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An Efficient Technique to Detect Visual Defects in Particleboards
Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
2008 (English)In: Informatica (Vilnius), ISSN 0868-4952, E-ISSN 1822-8844, Vol. 19, no 3, 363-376 p.Article in journal (Refereed) Published
Abstract [en]

This paper is concerned with the problem of image analysis based detection of local defects embedded in particleboard surfaces. Though simple, but efficient technique developed is based on the analysis of the discrete probability distribution of the image intensity values and the 2D discrete Walsh transform. Robust global features characterizing a surface texture are extracted and then analyzed by a pattern classifier. The classifier not only assigns the pattern into the quality or detective class, but also provides the certainty value attributed to the decision. A 100% correct classification accuracy was obtained when testing the technique proposed on a set of 200 images.

Place, publisher, year, edition, pages
Vilnius: Institute of Mathematics and Cybernetics, Lithuanian Academy of Sciences , 2008. Vol. 19, no 3, 363-376 p.
Keyword [en]
defect detection, image analysis, Walsh transform
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:hh:diva-113ISI: 000259782500003Scopus ID: 2-s2.0-52449084807OAI: oai:DiVA.org:hh-113DiVA: diva2:236279
Available from: 2009-09-22 Created: 2009-09-22 Last updated: 2015-03-16Bibliographically approved

Open Access in DiVA

fulltext(1108 kB)92 downloads
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Scopushttp://www.mii.lt/informatica/pdf/INFO726.pdf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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