Korean chess game implementation by hand gesture recognition using stereo camera

In this paper, we propose a real-time hand gesture recognition system, using a thinning method which utilizes a stereo camera and implements a Korean chess game system. We implement a depth map in the hand detection portion which uses the sum of absolute differences method, based on the acquired right-left image of detecting the foreground object. We use a convex hull to detect the regions of interest (ROI) and calculate the depth of the object in the ROI in order to obtain more accurate hand images. Then, we remove the background image in the ROI and get the foreground image as a hand image. Finally, we use a blob-labeling method to obtain the clean hand image, without the noise caused by computing distance from stereo matching. The hand gesture recognition system uses the Zhang and Suen thinning algorithm to obtain feature point, angle and distance. This system recognizes five types of hand gestures. The proposed method achieves an average recognition rate of 83%. At last, we applied the gesture recognition result to the Korean chess game system which can move the chess pieces by hand.