@inproceedings{098445cdc41d4c38a83868b3fd1fcf61,
title = "Image based Arabic Sign Language recognition",
abstract = "In this paper we propose an image based system for Arabic Sign Language recognition. The recognition stage is performed using a Hidden Markov Model. We have used a Gaussian skin color model to detect the signer's face. The detected face region is then used as a reference to track the hands movement using region growing from the sequence of images comprising the signs. A number of features are then selected from the detected hand regions across the sequence of images. Such features are then used as input to the HMM. The proposed system achieved a recognition accuracy of 98\% for a data set of 50 signs.",
author = "Mohamed Mohandes and Mohamed Deriche",
year = "2005",
doi = "10.1109/ISSPA.2005.1580202",
language = "English",
isbn = "0780392434",
series = "Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005",
pages = "86--89",
booktitle = "Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005",
}