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Color image segmentation using Laplacian eigenmaps

[+] Author Affiliations
Ioannis Tziakos

Queen Mary University of London, Department of Electronic Engineering, United Kingdom

Christos Theoharatos

University of Patras, Department of Physics, Electronics Laboratory, Patras 26500, Greece

Nikolaos A. Laskaris

Aristotle University of Thessaloniki, Department of Informatics, Artificial Intelligence and Information Analysis Laboratory, Thessaloniki 54124, Greece

George Economou

University of Patras, Department of Physics, Electronics Laboratory, Patras 26500, Greece

J. Electron. Imaging. 18(2), 023004 (April 21, 2009). doi:10.1117/1.3122369
History: Received April 05, 2008; Revised February 12, 2009; Accepted March 10, 2009; Published April 21, 2009
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The novel technique of Laplacian eigenmaps (LE) is studied as a means of improving the clustering-based segmentation of color images. Taking advantage of the ability of the LE algorithm to learn the actual manifold of the multivariate data, a computationally efficient scheme is introduced. After embedding the local image characteristics, extracted from overlapping regions, in a high-dimensional feature space, the skeleton of the intrinsically low-dimensional manifold is constructed using spectral graph theory. Using the LE-based dimensionality reduction technique, a low-dimensional map is computed in which the variations of the local image characteristics are presented in the context of global image variation. The nonlinear projections on this map serve as inputs to the Fuzzy C-Means (FCM) algorithm, boosting its clustering performance significantly. The final segmentation is produced by a simple labeling scheme. The application of the presented approach to color images is very encouraging and illustrates the effectiveness of the performance over alternative methods.

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© 2009 SPIE and IS&T

Citation

Ioannis Tziakos ; Christos Theoharatos ; Nikolaos A. Laskaris and George Economou
"Color image segmentation using Laplacian eigenmaps", J. Electron. Imaging. 18(2), 023004 (April 21, 2009). ; http://dx.doi.org/10.1117/1.3122369


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