SEGMENTATION OF MULTIGRADATION IMAGES BASED ON SPATIAL CONNECTIVITY FEATURES

Leonid Timchenko

tumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department (Ukraine)
https://orcid.org/0000-0001-5056-5913

Natalia Kokriatskaya


State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department (Ukraine)
https://orcid.org/0000-0003-0090-3886

Volodymyr Tverdomed


1State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, 2Kyiv Institute of Railway Transport (Ukraine)
http://orcid.org/0000-0002-0695-1304

Oleksandr Stetsenko


State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department (Ukraine)
http://orcid.org/0000-0001-8359-0218

Valentina Kaplun


Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0003-4353-3694

Oleg K. Kolesnytskyj


Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0003-0336-4910

Oleksandr Reshetnik


Vinnytsia National Technical University (Ukraine)
http://orcid.org/0009-0006-7320-329X

Saule Smailova


D.Serikbayev East Kazakhstan State Technical University (Kazakhstan)
http://orcid.org/0000-0002-8411-3584

Ulzhalgas Zhunissova


Astana Medical University (Kazakhstan)
http://orcid.org/0000-0001-5255-9314

Abstract

The article aims to study the multi-level segmentation process of images of arbitrary configuration and placement based on features of spatial connectivity. Existing image processing algorithms are analyzed, and their advantages and disadvantages are determined. A method of organizing the process of segmentation of multi-gradation halftone images is developed and an algorithm of actions according to the described method is given.


Keywords:

image segmentation, image processing, halftone images, spatial connectivity

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Published
2023-09-30

Cited by

Timchenko, L., Kokriatskaya, N., Tverdomed, V., Stetsenko, O., Kaplun, V., Kolesnytskyj, O. K., … Zhunissova, U. (2023). SEGMENTATION OF MULTIGRADATION IMAGES BASED ON SPATIAL CONNECTIVITY FEATURES. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 13(3), 47–50. https://doi.org/10.35784/iapgos.5352

Authors

Leonid Timchenko 
tumchenko_li@gsuite.duit.edu.ua
State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department Ukraine
https://orcid.org/0000-0001-5056-5913

Authors

Natalia Kokriatskaya 

State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department Ukraine
https://orcid.org/0000-0003-0090-3886

Authors

Volodymyr Tverdomed 

1State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, 2Kyiv Institute of Railway Transport Ukraine
http://orcid.org/0000-0002-0695-1304

Authors

Oleksandr Stetsenko 

State University of Infrastructure and Technology, Artificial Intelligence Systems and Telecommunication Technologies Department Ukraine
http://orcid.org/0000-0001-8359-0218

Authors

Valentina Kaplun 

Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0003-4353-3694

Authors

Oleg K. Kolesnytskyj 

Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0003-0336-4910

Authors

Oleksandr Reshetnik 

Vinnytsia National Technical University Ukraine
http://orcid.org/0009-0006-7320-329X

Authors

Saule Smailova 

D.Serikbayev East Kazakhstan State Technical University Kazakhstan
http://orcid.org/0000-0002-8411-3584

Authors

Ulzhalgas Zhunissova 

Astana Medical University Kazakhstan
http://orcid.org/0000-0001-5255-9314

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