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Research on Visual Detection Methods and Development Trends of Surface Defects of Urban Tunnels

  • Geng Xu
  • , Mingxin Gao
  • , Feng Liu
  • , Yang Liu*
  • *Corresponding author for this work

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

Abstract

The detection of surface defects in urban tunnels is a key focus of safety operations and maintenance. Structural surface defect detection has gone through three key phases: manual visual inspection phase, manual instrumental inspection phase, and image visual perception phase, with most current studies focusing on the third phase. This paper analyses the current situation and problems of existing surface defects detection technologies at two levels: Traditional image processing and intelligent machine vision perception. Correspondingly, future trends in surface defect detection techniques for urban tunnels are discussed, which provide solutions for the development of intelligent perception of the structural safety status of urban tunnels.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Prognostics and Health Management, ICPHM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages291-295
Number of pages5
ISBN (Electronic)9798350346251
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 IEEE International Conference on Prognostics and Health Management, ICPHM 2023 - Montreal, Canada
Duration: 5 Jun 20237 Jun 2023

Publication series

Name2023 IEEE International Conference on Prognostics and Health Management, ICPHM 2023

Conference

Conference2023 IEEE International Conference on Prognostics and Health Management, ICPHM 2023
Country/TerritoryCanada
CityMontreal
Period5/06/237/06/23

Keywords

  • Computer Vision
  • Convolutional Neural Networks
  • Deep Learning
  • Defect detection
  • Image Processing

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