Research on FOD Detection for Airport Runway based on YOLOv3

摘要

Foreign object debris (FOD) on airport runways is a threatening factor to aircraft taking off and landing. Accurately detection of foreign objects debris is important to ensure aircraft flight safety. In this paper, a detection algorithm based on YOLOv3(You Only Look Once) for foreign objects debris is presented. This method employs deep residual network to extract feature and multi-scale feature fusion to detect small-scale FOD. Sample datasets of foreign object debris are established to validate our proposed method. The experiments show that the detection algorithm based on YOLOv3 effectively detect foreign objects debris, and has good accuracy and robustness.