Abstract
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<p>This paper is concerned with the … <p>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.</p>proposed on a set of 200 images.</p>
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Author
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Jonas Guzaitis +
, Antanas Verikas +
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Diva
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http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:236279
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EndPage
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376 +
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Issue
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3 +
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Journal
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Informatica (Vilnius) +
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PublicationType
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Journal Paper +
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Publisher
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Institute of Mathematics and Cybernetics, Lithuanian Academy of Sciences +
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StartPage
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363 +
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Title
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An Efficient Technique to Detect Visual Defects in Particleboards +
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Volume
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19 +
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Year
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2008 +
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Has queryThis property is a special property in this wiki.
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Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
, Publications:An Efficient Technique to Detect Visual Defects in Particleboards +
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Categories |
Publication +
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Modification dateThis property is a special property in this wiki.
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30 September 2016 20:42:24 +
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