Abstract

Hand Gesture is habitually used in every day life style. It is so natural way to communicate. Hand gesture recognition method is widely used in the application area of Controlling mouse and/or keyboard functionality, mechanical system, 3D World, Manipulate virtual objects, Navigate in a Virtual Environment, Human/Robot Manipulation and Instruction Communicate at a distance. This paper introduces a real time hand gesture recognition system. This system consists of three stages: image acquisition, feature extraction, and recognition. In the first stage input image of hand gestures are acquiesced by digital camera in approximate frame rate. In second stage a rotation, translation, scaling and orientation invariant feature extraction method has been introduce to extract the feature of the input image based on moment feature extraction method. Finally, a neural network is used to recognize the hand gestures. The performance of the system tested on real data. Based on the experimental results, we noted that this system shows satisfactory performance in hand gesture recognition.

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