The moving target tracking is a very important in computer vision research topic and is widely used, it is of great research significance, has been widely used, and involved in image recognition, production automation, intelligent pattern recognition, artificial intelligence, weather information, and other fields, but in some high speed movement, such as target under complex background target trajectory when not much target tracking is still more difficult. This paper mainly studies the Kalman tracking algorithm of ping-pong robot based on fuzzy real-time image. For table tennis high-speed motion blurred images, air resistance and the camera imaging distortion caused by factors such as the error problem, puts forward an adaptive measurement covariance discrete Kalman trajectory estimation algorithm. The algorithm with dynamic adjustment of measuring the size of the covariance, has realized the accurate tracking of the target motion trajectory, and further laid the groundwork for table tennis balls prediction and hitting arm. The experimental results show that the algorithm can effectively overcome the interference of measurement noise and data loss and give excellent tracking results when the image acquisition rate is higher than 70 frames /s and the table tennis speed is higher than 5 m/s.
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