*Proceeding Paper* **Exponential Particle Swarm Optimization Algorithm for Complexly Structured Images Segmentation †**

**Samer El-Khatib 1, Yuri Skobtsov 2,\* and Sergey Rodzin <sup>1</sup>**


**Abstract:** Image segmentation is the process of dividing an image into homogeneous regions according to certain features and is widely used in image processing. Complexly structured images usually contain complex and essential objects. These images are non-linear structural images and they contain a large number of elements with required specifications. The main goal of the proposed EPSO (Exponential Particle Swarm Optimization) algorithm is to prevent local solutions and find the exact global optimal solutions for the task of segmenting medical images. The execution time is compared with well-known segmentation algorithms. The EPSO method is superior to the segmentation methods studied, including the graph algorithm. Comparisons were made with existing segmentation algorithms (Grow cut, Random Walker, DPSO, K-means PSO, and hybrid-K-means ant colony optimization algorithm) in tabular form.

**Keywords:** complexly structured image segmentation; swarm intelligence; particle swarm optimization algorithm
