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In this paper, we propose a real-time hand gesture recognition system based on difference image entropy using a stereo camera. Existing systems use hand detection primarily with some type of marker. Our system, however, uses a real-time hand image recognition system. In the detection step, we implement a depth map using a sum of absolute differences based on the acquired right-left image using a stereo camera. This system detects a foreground object and perceives it as a hand. The hand gesture recognition system uses the difference image entropy of the input image and the average image. To evaluate the performance of the proposed technology, we implement a recognition experiment using the hand gesture 240 database. The proposed method shows an average recognition rate of 85%. Using the proposed method, we implement a Chinese chess game based on hand gesture recognition. |
