Dynamic Hand Gesture Recognition of Arabic Sign Language using Hand Motion Trajectory Features

In this paper we propose a system for dynamic hand gesture recognition of Arabic Sign Language. The proposed system takes the dynamic gesture (video stream) as input, extracts hand area and computes hand motion features, then uses these features to recognize the gesture. The system identifies the hand blob using YCbCr color space to detect skin color of hand. The system classifies the input pattern based on correlation coefficients matching technique. The significance of the system is its simplicity and ability to recognize the gestures independent of skin color and physical structure of the performers. The experiment results show that the gesture recognition rate of 20 different signs, performed by 8 different signers, is 85.67%.