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.

手语被认为是正常人与聋人之间的重要交流手段。因此，开发通信系统来帮助那些人是一个重要的问题。本文将中智技术和模糊c均值应用于检测和识别字母阿拉伯手语。提出的系统首先使用高斯滤波器删除噪声并准备要在下一步中使用的输入图像。之后，将图像转换为中智区域，然后提取其特征以开始分类阶段。然后在建议的系统中显示相应的字母。结果表明，所提出的系统具有良好的性能，而在实验中总分类精度达到了91％。