Knowledge-based power line detection for UAV surveillance and inspection systems

Li, Zhengrong, Liu, Yuee, Hayward, Ross F., Zhang, Jinglan, & Cai, Jinhai (2008) Knowledge-based power line detection for UAV surveillance and inspection systems. In Proceedings of The 23rd International Conference on Image and Vision Computing New Zealand, IEEE, Christchurch, New Zealand.

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Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in the automatic surveillance of electrical power infrastructure. For an automatic vision based power line inspection system, detecting power lines from cluttered background an important and challenging task. In this paper, we propose a knowledge-based power line detection method for a vision based UAV surveillance and inspection system. A PCNN filter is developed to remove background noise from the images prior to the Hough transform being employed to detect straight lines. Finally knowledge based line clustering is applied to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective.

Impact and interest:

11 citations in Scopus
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ID Code: 16731
Item Type: Conference Paper
Refereed: Yes
Keywords: Power line detection, PCNN, Hough transform, k-means clustering, UAV
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2008 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 09 Dec 2008 22:35
Last Modified: 29 Feb 2012 13:46

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