An edge detection technique using hybrid ant colony optimization-genetic algorithm Hi̇bri̇d karinca koloni̇si̇ opti̇mi̇zasyonu- geneti̇k algori̇tma kullanarak kenar beli̇rleme tekni̇ǧ i̇

Gulum T. O., Erdogan A. Y., YILDIRIM T.

2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Fethiye, Mugla, Turkey, 18 - 20 April 2012 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2012.6204576
  • City: Fethiye, Mugla
  • Country: Turkey
  • Yıldız Technical University Affiliated: Yes


In this paper, an image edge detection technique based on the ant colony system (ACS) is implemented. ACS is one of the many ant algorithms of Ant Colony Optimization (ACO). The number of artificial ants, the total step number for each ant and the size of ant memory used in ACS is determined by applying genetic algorithm. Several reproductions of input image are obtained by nonlinear contrast enhancement applied to the input image. More than one image is passed through ACS and the outputs are integrated onto each other to generate one output image. A global threshold is applied to this very last image in order to obtain binary edge image. © 2012 IEEE.