Towards the Automatic Visual Monitoring of Electricity Pylons from Aerial Images

Anicetus Odo, Stephen McKenna, David Flynn, Jan Vorstius

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

Abstract

Visual inspection of electricity transmission and distribution networks relies on flying a helicopter around energized high voltage towers for image collection. The sensed data is taken offline and screened by skilled personnel for faults. This poses high risk to the pilot and crew and is highly expensive and inefficient. This paper reviews work targeted at detecting components of electricity transmission and distribution lines with attention to unmanned aerial vehicle (UAV) platforms. The potential of deep learning as the backbone of image data analysis was explored. For this, we used a new data set of high resolution aerial images of medium to low voltage electricity towers. We demonstrated that reliable classification of towers is feasible using deep learning methods with very good results.
Original languageEnglish
Title of host publicationProceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
PublisherSciTePress
Pages566-573
Number of pages8
Volume5
ISBN (Electronic)978-989-758-402-2
DOIs
Publication statusPublished - 27 Feb 2020
Event15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 2020 - Valletta, Malta
Duration: 27 Feb 202029 Feb 2020
http://www.visapp.visigrapp.org/?y=2020

Conference

Conference15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 2020
Abbreviated titleVISIGRAPP 2020
CountryMalta
CityValletta
Period27/02/2029/02/20
Internet address

Keywords

  • Electricity Pylons
  • Transfer Learning
  • Unmanned Aerial Vehicles
  • Visual Inspection

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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