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Texture Classification Based on Lacunarity Descriptors

  • João Batista Florindo
  • Odemir Martinez Bruno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

The present work presents a novel solution to provide descriptors of a texture image with application in the classification of such images. The proposed method is based on the lacunarity measure of an image. We apply a multiscale transform over the power-law relation of lacunarity and extract the descriptors from a window of the multiscale transform selected whose limits are determined empirically. We compare the classification accuracy of the proposed method with other state-of-the-art and classical texture descriptors found in the literature. We also do a brief theoretical summary of lacunarity definition, explaining its excellent performance comprobed in the results.

Keywords

Pattern Recognition Fractal Theory Texture Descriptors Lacunarity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • João Batista Florindo
    • 1
  • Odemir Martinez Bruno
    • 1
  1. 1.Instituto de Física de São Carlos (IFSC)Universidade de São Paulo (USP)São CarlosBrazil

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