Recognition System for Alphabet Arabic Sign Language Using Neutrosophic and Fuzzy C-Means

Autor/inn/en	Elatawy, Safaa M.; Hawa, Doaa M.; Ewees, A. A.; Saad, Abeer M.
Titel	Recognition System for Alphabet Arabic Sign Language Using Neutrosophic and Fuzzy C-Means
Quelle	In: Education and Information Technologies, 25 (2020) 6, S.5601-5616 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-020-10184-6
Schlagwörter	Sign Language; Semitic Languages; Alphabets; Pattern Recognition; Classification; Accuracy; Artificial Intelligence + Suchen Sie Ihr Suchwort? Gebärdensprache; Arabisch; Hebräisch; Buchstabenschrift; Mustererkennung; Classification system; Klassifikation; Klassifikationssystem; Künstliche Intelligenz
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01