Real-time Power Line Detection Network using Visible Light and Infrared Images

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

In the electrical industry, power line detection is an important task for safety of autonomous drone, which assists inspection of the electrical facilities. In this paper, we proposed real-time power line detection network, which is based on deep learning. Building on existing fast segmentation convolutional neural network (Fast-SCNN), which showed competitive performance with fast processing time for image segmentation, we modified its classifier part by inserting additional convolution layers and transposed convolution layer to improve the performance. Furthermore, unlike previous studies that utilized one-kind of sensor image, stacked four-channel image of visual light (VL) and contrast enhanced infrared (IR) were introduced as an input of our modified network. Experimental results on our model showed that the mean intersection over union of multi sensor image (VL+IR) was 6.7% value higher than the Fast-SCNN with single sensor image (VL) and real-time processing speed of 24 frames per second on the drone captured outdoor dataset.

Original languageEnglish
Title of host publication2019 International Conference on Image and Vision Computing New Zealand, IVCNZ 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728141879
DOIs
StatePublished - Dec 2019
Event2019 International Conference on Image and Vision Computing New Zealand, IVCNZ 2019 - Dunedin, New Zealand
Duration: 2 Dec 20194 Dec 2019

Publication series

NameInternational Conference Image and Vision Computing New Zealand
Volume2019-December
ISSN (Print)2151-2191
ISSN (Electronic)2151-2205

Conference

Conference2019 International Conference on Image and Vision Computing New Zealand, IVCNZ 2019
Country/TerritoryNew Zealand
CityDunedin
Period2/12/194/12/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Deep learning
  • Infrared image
  • Power line detection
  • Real-time
  • Segmentation

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