Texture image classification using complex texton

Zhenhua Guo, Qin Li, Lin Zhang, Jia You, Wenhuang Liu, Jinghua Wang

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


Statistical textons has shown its potential ability in texture image classification. The maximal response 8 (MR8) method extracts an 8-dimensional feature set from 38 filters. It is one of state-of-the-art rotation invariant texture classification methods. This method assumes that each local patch has a dominant orientation, thus it keeps the maximal response from six responses of different orientations in the same scale. To validate whether local dominant orientation is necessary for texture classification, in this paper, a complex texton, complex response 8 (CR8), is proposed. The average and standard deviation of filter responses for different orientations is computed, and then an 8-dimensional complex texton is extracted. After using k-means clustering algorithm to learn a texton dictionary, a histogram of texton distribution could be built for a given image. Experimental results on one large public database show that CR8 could get comparable results with MR8.
Original languageEnglish
Title of host publicationAdvanced Intelligent Computing Theories and Applications
Subtitle of host publicationWith Aspects of Artificial Intelligence - 7th International Conference, ICIC 2011 - Revised Selected Papers
Number of pages7
Publication statusPublished - 1 Dec 2011
Event7th International Conference on Intelligent Computing, ICIC 2011 - Zhengzhou, China
Duration: 11 Aug 201114 Aug 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6839 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Conference on Intelligent Computing, ICIC 2011


  • clustering
  • maximal response 8
  • texton
  • Texture classification

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science


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