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Gabor Filter-Based Texture Features to Archaeological Ceramic Materials Characterization

  • Mohamed Abadi
  • Majdi Khoudeir
  • Sylvie Marchand
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

This paper presents a self-learning system for automatic texture characterization and classification on ceramic pastes or fabrics and surfaces. The system uses Gabor filter as pre-processing methods with feature extraction possibilities. On these features it applies a linear discriminant analysis (LDA) and k-nearest neighbor classifiers (k-NN) with its best parameters. Experimental results of the recognition ceramic materials, deals on the field and in the laboratory, for different ceramic pastes and surfaces show a good accuracy and applicability of the process on this type of data.

Keywords

Egyptian ceramic materials ceramic fabrics and surface texture characterization feature extraction classification algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohamed Abadi
    • 1
  • Majdi Khoudeir
    • 1
  • Sylvie Marchand
    • 2
  1. 1.XLIM-SIC DepartmentUMR CNRS 6172Chasseneuil-FuturoscopeFrance
  2. 2.Institut français d’archéologie orientaleCairoEgypt

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