An Approach to Recognizing Numerals and Alphabets Signs for Impaired People

Authors

  • Bhavika Patel Birla Vishvakarma Mahavidhyalaya (Engg. College)
  • Narendra M Patel Birla Vishvakarma Mahavidhyalaya (Engg. College)
  • Zankhana H. Shah Birla Vishvakarma Mahavidhyalaya (Engg. College)

DOI:

https://doi.org/10.37591/joosd.v6i3.2306

Abstract

Abstract: Sign Language is the language used by deaf and dumb people for communication in their day to day life. Every nation has its own sign language. Indian people use Indian Sign Language. Generally, other sign languages such as ASL (American Sign Language) and BSL (British Sign Language) are single-handed sign language while ISL is the language which uses both hands to make signs. So, it is difficult to exactly classify and recognize those types of signs. The work presented here focuses on recognizing Indian sign language where Fourier descriptor is used for feature extraction and classification is achieved using a neural network.

Keywords: A nonverbal form of communication, preprocessing, Contour extraction, Fourier descriptor, neural network

Cite this Article: Bhavika Patel, Narendra M. Patel, Zankhana H. Shah. An Approach to Recognizing Numerals and Alphabets Signs for Impaired People. Journal of Open Source Developments. 2019; 6(2): 1–7p.

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Published

2019-12-30

Issue

Vol. 6 No. 3 (2019)

Section

Research Articles

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