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Automatic Power Line Reconstruction from Multiple Drone Images Based on the Epipolarity

  • Oh, Jae Hong (Dept. of Civil Engineering, Korea Maritime and Ocean University) ;
  • Lee, Chang No (Dept. of Civil Engineering, Seoul National University of Science and Technology)
  • 투고 : 2018.05.09
  • 심사 : 2018.06.01
  • 발행 : 2018.06.30

초록

Electric transmission towers are facilities to transport electrical power from a plant to an electrical substation. The towers are connected using power lines that are installed with a proper sag by loosening the cable to lower the tension and to secure the sufficient clearance from the ground or nearby objects. The power line sag may extend over the tolerance due to the weather such as strong winds, temperature changes, and a heavy snowfall. Therefore the periodical mapping of the power lines is required but the poor accessibility to the power lines limit the work because most power lines are placed at the mountain area. In addition, the manual mapping of the power lines is also time-consuming either using the terrestrial surveying or the aerial surveying. Therefore we utilized multiple overlapping images acquired from a low-cost drone to automatically reconstruct the power lines in the object space. Two overlapping images are selected for epipolar image resampling, followed by the line extraction for the resampled images and the redundant images. The extracted lines from the epipolar images are matched together and reconstructed for the power lines primitive that are noisy because of the multiple line matches. They are filtered using the extracted line information from the redundant images for final power lines points. The experiment result showed that the proposed method successfully generated parabolic curves of power lines by interpolating the power lines points though the line extraction and reconstruction were not complete in some part due to the lack of the image contrast.

키워드

참고문헌

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피인용 문헌

  1. 3D Reconstruction of Power Lines Using UAV Images to Monitor Corridor Clearance vol.12, pp.22, 2018, https://doi.org/10.3390/rs12223698