Automated Damage Inspection of Power Transmission Towers from UAV Images

Aleixo Cambeiro Barreiro, Clemens Seibold, Anna Hilsmann, Peter Eisert, Peter Eisert

2022

Abstract

Infrastructure inspection is a very costly task, requiring technicians to access remote or hard-to-reach places. This is the case for power transmission towers, which are sparsely located and require trained workers to climb them to search for damages. Recently, the use of drones or helicopters for remote recording is increasing in the industry, sparing the technicians this perilous task. This, however, leaves the problem of analyzing big amounts of images, which has great potential for automation. This is a challenging task for several reasons. First, the lack of freely available training data and the difficulty to collect it complicate this problem. Additionally, the boundaries of what constitutes a damage are fuzzy, introducing a degree of subjectivity in the labelling of the data. The unbalanced class distribution in the images also plays a role in increasing the difficulty of the task. This paper tackles the problem of structural damage detection in transmission towers, addressing these issues. Our main contributions are the development of a system for damage detection on remotely acquired drone images, applying techniques to overcome the issue of data scarcity and ambiguity, as well as the evaluation of the viability of such an approach to solve this particular problem.

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Paper Citation


in Harvard Style

Cambeiro Barreiro A., Seibold C., Hilsmann A. and Eisert P. (2022). Automated Damage Inspection of Power Transmission Towers from UAV Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-555-5, pages 382-389. DOI: 10.5220/0010826500003124


in Bibtex Style

@conference{visapp22,
author={Aleixo Cambeiro Barreiro and Clemens Seibold and Anna Hilsmann and Peter Eisert},
title={Automated Damage Inspection of Power Transmission Towers from UAV Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2022},
pages={382-389},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010826500003124},
isbn={978-989-758-555-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Automated Damage Inspection of Power Transmission Towers from UAV Images
SN - 978-989-758-555-5
AU - Cambeiro Barreiro A.
AU - Seibold C.
AU - Hilsmann A.
AU - Eisert P.
PY - 2022
SP - 382
EP - 389
DO - 10.5220/0010826500003124