Real-Time and Robust Method for Hand Gesture Recognition System Based on Cross-Correlation Coefficient

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 forcommunicating with the virtual environment. In this paper a novel and real-time approach for hand gesture recognition systemis presented. In the suggested method, first, the hand gesture is extracted from the main image by the image segmentation andmorphological operation and then is sent to feature extraction stage. In feature extraction stage the Cross-correlation coefficientis 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%.

کلیدواژه ها:

Hand Gesture Recognition ، Image Processing ، Virtual Reality ، Cross-correlation