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Proceedings Paper

Similarity of color images
Author(s): Markus Andreas Stricker; Markus Orengo
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Paper Abstract

We describe two new color indexing techniques. The first one is a more robust version of the commonly used color histogram indexing. In the index we store the cumulative color histograms. The L1-, L2-, L(infinity )-distance between two cumulative color histograms can be used to define a similarity measure of these two color distributions. We show that this method produces slightly better results than color histogram methods, but it is significantly more robust with respect to the quantization parameter of the histograms. The second technique is an example of a new approach to color indexing. Instead of storing the complete color distributions, the index contains only their dominant features. We implement this approach by storing the first three moments of each color channel of an image in the index, i.e., for a HSV image we store only 9 floating point numbers per image. The similarity function which is used for the retrieval is a weighted sum of the absolute differences between corresponding moments. Our tests clearly demonstrate that a retrieval based on this technique produces better results and runs faster than the histogram-based methods.

Paper Details

Date Published: 23 March 1995
PDF: 12 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205308
Show Author Affiliations
Markus Andreas Stricker, Swiss Federal Institute of Technology (Switzerland)
Markus Orengo, Swiss Federal Institute of Technology (Switzerland)

Published in SPIE Proceedings Vol. 2420:
Storage and Retrieval for Image and Video Databases III
Wayne Niblack; Ramesh C. Jain, Editor(s)

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