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Feature Selection for ‘Orange Skin’ Type Surface Defect in Furniture Elements

  • Bartosz Świderski
  • Michał Kruk
  • Grzegorz Wieczorek
  • Jarosław Kurek
  • Katarzyna Śmietańska
  • Leszek J. Chmielewski
  • Jarosław Górski
  • Arkadiusz Orłowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10842)

Abstract

The surfaces of furniture elements having the orange skin surface defect were investigated in the context of selecting optimum features for surface classification. Features selected from a set of 50 features were considered. Seven feature selection methods were used. The results of these selections were aggregated and found consistently positive for some of the features. Among them were primarily the features based on local adaptive thresholding and on Hilbert curves used to evaluate the image brightness variability. These types of features should be investigated further in order to find the features with more significance in the problem of surface quality inspection. The groups of features which appeared least profitable in the analysis were the two features based on percolation, and the one based on Otsu global thresholding.

Keywords

Feature selection Surface defect Orange skin Detection Furniture Feature selection Brightness variability 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Applied Informatics and Mathematics – WZIMWarsaw University of Life Sciences – SGGWWarsawPoland
  2. 2.Faculty of Wood Technology – WTDWarsaw University of Life Sciences – SGGWWarsawPoland

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