HAND GESTURE RECOGNITION SYSTEM FOR HUMAN COMPUTER INTERACTION USING CONTOUR ANALYSIS

Hand gesture recognition is a very challenging topic for real life applications because of its requirements on the robustness, accuracy and efficiency. This paper describes a system that enable a user to perform computer operations using hand gesture with a simple web camera as input device. This system involves four phases namely image acquisition, image pre-processing, feature extraction and gesture recognition. In the first phase, the input image is acquired with the help of a camera. In the second phase, the skin color of hand region is detected using HSV color space and morphological operations such as erosion and dilation are performed to remove noise followed by smoothing and thresholding of hand image. In Feature extraction phase, contours of hand image are detected. Finally, Gesture recognition phase includes recognizing hand gestures using contour analysis by comparing Auto-Correlation Function (ACF) amongst the contours and if they are close, then calculate Inter-Correlation Function (ICF) to truly determine similarity. Each recognized gesture is assigned with the corresponding action.