Akademik Veri Yönetim Sistemi
International Cumhuriyet Artificial Intelligence Applications Conference, CAIAC 2021, Sivas, Türkiye, 3 - 04 Aralık 2021, ss.1-5
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.