Devising a method for segmenting images acquired from space optical and electronic observation systems based on the Sine-Cosine algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.265775

Keywords:

image segmentation, space optoelectronic surveillance system, Sine-Cosine algorithm

Abstract

The object of this study is the process of segmentation of images acquired from space optoelectronic surveillance systems. The method to segment images from space optoelectronic surveillance systems based on the Sine-Cosine algorithm involves determining the threshold level; unlike the known ones, the following is carried out in it:

– preliminary selection of red-green-blue color space brightness channels in the original image;

– calculation of the maximum distance of movement of agents in the image in each brightness channel;

– calculation of the values that determine the movement of agents in the image in each brightness channel;

– determining the position of agents in the image using trigonometric functions of the sine and cosine in each brightness channel.

An experimental study into segmenting images acquired from space optoelectronic surveillance systems based on the Sine-Cosine algorithm was carried out. It was found that the improved method of image segmentation based on the Sine-Cosine algorithm makes it possible to segment the images. In this case, objects of interest, snow-covered objects of interest, background objects, and undefined areas of the image (anomalous areas) are identified.

The quality of image segmentation was assessed using the Sine-Cosine algorithm-based method. It was found that the improved segmentation method based on the Sine-Cosine algorithm reduces the segmentation error of the first kind by an average of 21 % and the segmentation error of the first kind by an average of 17 %.

Methods of image segmentation can be implemented in software and hardware systems that process images acquired from space optoelectronic surveillance systems.

Further studies may involve comparing the quality of segmentation by the method based on the Sine-Cosine algorithm with segmentation methods based on evolutionary algorithms (for example, genetic ones).

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

Vladyslav Khudov, Kharkiv National University of Radio Electronics

PhD, Junior Researcher

Department of Information Technology Security

Volodymyr Maliuha, Ivan Kozhedub Kharkiv National Air Force University

Doctor of Military Sciences, Associate Professor, Head of Department

Department of Anti-Aircraft Missile Forces Tactic

Anatolii Andriienko, Hetman Petro Sahaidachnyi National Army Academy

PhD, Senior Research

Department of Automobiles and Automobile Industry

Yevhen Tertyshnik, State Scientific Research Institute of Armament and Military Equipment Testing and Certification

Senior Researcher

Department of Scientific Research

Viktor Pashchenko, National Academy of the National Guard of Ukraine

PhD, Senior Lecturer

Department of Tactics

Dmytro Parashchuk, Hetman Petro Sahaidachnyi National Army Academy

PhD, Senior Lecturer

Department of Automobiles and Automobile Industry

Irina Khizhnyak, Ivan Kozhedub Kharkiv National Air Force University

PhD

Department of Radar Troops Tactic

Temir Kalimulin, Ivan Kozhedub Kharkiv National Air Force University

Adjunct

Department of Radar Troops Tactic

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Devising a method for segmenting images acquired from space optical and electronic observation systems based on the Sine-Cosine algorithm

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Published

2022-10-27

How to Cite

Khudov, H., Makoveichuk, O., Khudov, V., Maliuha, V., Andriienko, A., Tertyshnik, Y., Pashchenko, V., Parashchuk, D., Khizhnyak, I., & Kalimulin, T. (2022). Devising a method for segmenting images acquired from space optical and electronic observation systems based on the Sine-Cosine algorithm . Eastern-European Journal of Enterprise Technologies, 5(9(119), 17–24. https://doi.org/10.15587/1729-4061.2022.265775

Issue

Vol. 5 No. 9(119) (2022): Information and controlling system

Section

Information and controlling system

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Copyright (c) 2022 Hennadii Khudov, Oleksandr Makoveichuk, Vladyslav Khudov, Volodymyr Maliuha, Anatolii Andriienko, Yevhen Tertyshnik, Viktor Pashchenko, Dmytro Parashchuk, Irina Khizhnyak, Temir Kalimulin

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