PLE: Power Line Extraction Algorithm for UAV-based Power Inspection

Power line detection plays an important role in automatic power inspection systems based on the vision sensor and UAV (Unmanned Aerial Vehicle). The positioning of the power line is essential to assist in planning and navigation along the power line during the UAV-based power inspection process. For...

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Bibliographic Details
Published in:IEEE sensors journal Vol. 22; no. 20; p. 1
Main Authors: Shuang, Feng, Chen, Xingzhi, Li, Yong, Wang, Yuebin, Miao, Naipeng, Zhou, Zixuan
Format: Journal Article
Language:English
Published: New York IEEE 15.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Autonomous aerial vehicles
Data mining
Datasets
Electrocutions
Feature extraction
Image edge detection
Image segmentation
Inspection
parallel line detection
power inspection
power line
Power lines
Straight lines
Transforms
UAV
Unmanned aerial vehicles
ISSN:1530-437X, 1558-1748
Online Access:Get full text
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Summary:Power line detection plays an important role in automatic power inspection systems based on the vision sensor and UAV (Unmanned Aerial Vehicle). The positioning of the power line is essential to assist in planning and navigation along the power line during the UAV-based power inspection process. For the along-line inspection problem of UAV power inspection, we developed a power line extraction algorithm based on parallel line detection and the straight line stretching. The proposed algorithm first extracts the image edges by Canny algorithm, and then constructs criterion functions for power line extraction based on power line feature information e.g. length, width and direction. Finally, the information on power line location, direction, width, etc. will be combined to get the exact power line regions. In order to effectively evaluate the accuracy and efficiency of the power line extraction algorithm, we constructed a power line dataset for UAV inspection and proposed a power line extraction effect evaluation method. The experimental results demonstrate that the proposed method can effectively reduce the influence of ground environment and other interference factors. Compared with other methods, the proposed algorithm is significantly better than the comparison methods in detecting power lines for the constructed data set. Moreover, it is still a higher detection accuracy than the comparison methods when the power line is far away from UAV.
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ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3202033