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ToFA: Tower frame abstraction from transmission line inspection visible video

机译:TOFA:传输线检查可见视频的塔架抽象

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Transmission Line Inspection by helicopter inspection obtains a large amount of video data, industrial applications are in urgent need of locating target tower rapidly within these video. However, using traditional object detection algorithm to extract video frame including target tower makes complete tower extraction difficulty: In ? background and face with changeable natural factors, the abstraction speed and accuracy can't meet the business needs. In this paper, a tower frame abstraction method based on transmission line inspection visible video is proposed to locate target tower rapidly. First, according to the known tower running number, obtain the corresponding latitude and longitude data of the target tower in the device and ledgers systems. Then match latitude and longitude with the synchronous telemetry data, get video segment containing the target tower. On this basis, based on the video segment, changing the color space and selecting feature channel to extract connected components, use a linear feature to locate the tower rapidly. Actual transmission line videos are used to test algorithm performance, test data includes far-focus video data, near-focus and far-focus blended video data and data with complex farm background. Detection accuracy rate is 88.2% in average, it verifies the effectiveness of the algorithm.
机译:通过直升机检测的传输线检查获得大量的视频数据,工业应用迫切需要在这些视频中快速定位目标塔。但是,使用传统的物体检测算法提取包括目标塔的视频帧,使得完整的塔提取难度:在?背景和面部具有可变的自然因素,抽象速度和准确性无法满足业务需求。本文提出了一种基于传输线检查可见视频的塔架抽象方法来快速定位目标塔。首先,根据已知的塔架运行号码,在设备和LEDGERS系统中获得目标塔的相应纬度和经度数据。然后使用同步遥测数据匹配纬度和经度,获取包含目标塔的视频段。在此基础上,基于视频段,更改色彩空间和选择要素通道以提取连接的组件,使用线性特征快速定位塔。实际传输线路视频用于测试算法性能,测试数据包括远焦焦点视频数据,近焦点和远重混合视频数据和数据与复杂的农场背景。检测精度率平均为88.2 %,它验证了算法的有效性。

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