Improved Real-Time Approach to Static Hand Gesture Recognition

A real-time hand detection and tracking system is developed in this work in which the gestures are recognized by counting the number of fingers. More than fifteen kinds of hand gestures are recognized in this system and these gestures are then mapped with the keyboard keys. For background Subtraction we used Grayscale color space followed by. contour of hand, which is developed using Canny’s Algorithm to which we applied Chan’s algorithm to obtain the convex hull. From the defect points of Convex Hull, we obtained the center point of the hand. Using this, we counted the fingers and thereby recognizing the gestures. We performed several trials to validate the feasibility and applicability of the proposed system, and confirmed the accuracy of 93.20%.