Texture classification based on lacunarity descriptors

  • Authors:
  • João Batista Florindo;Odemir Martinez Bruno

  • Affiliations:
  • Instituto de Física de São Carlos (IFSC), Universidade de São Paulo (USP), São Carlos, SP, Brazil;Instituto de Física de São Carlos (IFSC), Universidade de São Paulo (USP), São Carlos, SP, Brazil

  • Venue:
  • ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
  • Year:
  • 2012

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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.