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An efficient color representation for image retrieval.

Y Deng1, B S Manjunath, C Kenney

  • 1Hewlett-Packard Laboratories, Palo Alto, CA 94304, USA. deng@hpl.hp.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
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This study introduces a new compact color descriptor and indexing method for efficient image retrieval. It enables faster searching in large image databases by representing colors effectively.

Area of Science:

  • Computer Vision
  • Image Processing
  • Information Retrieval

Background:

  • Traditional color histograms face high-dimensional indexing challenges in large image databases.
  • Efficient similarity retrieval in large image datasets remains a significant computational problem.

Purpose of the Study:

  • To develop a compact color descriptor for efficient similarity retrieval in large image databases.
  • To introduce an effective indexing method for the proposed color descriptor.

Main Methods:

  • Colors in image regions are clustered into representative colors and their percentages.
  • A novel feature descriptor is created using representative colors and their distribution.
  • A similarity measure analogous to quadratic color histogram distance is defined.

Related Experiment Videos

  • Indexing is performed in a three-dimensional (3-D) color space to avoid high dimensionality.

    • Main Results:

    • The proposed descriptor effectively represents color information in image regions.
    • The indexing scheme allows for fast similarity retrieval.
    • Experimental results demonstrate favorable comparison with traditional color histograms in computational complexity.

    Conclusions:

    • The compact color descriptor and its indexing method offer an efficient solution for image similarity retrieval.
    • This approach addresses the limitations of traditional color histograms in large-scale applications.
    • The method provides a computationally efficient alternative for color-based image database searching.