Segmentation of Histological Images using Artificial Bee Colony Algorithm

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Warsame K. M., Kurban R., Durmuş A.

International Cumhuriyet Artificial Intelligence Applications Conference, CAIAC 2021, Sivas, Turkey, 3 - 04 December 2021, pp.1-5

  • Publication Type: Conference Paper / Full Text
  • City: Sivas
  • Country: Turkey
  • Page Numbers: pp.1-5
  • Abdullah Gül University Affiliated: No


Image segmentation is an important topic in image processing. Various algorithms are proposed for segmentation of medical images. In this paper, we study 3 methods for color image segmentation, particularly histological images stained with Hematoxylin and Eosin. Color image segmentation is a process of extracting information from the images more connected regions satisfying uniformity criterion which is based on features derived from spectral component. Color images provide more information than gray version of it. In this paper, images obtained from the literature are segmented by K-means, fuzzy C-means and artificial bee colony (ABC) algorithm based iterative Euclidean distance minimization. Experiments are conducted both on RGB color spaces and Lab color spaces. Experimental analyses show that methods achieve successful segmentation results.