Optimizing Wind Turbine Surface Defect Detection: A Rotated Bounding Box Approach

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 sat...

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Bibliographic Details
Published in2024 32nd European Signal Processing Conference (EUSIPCO) pp. 631 - 635
Main Authors Gohar, Imad, Halimi, Abderrahim, Yew, Weng Kean, See, John
Format Conference Proceeding
LanguageEnglish
Published European Association for Signal Processing - EURASIP 26.08.2024
Subjects
Defect detection
Location awareness
oriented bounding boxes
Reliability
Remote sensing
Satellite images
Signal processing
Soft sensors
surface defect detection
UAV remote sensing
Visualization
wind turbine blade
Wind turbines
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Summary: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.
ISSN:2076-1465