DocumentCode
2949558
Title
High voltage transmission line detection for uav based routing inspection
Author
Weiran Cao ; Linlin Zhu ; Jianda Han ; Tianran Wang ; Yingkui Du
Author_Institution
Grad. Univ. of Chinese Acad. of Sci., Beijing, China
fYear
2013
fDate
9-12 July 2013
Firstpage
554
Lastpage
558
Abstract
The Hough Transform (HT), the Radon Transform (RT) and the Line Segment Detector (LSD) are the most well-known methods for line detection. But the HT and RT methods cost large computing consumption and always resulting a poor performance with many outliers. The LSD method is not effective to the real application of complex background condition. In this paper, a boundary search radon transform (BSRT) approach is proposed for high voltage transmission line detection in Unmanned Aerial Vehicle (UAV) based routing inspection. The core idea assumes that the initial point of an integral line is on one of the four image boundaries, so it isn´t always necessary to analyze all points in an image and a new line detection strategy is designed. Comparing to the HT, RT and LSD methods, our method is validated by the experimental results to be fast, efficient and reliable to complex environments.
Keywords
Hough transforms; Radon transforms; automatic optical inspection; autonomous aerial vehicles; mobile robots; power transmission lines; robot vision; telerobotics; BSRT approach; HT method; Hough transform; LSD method; RT method; UAV-based routing inspection; boundary search radon transform approach; complex background condition; high voltage transmission line detection; image boundaries; integral line; line segment detector; new line detection strategy; unmanned aerial vehicle-based routing inspection; Algorithm design and analysis; Approximation algorithms; Complexity theory; Image segmentation; Inspection; Power transmission lines; Transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics (AIM), 2013 IEEE/ASME International Conference on
Conference_Location
Wollongong, NSW
ISSN
2159-6247
Print_ISBN
978-1-4673-5319-9
Type
conf
DOI
10.1109/AIM.2013.6584150
Filename
6584150
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