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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| Vydáno v: | IEEE sensors journal Ročník 22; číslo 20; s. 1 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
15.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1530-437X, 1558-1748 |
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| Abstract | 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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| AbstractList | Power line detection plays an important role in automatic power inspection systems based on the vision sensor and unmanned aerial vehicle (UAV). 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 (PLE) algorithm based on parallel line detection and straight line stretching. The proposed algorithm first extracts the image edges by the Canny algorithm and then constructs criterion functions for PLE based on power line feature information, e.g., length, width, and direction. Finally, the information on power line location, direction, width, and so on will be combined to get the exact power line regions. In order to effectively evaluate the accuracy and efficiency of the PLE algorithm, we constructed a power line dataset for UAV inspection and proposed a PLE 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 dataset. Moreover, it is still a higher detection accuracy than the comparison methods when the power line is far away from UAV. 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. |
| Author | Miao, Naipeng Chen, Xingzhi Li, Yong Shuang, Feng Zhou, Zixuan Wang, Yuebin |
| Author_xml | – sequence: 1 givenname: Feng orcidid: 0000-0002-4733-4732 surname: Shuang fullname: Shuang, Feng organization: School of Electrical Engineering, Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Guangxi University, Guangxi, China – sequence: 2 givenname: Xingzhi surname: Chen fullname: Chen, Xingzhi organization: School of Electrical Engineering, Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Guangxi University, Guangxi, China – sequence: 3 givenname: Yong orcidid: 0000-0002-7230-3196 surname: Li fullname: Li, Yong organization: School of Electrical Engineering, Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Guangxi University, Guangxi, China – sequence: 4 givenname: Yuebin orcidid: 0000-0002-6978-4558 surname: Wang fullname: Wang, Yuebin organization: School of Land Science and Technology, China University of Geosciences, Beijing, China – sequence: 5 givenname: Naipeng surname: Miao fullname: Miao, Naipeng organization: School of Electrical Engineering, Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Guangxi University, Guangxi, China – sequence: 6 givenname: Zixuan surname: Zhou fullname: Zhou, Zixuan organization: School of Electrical Engineering, Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Guangxi University, Guangxi, China |
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| Snippet | Power line detection plays an important role in automatic power inspection systems based on the vision sensor and UAV (Unmanned Aerial Vehicle). The... Power line detection plays an important role in automatic power inspection systems based on the vision sensor and unmanned aerial vehicle (UAV). The... |
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| SubjectTerms | 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 |
| Title | PLE: Power Line Extraction Algorithm for UAV-based Power Inspection |
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