Abstract
Detecting surface defects on Wind Turbine Blades (WTBs) from remotely sensed images is a crucial step toward automated visual inspection. Typical object detection algorithms use standard bounding boxes to locate defects on WTBs. However, Oriented Bounding Boxes (OBBs) have been shown in cases of satellite imagery, to provide more precise localization of object regions and actual orientation. Existing WTB datasets do not depict defects using OBBs and this causes the lack of useful orientational information. In this paper, we consider OBBs for WTB surface defect detection through two publicly available datasets, introducing new annotations to the community. Base-lines were constructed on state-of-the-art rotated object detectors, demonstrating considerable promise and known gaps that can be addressed in the future. We present a comprehensive analysis of their performances including ablation study and discussions on the importance of angular disparity between OBBs.
Original language | English |
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Title of host publication | 32nd European Signal Processing Conference (EUSIPCO) |
Publisher | IEEE |
Pages | 631-635 |
Number of pages | 5 |
ISBN (Electronic) | 9789464593617 |
DOIs | |
Publication status | Published - 23 Oct 2024 |
Event | 32nd European Signal Processing Conference 2024 - Lyon, France, Lyon, France Duration: 26 Aug 2024 → 30 Aug 2024 https://eusipcolyon.sciencesconf.org/ https://eurasip.org/Proceedings/Eusipco/Eusipco2024/HTML/index.html |
Conference
Conference | 32nd European Signal Processing Conference 2024 |
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Abbreviated title | EUSIPCO 2024 |
Country/Territory | France |
City | Lyon |
Period | 26/08/24 → 30/08/24 |
Internet address |
Keywords
- UAV remote sensing
- oriented bounding boxes
- surface defect detection
- wind turbine blade
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering