Knowledge-based power line detection for UAV surveillance and inspection systems
- Resource Type
- Conference
- Authors
- Li, Zhengrong; Liu, Yuee; Hayward, Ross; Zhang, Jinglan; Cai, Jinhai
- Source
- 2008 23rd International Conference Image and Vision Computing New Zealand Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference. :1-6 Nov, 2008
- Subject
- Signal Processing and Analysis
Computing and Processing
Bioengineering
Unmanned aerial vehicles
Surveillance
Inspection
Australia
Filters
Energy management
Vegetation mapping
Application software
Vehicle detection
Information technology
Power line detection
UAV
Hough transform
PCNN
k-means clustering
- Language
- ISSN
- 2151-2191
2151-2205
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.