裴云成, 贝前程, 刘海英, 张绍杰. 基于机器视觉的安全距离检测方法[J]. 山东电力技术, 2021, 48(1): 27-31.
引用本文: 裴云成, 贝前程, 刘海英, 张绍杰. 基于机器视觉的安全距离检测方法[J]. 山东电力技术, 2021, 48(1): 27-31.
PEI Yun-cheng, BEI Qian-cheng, LIU Hai-ying, ZHANG Shao-jie. Application of Machine Vision in the Safety Distance Detection of Power Transmission Network[J]. Shandong Electric Power, 2021, 48(1): 27-31.
Citation: PEI Yun-cheng, BEI Qian-cheng, LIU Hai-ying, ZHANG Shao-jie. Application of Machine Vision in the Safety Distance Detection of Power Transmission Network[J]. Shandong Electric Power, 2021, 48(1): 27-31.

基于机器视觉的安全距离检测方法

Application of Machine Vision in the Safety Distance Detection of Power Transmission Network

  • 摘要: 将机器视觉技术应用在距离检测中能更好地提高检测的精度,特别是在某些重要场所和恶劣环境下,机器视觉技术能更好地代替人类工作。将双目视觉技术与图像处理技术相结合,先应用高斯拉普拉斯算子(Laplacian of Gaussian,LOG)对采集的图像进行预处理,获得清晰的边缘信息,然后根据双目立体视觉原理,获取图像边缘点的坐标,最后根据空间点的距离公式获得两物体边缘点距离集合。筛选出其中的最短距离即为两物体间安全距离的判断依据,此方法也可用于输电线路周围障碍物安全距离的检测。

     

    Abstract: The application of machine vision technology in the distance detection of transmission networks can better improve the accuracy of detection.Especially in some important places and harsh environments,machine vision technology can better replace human labor.In this paper,a new distance detection method is proposed combining binocular vision technology and image processing technology.The Laplacian of Gaussian(LOG) algorithm is firstly applied to preprocess the collected images to obtain clear edge information.Then the coordinates of the edge points of the image can be obtained based on the principle of binocular vision stereo reconstruction.Finally the distance formula of the space point is used to calculate the distance set between the edge points of the object and the transmission line.The shortest distance is found out for determining whether the surrounding objects are within a safe distance range.The accuracy of this method satisfies the need of examine of the safe distance between obstacles and surrounding transmission lines.

     

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