Cell histograms versus color histograms for image representation and retrieval

  • Authors:

  • Renato O. Stehling;Mario A. Nascimento;Alexandre X. Falcão

  • Affiliations:

  • Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil;Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada;Institute of Computing, University of Campinas, Campinas, São Paulo, Brazil

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2003

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Abstract

This paper presents a new approach for content-based image retrieval, which is based on the well-known and widely used color histograms. Previous approaches have used a single global color histogram (GCH) for the whole image, or local color histograms (LCHs) for cells within a grid of fixed size. Our approach is also based on a grid of cells, but unlike the latter it uses a cell histogram for each of the colors actually present in the images, representing how that color is distributed among the image cells - hence the name Cell/Color Histograms. Our experiments have shown that the actual number of colors present in images is often low. Thus we are able to achieve performance comparable to using LCHs within a grid, but with a much smaller space overhead. Furthermore, the proposed approach is very flexible in the sense that the user has alternative ways to calibrate the trade-off between space overhead and retrieval effectiveness. In fact, we have been able to outperform GCHs (typically a compact representation) in terms of effectiveness requiring less storage space.