13 January 2003 Fermat theorem and elliptic color histogram features
Author Affiliations +
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luigi Cinque, Luigi Cinque, Stefano Levialdi, Stefano Levialdi, Alessio Malizia, Alessio Malizia, F. De Rosa, F. De Rosa, } "Fermat theorem and elliptic color histogram features", Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); doi: 10.1117/12.472834; https://doi.org/10.1117/12.472834
PROCEEDINGS
7 PAGES


SHARE
RELATED CONTENT

Content-based image retrieval
Proceedings of SPIE (February 26 2010)
Image retrieval by using subpiece accumulative histogram
Proceedings of SPIE (September 25 2001)
A lightweight image retrieval system for paintings
Proceedings of SPIE (January 16 2005)

Back to Top