An Efficient Technique to Detect Visual Defects in Particleboards

Authors:
Jonas Guzaitis;Antanas Verikas
Affiliations:
Department of Applied Electronics, Kaunas University of Technology, LT-51368, Kaunas, Lithuania, e-mail: jonas.guzaitis@ktu.lt;Department of Applied Electronics, Kaunas University of Technology, Intelligent Systems Laboratory, Halmstad University Box 823, S-30118 Halmstad, Sweden, e-mail: antanas.verikas@hh.se
Venue:
Informatica
Year:
2008

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Abstract

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.