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Image Retrieval by Colour and Texture Using Chromaticity Histograms and Wavelet Frames

  • Spyros Liapis
  • Georgios Tziritas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)

Abstract

In this paper the combination of texture and colour features is used for image classification. Texture features are extracted using the Discrete Wavelet Frame analysis. 2-D or 1-D histograms of the CIE Lab chromaticity coordinates are used as colour features. The 1-D histograms of the a, b coordinates were also modeled according to the generalized Gaussian distribution. The similarity measure defined on the features distribution is based on the Bhattacharya distance. Retrieval benchmarking is performed on textured colour images from natural scenes, obtained from the VisTex database of MIT Media Laboratory and from the Corel Photo Gallery.

Keywords

Texture Feature Image Retrieval Colour Feature Wavelet Frame Classi Cation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Spyros Liapis
    • 1
  • Georgios Tziritas
    • 1
  1. 1.Computer Science DepartmentUniversity of CreteHeraklionGreece

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