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Histogram compression and image retrieval through Padua points interpolation

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Colour has proved to be a very powerful feature for image indexing. There are many examples of image retrieval systems based on colour or chromaticity histograms in the literature, following on from the histogram intersection method of Swain and Ballard. Here we propose a compact representation of the chromaticity histogram that achieves very good performance in image retrieval. Specifically, we use a new type of polynomial interpolation in two variables, which relies on the Padua points as interpolation nodes. What we obtain is a vector of coefficients, that represents the interpolation polynomial and is “characteristic” for an image, and that can be compared to the corresponding vectors of other images. Experiments show that our new compact Padua point representation supports excellent indexing and recognition.
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Document Type: Research Article

Publication date: January 1, 2008

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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