International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2557

Full Length Research Paper

Image thresholding based on evolutionary algorithms

N. Razmjooy1, B. Somayeh Mousavi2*, P. Sargolzaei3 and F. Soleymani4
  1Department of Electrical Engineering, Majlesi Branch, Islamic Azad University, Isfahan, Iran. 2Department of Computer, Zahedan Branch, Islamic Azad University, Zahedan, Iran. 3Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran. 4Department of Mathematics, Zahedan Branch, Islamic Azad University, Zahedan, Iran.
Email: [email protected]

  •  Accepted: 26 September 2011
  •  Published: 30 November 2011



The objective of this paper is to propose an adaptive-evolutionary method for thresholding which is used as an artificial intelligent algorithm for image segmentation especially for object segmentation. This method employs resistant versus mixed histograms because of its suitable fitness function selection that consists of the histogram details. As things develop in the paper, three evolutionary methods known as genetic algorithm (GA), imperial competitive algorithm (ICA) and adaptive particle swarm optimization are used to minimize the error function. Finally, a powerful algorithm for image thresholding is found. The comparisons and experimental results show that this system is better than other methods particularly Otsu’s, GA and even new algorithms like ICA.


Key words: Segmentation, adaptive particle swarm optimization (APSO), genetic algorithm (GA), imperialist competitive algorithm (ICA), threshold, fitness function.