无人机图像的输电线异物检测方法研究

Research on Foreign Body Detection Method of Transmission Line in UAV Image

目前无人机进行巡线成为热点,但无人机获取的图片是通过人工复检发现是否有异物的存在,效率很低、误检漏检率高。为了使无人机巡检更加高效和实现智能巡检,本文结合图像处理技术设计了一种根据异物轮廓特征进行异物检测的方法:首先对获取的图像进行灰度化,然后采用迭代阈值法对图像进行分割,用数学形态学结合连通区域管理去除分割后背景的影响,通过寻找轮廓和根据异物轮廓特征对异物进行检测。通过实验证明了该方法能有效检测出输电线上存在的异物。

At present,the UAV patrol line has become a hot spot,but the pictures taken by unmanned aerial vehicles are manually reexamined to find out whether there is any foreign body,which has a low efficiency and a high rate of false detection and mission.In order to make UAV inspection more efficient and realize intelligent inspection,a method of foreign object detection is designed based on the contour feature of foreign objects in combination with image processing technology.Firstly,the acquired image is grayed out,and then iterative threshold method is adopted.The image is segmented,and the influence of the segmented background is removed by mathematical morphology combined with the connected region management,and the foreign matter is detected by searching for the contour and according to the contour feature of the foreign object.Experiments show that the method can effectively detect the foreign matter present on the transmission line.