@inproceedings{6013604b410c4b4194b47ed29732c9e2,
title = "Arabic sign language recognition an image - Based approach",
abstract = "In this paper we propose an image based system for Arabic Sign Language recognition. A Gaussian skin color model is used to detect the signer's face. The centroid of the detected face 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. The recognition stage is performed using a Hidden Markov Model. The proposed system achieved a recognition accuracy of about 93\% for a data set of 300 signs with leave one out method.",
author = "M. Mohandes and Quadri, \{S. I.\} and M. Deriche",
year = "2007",
doi = "10.1109/AINAW.2007.98",
language = "English",
isbn = "0769528473",
series = "Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07",
pages = "272--276",
booktitle = "Proceedings - 21st International Conference on Advanced Information Networking and ApplicationsWorkshops/Symposia, AINAW'07",
}