Determination of the number of clusters on images from space optic-electronic observation systems using the k-means algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.282374

Keywords:

image clustering, space observation system, k-means, errors of the 1st and 2nd kind, number of clusters

Abstract

The object of research is the process of clustering images from space optical-electronic surveillance systems. The main hypothesis of the study assumed that experimental studies would make it possible to determine the number of clusters on images from space optical-electronic surveillance systems when using the k-means algorithm.

The method of clustering images from space optical-electronic surveillance systems using the k-means algorithm, unlike the known ones, implies:

– splitting the source image into Red-Green-Blue brightness channels;

– determination of the Euclidean distance between pixels;

– distribution of the entire set of image pixels into clusters;

– recalculation of "centers" of each subset;

– reassignment of new "centers" of each cluster;

– minimization of the total intracluster variance.

Experimental studies were conducted on the clustering of the original image using the k-means method at different values of k. It was established that with an increase in the value of k, the visual quality of clustering improves, and it is possible to visually determine a larger number of clusters in the images.

To determine the number of clusters, the sum of clustering errors of type 1 and 2 at different values of k was evaluated. It was established that when the value of k increases, the sum of errors of the 1st and 2nd kind initially decreases exponentially. A further increase in the value of k does not lead to a significant decrease in errors of the 1st and 2nd kind. It was established that for a typical image from the space optical-electronic observation system, the value of k in the clustering method based on the k-means algorithm should be equal to 4. At the same time, the sum of errors of the 1st and 2nd kind is 31.3 %.

Further research is directed to the development of clustering methods that reduce the sum of errors of the 1st and 2nd kind

Author Biographies

Hennadii Khudov, Ivan Kozhedub Kharkiv National Air Force University

Doctor of Technical Sciences, Professor, Head of Department

Department of Radar Troops Tactic

Oleksandr Makoveichuk, Academician Yuriy Bugay International Scientific and Technical University

Doctor of Technical Sciences, Associate Professor

Department of Computer Sciences and Software Engineering

Volodymyr Komarov, Scientific-Research Institute of Military Intelligence

Doctor of Military Sciences, Professor,  Head of Research Department

Vladyslav Khudov, Kharkiv National University of Radio Electronics

PhD, Junior Researcher

Department of Information Technology Security

Irina Khizhnyak, Ivan Kozhedub Kharkiv National Air Force University

PhD

Department of Radar Troops Tactic

Volodymyr Bashynskyi, The Central Research Institute of the Armed Forces of Ukraine

Doctor of Technical Sciences, Chief Researcher

Stanislav Stetsiv, Hetman Petro Sahaidachnyi National Army Academy

Assistant Professor

Department of Missile Forces

Yevhen Dudar, Hetman Petro Sahaidachnyi National Army Academy

Deputy Head of Department

Department of Troop Training

Andrii Rudiy, Hetman Petro Sahaidachnyi National Army Academy

Senior Lecturer

Department of Armoured Vehicles

Mykhailo Buhera, Central Scientifically-Research Institute of Armaments and Military Equipment of the Armed Forces of Ukraine

PhD, Senior Researcher

Scientific and Organizational Department

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Determination of the number of clusters on images from space optic-electronic observation systems using the k-means algorithm

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Published

2023-06-30

How to Cite

Khudov, H., Makoveichuk, O., Komarov, V., Khudov, V., Khizhnyak, I., Bashynskyi, V., Stetsiv, S., Dudar, Y., Rudiy, A., & Buhera, M. (2023). Determination of the number of clusters on images from space optic-electronic observation systems using the k-means algorithm. Eastern-European Journal of Enterprise Technologies, 3(9 (123), 60–69. https://doi.org/10.15587/1729-4061.2023.282374

Issue

Vol. 3 No. 9 (123) (2023): Information and controlling system

Section

Information and controlling system

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Copyright (c) 2023 Hennadii Khudov, Oleksandr Makoveichuk, Volodymyr Komarov, Vladyslav Khudov, Irina Khizhnyak, Volodymyr Bashynskyi, Stanislav Stetsiv, Yevhen Dudar, Andrii Rudiy, Mykhailo Buhera

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