Three-dimensional connectivity index for texture recognition

Joao Batista Florindo, Gabriel Landini, Odemir Bruno

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
130 Downloads (Pure)

Abstract

This work proposes a new method of texture analysis for grey-level images based on the distribution of connectivity indexes in local neighbourhoods. The connectivity index acts as a measure of homogeneity of textures and its distribution is computed at various local neighbourhood sizes. The resulting descriptors provide an efficient multiscale representation of connectivity at different scales. The method was tested in the classification of UIUC, Outex, and KTH-TIPS2b databases and outperformed several state-of-the-art approaches, including such as LBP, LBP+VAR, MR8, multifractals among others.
Original languageEnglish
Pages (from-to)239–244
JournalPattern Recognition Letters
Volume84
Early online date29 Sep 2016
DOIs
Publication statusPublished - Dec 2016

Keywords

  • Local connectivity
  • Texture analysis
  • Pattern recognition
  • Image classification

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