By Topic

Color image segmentation using automatic thresholding and the fuzzy C-means techniques

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ben Chaabane, S. ; SICISI, Ecole Super. des Sci. et Tech. de Tunis (ESSTT), Tunis ; Sayadi, M. ; Fnaiech, F. ; Brassart, E.

In this paper, a color image segmentation approach based on automatic histogram thresholding and the fuzzy C-means (FCM) techniques is presented. The originality of this work remains in using thresholding and clustering techniques together for color image segmentation. The histogram considers the occurrence of the gray levels among pixels. In a first stage, the thresholding histogram is used for finding all major homogenous areas. In order to reduce the computational burden required by the fuzzy C-means, the coarse-fine concept methodology is used. The thresholding technique is used for the coarsely segmentation. After the coarse step, and in order to refine further the segmentation of the assigned pixels which remain unclassified, the fuzzy C-means technique is then applied. The experimental results show that the proposed approach can find homogeneous areas effectively, and can solve the problem of discriminating shading in color images to some extent.

Published in:

Electrotechnical Conference, 2008. MELECON 2008. The 14th IEEE Mediterranean

Date of Conference:

5-7 May 2008