A study of improved salp swarm algorithm in threshold segmentation of two-dimensional OTSU images

Heyu Wang; Tong Wu

doi:10.1117/12.3042704

10 September 2024 A study of improved salp swarm algorithm in threshold segmentation of two-dimensional OTSU images

Heyu Wang, Tong Wu

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132570A (2024) https://doi.org/10.1117/12.3042704
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

Aiming at the deficiencies of the Slap Swarm Algorithm in terms of solution accuracy, convergence speed and global search capability, an improved Slap Swarm Algorithm is proposed. Firstly, an improved Tent chaotic sequence is used for population initialization; secondly, adaptive weight factor and Levy flight strategy are used to update the leader position; meanwhile, non-uniform Gaussian variation operator is used to update the follower position. In the experimental results, it is shown that the improved algorithm has higher accuracy as well as convergence; in the application, the selection of the optimal average fitness value (image segmentation threshold) is faster and more accurate, and the segmentation threshold is more appropriate.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Heyu Wang and Tong Wu "A study of improved salp swarm algorithm in threshold segmentation of two-dimensional OTSU images", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132570A (10 September 2024); https://doi.org/10.1117/12.3042704

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Mathematical optimization

Cameras

Particle swarm optimization

Algorithms

Performance modeling

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