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Color-Based Classification of Natural Rock Images Using Classifier Combinations

  • Leena Lepistö
  • Iivari Kunttu
  • Ari Visa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

Abstract

Color is an essential feature that describes the image content and therefore colors occurring in the images should be effectively characterized in image classification. The selection of the number of the quantization levels is an important matter in the color description. On the other hand, when color representations using different quantization levels are combined, more accurate multilevel color description can be achieved. In this paper, we present a novel approach to multilevel color description of natural rock images. The description is obtained by combining separate base classifiers that use image histograms at different quantization levels as their inputs. The base classifiers are combined using classification probability vector (CPV) method that has proved to be an accurate way of combining classifiers in image classification.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Leena Lepistö
    • 1
  • Iivari Kunttu
    • 1
  • Ari Visa
    • 1
  1. 1.Institute of Signal ProcessingTampere University of TechnologyTampereFinland

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