Hand gesture recognition system for real-time application

In recent years, several researches are being done to improve the means by which human to machine interaction. With the development of input devices like keyboard, mouse and pen are not sufficient due to this limitation direct use of hand gesture as an input device to provide natural human to machine interaction. The objective of this paper is to implement the vision based hand gesture recognition system to control the movement of robot. We can use of Scale invariant feature transform (SIFT) for extract the keypoint from the gesture image capture by single sensing device. Space incompatibility of SIFT keypoint causes bag of feature approach was introduced. Then use the vector quantization will map the keypoint extracted from SIFT into unified dimensional histogram vector after the K-mean clustering. The histogram vectors as an input to multiclass SVM classifier for recognize the gesture. Generate the grammar apply to the robot to control the movements (Left, Right, Straight ward, Backward, stop) of robot.