Research on adaptive Harris corner detection of UAV airport runway based on stereo vision

As a key facility for aircraft taking off and landing, the airport runway's safety status directly affects the safety and efficiency of air traffic. Therefore, it is of great significance to monitor the runway state accurately and efficiently, and to find and deal with potential safety hazards in time for ensuring flight safety. In this paper, the research on adaptive Harris corner detection of UAV airport runway based on stereo vision is proposed. The objective function of adaptive Harris corner detection for UAV airport runway is constructed. Based on this, the uneven settlement of UAV airport runway is calculated, and the pixel corner objects in stereo vision image that meet the characteristics of adaptive Harris corner are analyzed, and the adaptive Harris corner detection results are obtained. The experimental results show that the stereo matching degree of this method is high, and all the targets are detected correctly, which shows that it has high detection accuracy, can accurately capture the runway settlement changes, find potential problems in time, and ensure the safe use of UAV airport runway.