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Chapter 28
Contourlet Texture Retrieval Algorithm with Two Energy and Kurtosis Features

Excerpt

Contourlet texture image retrieval algorithm can achieve higher retrieval rates than wavelet ones under same structure due to much finer directional information representation than wavelet transform and have been studied by many researchers. In order to improve the retrieval rate further, a new contourlet transform based texture image retrieval system was proposed in this paper. In the system, absolute mean sub-bands energy, L2-energy and kurtosis in contourlet domain were cascaded to form feature vectors, and the similarity metric was Canberra distance. Experimental results show that this contourlet transform based image retrieval system is superior to that of the contourlet transform with absolute mean sub-bands energy and standard deviations features widely used today under the same system structure.

  • 1. Introduction
  • 2. Key Techniques of this New Contourlet Texture Image Retrieval Algorithm
  • 3. Experiment and Results
  • 4. Conclusions
  • Acknowledgements
  • References

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