Open Access

Perceptual Dominant Color Extraction by Multidimensional Particle Swarm Optimization

  • Serkan Kiranyaz1Email author,
  • Stefan Uhlmann (EURASIP Member)1,
  • Turker Ince2 and
  • Moncef Gabbouj1
EURASIP Journal on Advances in Signal Processing20102009:451638

DOI: 10.1155/2009/451638

Received: 25 March 2009

Accepted: 7 December 2009

Published: 7 February 2010

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.

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Authors’ Affiliations

(1)
Signal Processing Department, Tampere University of Technology
(2)
Faculty of Computer Science, Izmir University of Economics

Copyright

© Serkan Kiranyaz et al. 2009

This article is published under license to BioMed Central Ltd. 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.