Pattern Analysis and Applications

, Volume 10, Issue 4, pp 333–343 | Cite as

Integrated color, texture and shape information for content-based image retrieval

  • Ryszard S. Choraś
  • Tomasz Andrysiak
  • Michał Choraś
Theoretical Advances

Abstract

Feature extraction and the use of the features as query terms are crucial problems in content-based image retrieval (CBIR) systems. The main focus in this paper is on integrated color, texture and shape extraction methods for CBIR. We have developed original CBIR methodology that uses Gabor filtration for determining the number of regions of interest (ROIs), in which fast and effective feature extraction is performed. In the ROIs extracted, texture features based on thresholded Gabor features, color features based on histograms, color moments in YUV space, and shape features based on Zernike moments are then calculated. The features presented proved to be efficient in determining similarity between images. Our system was tested on postage stamp images and Corel photo libraries and can be used in CBIR applications such as postal services.

Keywords

Image retrieval Computer vision Feature extraction Zernike moments Texture analysis 

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Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  • Ryszard S. Choraś
    • 1
  • Tomasz Andrysiak
    • 1
  • Michał Choraś
    • 1
  1. 1.Image Processing GroupInstitute of TelecommunicationsBydgoszczPoland

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