Development of an optoelectronic image segmentation method from unmanned aerial vehicles based on the ant colony optimization algorithm under the influence of salt-and-pepper noise
DOI:
https://doi.org/10.15587/2706-5448.2025.344562Keywords:
optoelectronic image, segmentation, ant colony optimization algorithm, salt-and-pepper noiseAbstract
The object of research is the process of segmenting an image from an unmanned aerial vehicle based on the ant algorithm under the influence of salt-and-pepper noise.
“Salt”-and-“pepper” noise occurs due to data transmission errors, failures of digital camera sensors or malfunctions during recording/reading of information. It is characterized by the random appearance of individual pixels in the image, the value of which is equal to the minimum (“pepper”) or maximum (“salt”) brightness level.
Unlike the known ones, the method of segmenting an optoelectronic image based on the ant algorithm provides image segmentation under the influence of salt-and-pepper noise and involves:
– initialization of initial parameters;
– calculation of the length of the path segment of agents;
– calculation of the attractiveness of the route for the agent;
– updating the pheromone concentration;
– calculation of the probability of transition of agents;
– calculation of the objective function;
– movement of agents;
– determination of the best route of agents.
Experimental studies have shown that the segmentation method based on the ant algorithm provides a reduction in segmentation errors of the first kind on average:
– in the absence of salt-and-pepper noise – 4%;
– at the intensity of salt-and-pepper noise σ = 5–21%;
– at the intensity of salt-and-pepper noise σ = 15–10%.
The segmentation method based on the ant algorithm provides a reduction in segmentation errors of the second kind on average:
– in the absence of salt-and-pepper noise – 3%;
– at the intensity of salt-and-pepper noise σ = 5–15%;
– at the intensity of salt-and-pepper noise σ = 15–6%.
The practical significance of the segmentation method based on the ant algorithm is to ensure high-quality image segmentation under the influence of salt-and-pepper noise.
Supporting Agency
- The research was conducted with grant support from the National Research Foundation of Ukraine within the framework of the competition “Science for Strengthening the Defense Capability of Ukraine”, project “Information technology for automated segmentation of object images in FPV strike drone targeting systems based on swarm intelligence algorithms”, registration number 2023.04/0153.
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Copyright (c) 2025 Igor Ruban, Hennadii Khudov, Vladyslav Khudov, Oleksandr Makoveichuk, Irina Khizhnyak, Ihor Butko, Andrii Hryzo, Rostyslav Khudov, Petro Mynko, Oleksii Baranik
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