numerals. Many of them method is used to recognize static gesture. Only few works have been reported for dynamic gesture recognition of ISL. The mainly four steps are involved to recognize the sign: gesture acquisition, tracking and segmentation, feature extraction and gesture recognition. This paper presents a survey on various sign recognition approaches for ISL.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-01-20

Issue

Volume 4, Issue 2, January-February-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Twinkal H. Panchal, Pradip R. Patel, " A Survey of Sign Recognition Approaches for Indian Sign Language, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 2, pp.11-16 , January-February-2018.