@inproceedings{ebdc71b1e6c84268abe05dab4ec20720,
title = "Isolated 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 colour 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 ranging from 87\% to 96\% for a data set of 300 signs.",
keywords = "Arabic sign language recognition, Gaussian skin model, Hidden Markov model, Region growing",
author = "M. Mohandes and U. Johar and M. Deriche and S. Ilyas",
year = "2008",
language = "English",
isbn = "9780980326727",
series = "5th International Conference on Information Technology and Applications, ICITA 2008",
pages = "365--368",
booktitle = "5th International Conference on Information Technology and Applications, ICITA 2008",
note = "5th International Conference on Information Technology and Applications, ICITA 2008 ; Conference date: 23-06-2008 Through 26-06-2008",
}