Recognition system for alphabet Arabic sign language using neutrosophic and fuzzy c-means


Sign language is considered as the important communication means among the normal people and the deaf. Therefore, developing communication systems to help those people is an important issue. In this paper, the neutrosophic technique and fuzzy c-means are applied to detect and recognize the alphabet Arabic sign language. The proposed system starts by using a gaussian filter to delete the noise and prepare the input image to be used in the next step. After that, the image is converted to the neutrosophic domain then its features are extracted to start the classification phase; then the corresponding letter is displayed in the proposed system. The results showed good performance for the proposed system whereas, the total classification accuracy reached 91% in the experiment.

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Correspondence to Safaa M. Elatawy.

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Elatawy, S.M., Hawa, D.M., Ewees, A.A. et al. Recognition system for alphabet Arabic sign language using neutrosophic and fuzzy c-means. Educ Inf Technol (2020).

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  • Arabic sign language recognition
  • Neutrosophic
  • Image processing
  • Fuzzy c-means