Mohandes, M. and A-Buraiky, S. and Halawani, T. and Al-Baiyat, S. (2004) Automation of the Arabic sign language recognition. Information and Communication Technologies: From Theory to Applications, 2004. Proceedings. 2004 International conference, 1.
This paper introduces a system to recognize the Arabic sign language using an instrumented glove and a machine learning method. Interfaces in sign language systems can be categorized as direct-device or vision-based. The direct-device approach uses measurement devices that are in direct contact with the hand such as instrumented gloves, flexion sensors, styli and position-tracking devices. On the other hand, the vision-based approach captures the movement of the singer's hand using a camera that is sometimes aided by making the signer wear a glove that has painted areas indicating the positions of the fingers or knuckles. The proposed system basically consists of a PowerGlove that is connected through the serial port to a workstation running the support vector machine algorithm. Obtained results are promising even though a simple and cheap glove with limited sensors was utilized.
|Divisions:||College Of Engineering Sciences > Electrical Engineering Dept|
|Creators:||Mohandes, M. and A-Buraiky, S. and Halawani, T. and Al-Baiyat, S.|
|Deposited By:||KFUPM ePrints Admin|
|Deposited On:||24 Jun 2008 16:46|
|Last Modified:||12 Apr 2011 13:16|
Repository Staff Only: item control page