Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems

The paper presents the results of the study of a two-stage procedure for selecting a reference object in the current image formed by a correlation-extreme system used for autonomous navigation of unmanned aerial vehicles. The aim of this paper is to theoretically evaluate the probability of selectin...

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Main Authors: Udovenko S., Tiurina V., Boychenko O., Breus P., Onishchenko Yu., Gnusov Yu., Svitlychnyi V.
Format: Article
Language:English
Published: Academy of Sciences of Moldova 2023-11-01
Series:Problems of the Regional Energetics
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Online Access:https://journal.ie.asm.md/assets/files/03_04_60_2023.pdf
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author Udovenko S.
Tiurina V.
Boychenko O.
Breus P.
Onishchenko Yu.
Gnusov Yu.
Svitlychnyi V.
author_facet Udovenko S.
Tiurina V.
Boychenko O.
Breus P.
Onishchenko Yu.
Gnusov Yu.
Svitlychnyi V.
author_sort Udovenko S.
collection DOAJ
description The paper presents the results of the study of a two-stage procedure for selecting a reference object in the current image formed by a correlation-extreme system used for autonomous navigation of unmanned aerial vehicles. The aim of this paper is to theoretically evaluate the probability of selecting low-dimensional low-contrast objects in the segmented current image according to the proposed two-stage procedure. To achieve this goal, the problem of segmentation of images of the sighting surface and subsequent selection of the reference object in the presence of heterogeneous objects differing in brightness and area characteristics is solved. The most significant result is the justification of application of two-stage procedure of selection of the reference object in the current image by brightness and area parameters using the set thresholds. The significance of the obtained results consists in establishing the dependence of the probability of correct selection of the reference object on the noise level of the current images. It is shown that the probability of correct selection of the object in the image is a function of the threshold value and can be maximised by choosing its value. This approach allows to consider the influence of various factors leading to image noise on the quality of images formed by the navigation system. It is shown that when noise distorts more than 31% of the image pixels, the proposed two-stage procedure allows to ensure the selection of the reference object in the image with a probability not lower than 0.9.
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spelling doaj-art-3b6ef6a4b8394064b8482eb94788aa762025-08-20T02:52:56ZengAcademy of Sciences of MoldovaProblems of the Regional Energetics1857-00702023-11-01604304210.52254/1857-0070.2023.4-60.03Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems Udovenko S.0https://orcid.org/0000-0001-5945-8647Tiurina V. 1Boychenko O.2Breus P.3Onishchenko Yu.4Gnusov Yu. 5Svitlychnyi V.6Simon Kuznets Kharkiv National University of Economics, Kharkiv, UkraineKharkiv National Air Force University named after Ivan Kozhedub, Kharkiv, Ukraine State Scientific Research Institute of Armament and Military Equipment Testing and Certification, Cherkasy, Ukraine Flight Academy of the National Aviation University, Kropyvnytskyi, UkraineKharkiv National University of Internal Affairs, Kharkiv, UkraineKharkiv National University of Internal Affairs, Kharkiv, UkraineKharkiv National University of Internal Affairs, Kharkiv, UkraineThe paper presents the results of the study of a two-stage procedure for selecting a reference object in the current image formed by a correlation-extreme system used for autonomous navigation of unmanned aerial vehicles. The aim of this paper is to theoretically evaluate the probability of selecting low-dimensional low-contrast objects in the segmented current image according to the proposed two-stage procedure. To achieve this goal, the problem of segmentation of images of the sighting surface and subsequent selection of the reference object in the presence of heterogeneous objects differing in brightness and area characteristics is solved. The most significant result is the justification of application of two-stage procedure of selection of the reference object in the current image by brightness and area parameters using the set thresholds. The significance of the obtained results consists in establishing the dependence of the probability of correct selection of the reference object on the noise level of the current images. It is shown that the probability of correct selection of the object in the image is a function of the threshold value and can be maximised by choosing its value. This approach allows to consider the influence of various factors leading to image noise on the quality of images formed by the navigation system. It is shown that when noise distorts more than 31% of the image pixels, the proposed two-stage procedure allows to ensure the selection of the reference object in the image with a probability not lower than 0.9.https://journal.ie.asm.md/assets/files/03_04_60_2023.pdfcorrelation-extremal navigation systemunmanned aerial vehiclesinformation featuresimage segmentation methoddecision function.
spellingShingle Udovenko S.
Tiurina V.
Boychenko O.
Breus P.
Onishchenko Yu.
Gnusov Yu.
Svitlychnyi V.
Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
Problems of the Regional Energetics
correlation-extremal navigation system
unmanned aerial vehicles
information features
image segmentation method
decision function.
title Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
title_full Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
title_fullStr Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
title_full_unstemmed Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
title_short Segmentation of Images Used in Unmanned Aerial Vehicles Navigation Systems
title_sort segmentation of images used in unmanned aerial vehicles navigation systems
topic correlation-extremal navigation system
unmanned aerial vehicles
information features
image segmentation method
decision function.
url https://journal.ie.asm.md/assets/files/03_04_60_2023.pdf
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AT breusp segmentationofimagesusedinunmannedaerialvehiclesnavigationsystems
AT onishchenkoyu segmentationofimagesusedinunmannedaerialvehiclesnavigationsystems
AT gnusovyu segmentationofimagesusedinunmannedaerialvehiclesnavigationsystems
AT svitlychnyiv segmentationofimagesusedinunmannedaerialvehiclesnavigationsystems