无人机影像辅助下的路桥病害智能检测

路桥表面病害状况评估是路桥养护的一项重要内容。目前病害检测主要基于移动测量车和目视判断，具有工作量大、获取危险度高的缺点，而低空飞行的六旋翼无人机能够拍摄到人工无法获取到的多角度路桥照片，在路桥检测方面具有巨大的优势。本文基于无人机影像开展路桥病害检测相关研究，提出了一种新的路桥病害检测方法。首先通过多部件形变模型模拟病害目标，并在无人机影像中全局搜索，检测出潜在路桥病害区域。试验表明，本文算法在复杂背景下能够有效检测病害，目标检测精度达80%，具有很高的效率和鲁棒性。

Intelligent Road and Bridge Disease Detection Method Based on UAV Images

Disease assessment is an important aspect of roads and bridges maintenance.Current disease detection is mainly based on automatic measuring vehicles and visual judgments, with the shortcomings of heavy workload and high risk.Correspondingly, the low-flying six-rotor unmanned aerial vehicles (UAV) can take photos of roads and bridges from multi-angles, which has great advantages on roads and bridges detection.Based on UAV images, this paper developed a new method in disease detection of roads and bridges.First, the multi-component deformation model was used to simulate the disease target.Then the global image was searched to detect the potential disease areas.Finally, the disease areas were detected from UAV images.Experiments showed that the proposed algorithm could effectively detect the disease in complex background, and the target detection accuracy was over 80%, with high efficiency and strong robustness.