SpringerOpen Newsletter

Receive periodic news and updates relating to SpringerOpen.

Open Access Research Article

Perceptual Dominant Color Extraction by Multidimensional Particle Swarm Optimization

Serkan Kiranyaz1*, Stefan Uhlmann1, Turker Ince2 and Moncef Gabbouj1

Author Affiliations

1 Signal Processing Department, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland

2 Faculty of Computer Science, Izmir University of Economics, 35330 Izmir, Turkey

For all author emails, please log on.

EURASIP Journal on Advances in Signal Processing 2009, 2009:451638  doi:10.1155/2009/451638


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2009/1/451638


Received:25 March 2009
Revisions received:20 September 2009
Accepted:7 December 2009
Published:7 February 2010

© 2009 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Color is the major source of information widely used in image analysis and content-based retrieval. Extracting dominant colors that are prominent in a visual scenery is of utmost importance since the human visual system primarily uses them for perception and similarity judgment. In this paper, we address dominant color extraction as a dynamic clustering problem and use techniques based on Particle Swarm Optimization (PSO) for finding optimal (number of) dominant colors in a given color space, distance metric and a proper validity index function. The first technique, so-called Multidimensional (MD) PSO can seek both positional and dimensional optima. Nevertheless, MD PSO is still susceptible to premature convergence due to lack of divergence. To address this problem we then apply Fractional Global Best Formation (FGBF) technique. In order to extract perceptually important colors and to further improve the discrimination factor for a better clustering performance, an efficient color distance metric, which uses a fuzzy model for computing color (dis-) similarities over HSV (or HSL) color space is proposed. The comparative evaluations against MPEG-7 dominant color descriptor show the superiority of the proposed technique.

Publisher note

To access the full article, please see PDF.