Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform
Li, Zhengrong, Liu, Yuee, Walker, Rodney A., Hayward, Ross F., & Zhang, Jinglan (2009) Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform. Machine Vision and Applications, 21(5), pp. 677-686.
Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter
is developed to remove background noise and generate an
edge map prior to the Hough transform being employed to
detect straight lines. An improved Hough transform is used
by performing knowledge-based line clustering in Hough
space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.
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