Open AccessComparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony
Author(s) -
Hennadii Khudov,
Irina Khizhnyak
Publication year - 2021
Publication title -
sistemi obrobki ìnformacìï
Language(s) - English
Resource type - Journals
eISSN - 2518-1696
pISSN - 1681-7710
DOI - 10.30748/soi.2021.164.11
Subject(s) - ant colony optimization algorithms , swarm intelligence , segmentation , artificial intelligence , artificial bee colony algorithm , computer science , swarm behaviour , image segmentation , ant colony , pattern recognition (psychology) , computer vision , metaheuristic , particle swarm optimization , machine learning
The article discusses the methods of swarm intelligence, namely, an improved method based on the ant colony optimization and the method of an artificial bee colony. The goal of the work is to carry out a comparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony. Segmentation of tonal optical-electronic images was carried out using the proposed methods of swarm intelligence. The results of the segmentation of optical-electronic images obtained from the spacecraft are presented. A visual assessment of the quality of segmentation results was carried out using improved methods. The classical errors of the first and second kind of segmentation of optoelectronic images are calculated for the proposed methods of swarm intelligence and for known segmentation methods. The features of using each of the proposed methods of swarm intelligence are determined. The tasks for which it is better to use each of the proposed methods of swarm intelligence are determined.