Rotation invariant texture classification using binary filter response pattern (BFRP)

Zhenhua Guo, Lei Zhang, Dapeng Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


Using statistical textons for texture classification has shown great success recently. The maximal response 8 (MR8) method, which extracts an 8-dimensional feature set from 38 filters, is one of state-of-the-art rotation invariant texture classification methods. However, this method has two limitations. First, it require a training stage to build a texton library, thus the accuracy depends on the training samples; second, during classification, each 8-dimensional feature is assigned to a texton by searching for the nearest texton in the library, which is time consuming especially when the library size is big. In this paper, we propose a novel texton feature, namely Binary Filter Response Pattern (BFRP). It can well address the above two issues by encoding the filter response directly into binary representation. The experimental results on the CUReT database show that the proposed BFRP method achieves better classification result than MR8, especially when the training dataset is limited and less comprehensive.
Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Number of pages8
Publication statusPublished - 28 Sep 2009
Event13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany
Duration: 2 Sep 20094 Sep 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5702 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009


  • LBP
  • MR8
  • Texton
  • Texture Classification

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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