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ANN and ICA sparse code shrinkage de-noising based defect detection in pavement tiles
Kaunas Univ Technol, Dept Appl Elect, Kaunas, Lithuania.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
2008 (English)In: Information Technologies' 2008, Proceedings, Kaunas, Lithuania: Kaunas University of Technology Press , 2008, p. 62-71Conference paper, Published paper (Refereed)
Abstract [en]

This paper is concerned with the problem of image analysis based detection of local defects embedded in pavement tiles surfaces. The technique developed is based on the ICA sparse code shrinkage denoising, the local 2D discrete Walsh transform and ANN. To reduce random noise, the ICA sparse code shrinkage de-noising is applied. Next, robust local features characterizing the surface texture are extracted based on the 2D Walsh transform and then analyzed by an artificial Neural Network. A 100% correct classification rate was obtained when testing the technique proposed on a set of surface images recorded from 400 tiles.

Place, publisher, year, edition, pages
Kaunas, Lithuania: Kaunas University of Technology Press , 2008. p. 62-71
Series
Information Technologies Conference Proceedings, ISSN 2029-0020
Keywords [en]
ANN, ICA, sparse code shrinkage
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:hh:diva-2717ISI: 000257510600008Local ID: 2082/3119OAI: oai:DiVA.org:hh-2717DiVA, id: diva2:239935
Conference
14th International Conference on Information and Software Technologies, IT 2008, Kaunas, Lithuania, April 24-25, 2008
Available from: 2009-07-06 Created: 2009-07-06 Last updated: 2025-02-07Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf