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In this paper, we present an autonomous helicopter with vision based navigation called South China University of Technology unmanned aerial vehicle (SCUAV). A GPS/INS system has been designed and implemented for getting stable navigation information. A Kalman filtering has been used in this system for data fusion. A real-time computer vision system is presented in this paper as the complement of the GPS/INS system. The vision algorithm is designed and implemented in this paper, which is integrated with algorithms for tracking a known landmark and estimating the helicopter positions. A method of image processing is designed for tracking and recognizing known land marks. At the end of the paper, we will present the experiment results to demonstrate our efficacious algorithm.