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Proceedings Paper

Quantitative evaluation of color image segmentation results using fuzzy neural network
Author(s): Didier Coquin
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Paper Abstract

In this paper we consider the problem of the automatic evaluation of the results of color image segmentation. There are supervised evaluation criteria based on the computation of the dissimilarity measure between segmentation result and ground truth. Also, there are unsupervised evaluation criteria that enable the quality of a segmentation result without any a priori knowledge. Here, starting from the criteria, we retained six attributes which are summarized in a performance vector and will be used for an evaluation based on a fuzzy neural network.

Paper Details

Date Published: 17 November 2008
PDF: 8 pages
Proc. SPIE 7266, Optomechatronic Technologies 2008, 72661G (17 November 2008); doi: 10.1117/12.807286
Show Author Affiliations
Didier Coquin, LISTIC, Domaine Univ. (France)

Published in SPIE Proceedings Vol. 7266:
Optomechatronic Technologies 2008
John T. Wen; Dalibor Hodko; Yukitoshi Otani; Jonathan Kofman; Okyay Kaynak, Editor(s)

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