Wavelet domain detection of rust in steel bridge images

Sindhu Ghanta, Tanja Karp, Sangwook Lee

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

25 Scopus citations

Abstract

This paper describes the detection of rust defects on highway steel bridges, which are one of the most commonly observed defects on coating surfaces and thus have to be taken care of appropriately since they severely affect the structural integrity of bridges. A rust defect assessment method is presented that automatically detects the percentage of rust in a given digital image of bridge surface taken from a conventional digital camera. A training and detection algorithm is implemented to classify a given block of the image as rust or non-rust. The results of the algorithm are analyzed for its efficiency and possible optimization techniques are suggested.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages1033-1036
Number of pages4
DOIs
StatePublished - 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: May 22 2011May 27 2011

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Country/TerritoryCzech Republic
CityPrague
Period05/22/1105/27/11

Keywords

  • Rust detection
  • bridges
  • classification
  • digital image processing
  • discrete wavelet transform

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