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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publication32nd European Signal Processing Conference (EUSIPCO)
PublisherIEEE
Pages631-635
Number of pages5
ISBN (Electronic)9789464593617
DOIs
Publication statusPublished - 23 Oct 2024
Event32nd European Signal Processing Conference 2024 - Lyon, France, Lyon, France
Duration: 26 Aug 202430 Aug 2024
https://eusipcolyon.sciencesconf.org/
https://eurasip.org/Proceedings/Eusipco/Eusipco2024/HTML/index.html

Conference

Conference32nd European Signal Processing Conference 2024
Abbreviated titleEUSIPCO 2024
Country/TerritoryFrance
CityLyon
Period26/08/2430/08/24
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

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