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DOI: 10.14569/IJACSA.2018.090552
PDF

Automatic Sign Language Recognition: Performance Comparison of Word based Approach with Spelling based Approach

Author 1: Shazia Saqib
Author 2: Syed Asad Raza Kazmi
Author 3: Khalid Masood
Author 4: Saleh Alrashed

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 5, 2018.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Evolution of computer based interaction has been through a number of phases. From command line interface to menu driven environment to Graphics User Interface, the communication has evolved to a better user friendly environment. A new form of communication is on the rise and that is Gesture Based Communication, which is a touch free environment basically. Although its applications are mainly for deaf community but smart mobiles, laptops and other similar devices are encouraging this new kind of communication. Sign languages all over the world have a dictionary of signs of several thousand words. Mostly these signs are word based which means that these signs do not make use of basic alphabet signs, rather a new sign has to be designed for every new word added to the dictionary. This paper suggests use of spelling-based gestures especially while communicating with smart phones and laptops.

Keywords: Feature extraction; human computer interaction; image segmentation; object recognition

Shazia Saqib, Syed Asad Raza Kazmi, Khalid Masood and Saleh Alrashed, “Automatic Sign Language Recognition: Performance Comparison of Word based Approach with Spelling based Approach” International Journal of Advanced Computer Science and Applications(IJACSA), 9(5), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090552

@article{Saqib2018,
title = {Automatic Sign Language Recognition: Performance Comparison of Word based Approach with Spelling based Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090552},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090552},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {5},
author = {Shazia Saqib and Syed Asad Raza Kazmi and Khalid Masood and Saleh Alrashed}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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