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Proceedings Paper

Fermat theorem and elliptic color histogram features
Author(s): Luigi Cinque; Stefano Levialdi; Alessio Malizia; F. De Rosa
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Paper Abstract

Color histograms are widely used for content-based image retrieval. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, a histogram is a coarse characterization of an image, and so images with very different appearances can have similar histograms. This is particularly important for large image databases, in which many images can have similar color histograms. We will show how to find a relationship between histograms and elliptic curves, in order to define a similarity color feature based onto parametric elliptic equations. This equations are directly involved in the Fermat's Last Theorem, thus representing a solution which is interesting in terms of theory and parametric properties.

Paper Details

Date Published: 13 January 2003
PDF: 7 pages
Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); doi: 10.1117/12.472834
Show Author Affiliations
Luigi Cinque, Univ. degli Studi di Roma La Sapienza (Italy)
Stefano Levialdi, Univ. degli Studi di Roma La Sapienza (Italy)
Alessio Malizia, Univ. degli Studi di Roma La Sapienza (Italy)
F. De Rosa, Univ. degli Studi di Roma La Sapienza (Italy)

Published in SPIE Proceedings Vol. 5010:
Document Recognition and Retrieval X
Tapas Kanungo; Elisa H. Barney Smith; Jianying Hu; Paul B. Kantor, Editor(s)

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