TY - GEN
T1 - Image based Arabic Sign Language recognition
AU - Mohandes, Mohamed
AU - Deriche, Mohamed
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/33847157933
U2 - 10.1109/ISSPA.2005.1580202
DO - 10.1109/ISSPA.2005.1580202
M3 - Conference contribution
AN - SCOPUS:33847157933
SN - 0780392434
SN - 9780780392434
T3 - Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
SP - 86
EP - 89
BT - Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
T2 - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Y2 - 28 August 2005 through 31 August 2005
ER -