  Hand gesture recognition possesses extensive applications in virtual reality,
sign language recognition, and computer games. The direct interface of hand
gestures provides us a new way for communicating with the virtual environment.
In this paper a novel and real-time approach for hand gesture recognition
system is presented. In the suggested method, first, the hand gesture is
extracted from the main image by the image segmentation and morphological
operation and then is sent to feature extraction stage. In feature extraction
stage the Cross-correlation coefficient is applied on the gesture to recognize
it. In the result part, the proposed approach is applied on American Sign
Language (ASL) database and the accuracy rate obtained 98.34%.
