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An efficient color image classification method using gradient magnitude based angle cooccurrence matrix

  • Rui Zhang*
  • , Baolin Yin
  • , Qiyang Zhao
  • , Bin Yang
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a novel texture feature GMACM, is presented according to the statistics of gradient angle cooccurrence in color images. Based on three different types of gradients defined in the RGB space, the corresponding GMACMs are introduced. With some well-designed color image classification experiments, it is shown that GMACMs outperform GLCM and Gabor filters significantly in efficiency and accuracy. It could be concluded that GMACM is powerful in classifying and understand color images.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages1073-1076
Number of pages4
DOIs
StatePublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong SAR
Duration: 26 Sep 201029 Sep 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong SAR
CityHong Kong
Period26/09/1029/09/10

Keywords

  • Cooccurrence matrix
  • GMACM
  • Gradient
  • Image classification

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