首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >UTILITY POLES EXTRACTION FROM MOBILE LIDAR DATA IN URBAN AREA BASED ON DENSITY INFORMATION
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UTILITY POLES EXTRACTION FROM MOBILE LIDAR DATA IN URBAN AREA BASED ON DENSITY INFORMATION

机译:基于密度信息,公用事业杆从城区移动激光雷达数据提取

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Utility poles located along roads play a key role in road safety and planning as well as communications and electricity distribution. In this regard, new sensing technologies such as Mobile Terrestrial Laser Scanner (MTLS) could be an efficient method to detect utility poles and other planimetric objects along roads. However, due to the vast amount of data collected by MTLS in the form of a point cloud, automated techniques are required to extract objects from this data. This study proposes a novel method for automatic extraction of utility poles from the MTLS point clouds. The proposed algorithm is composed of three consecutive steps of pre-processing, cable area detection, and poles extraction. The point cloud is first pre-processed and then candidate areas for utility poles are specified based on Hough Transform (HT). Utility poles are extracted by applying horizontal and vertical density information to these areas. The performance of the method was evaluated on a sample point cloud and 98% accuracy was achieved in extracting utility poles using the proposed method.
机译:沿路的公用事业杆在道路安全和规划以及通信和电力分布中起着关键作用。在这方面,诸如移动地面激光扫描仪(MTLS)之类的新感测技术可以是沿着道路检测公用电杆和其他平面图的有效方法。但是,由于点云的形式由MTL收集的大量数据,需要自动化技术从该数据中提取对象。本研究提出了一种从MTLS点云自动提取实用杆的新方法。所提出的算法由三个连续的预处理步骤组成,电缆区域检测和磁极提取。 Point云首先预处理,然后基于Hough变换(HT)指定了实用电杆的候选区域。通过将水平和垂直密度信息应用​​于这些区域来提取效用极点。在采样点云中评价该方法的性能,并使用该方法在提取效用极方面实现了98%的精度。

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