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JOURNALS // Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki // Archive

Zh. Vychisl. Mat. Mat. Fiz., 2024 Volume 64, Number 11, Pages 2212–2226 (Mi zvmmf11876)

This article is cited in 1 paper

Computer science

Accelerated algorithms for growing segments from image regions

D. M. Murashov

Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, 119333, Moscow, Russia

Abstract: New algorithms for merging superpixel regions into segments are proposed. The main idea of merging superpixels is as follows. Firstly, a strategy is used in which a segment is grown from neighboring regions while the conditions for merging are met, and, secondly, when merging regions, the applied information quality measure should not increase. Three algorithms based on the specified strategy are proposed, which differ in the conditions for making a decision on merging superpixels. A computational experiment is carried out on test images. The experiment showed that the proposed algorithms accelerate the segmentation process compared to the procedure used earlier with acceptable losses of information quality measures of the resulting partitions.

Key words: image segmentation, information redundancy, information variation, growing segments, combining segments, superpixel.

UDC: 519.67

Received: 08.04.2024
Revised: 08.04.2024
Accepted: 26.07.2024

DOI: 10.31857/S0044466924110164


 English version:
Computational Mathematics and Mathematical Physics, 2024, 64:11, 2722–2735

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© Steklov Math. Inst. of RAS, 2026