Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …

This paper studied the multilevel threshold image segmentation-based metaheuristics
optimization methods and their applications. Image segmentation is a common problem in …

Segmentation is a crucial step in image processing applications. This process separates
pixels of the image into multiple classes that permits the analysis of the objects contained in …

One of the most crucial aspects of image segmentation is multilevel thresholding. However,
multilevel thresholding becomes increasingly more computationally complex as the number …

Image segmentation is considered a crucial step required for image analysis and research.
Many techniques have been proposed to resolve the existing problems and improve the …

This study integrates a tunicate swarm algorithm (TSA) with a local escaping operator (LEO)
for overcoming the weaknesses of the original TSA. The LEO strategy in TSA-LEO prevents …

Optimization is the process of searching for the optimal (best-so-far) solution among a wide
range of solutions. Besides, in the last two decades, a family of algorithms known as …

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile
Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray …

Background and objective: Automatic segmentation of retinal blood vessels makes a major
contribution in CADx of various ophthalmic and cardiovascular diseases. A procedure to …

Due to the computational complexity of multilevel image thresholding, Swarm Intelligence
Optimization Algorithm (SIOA) has been widely applied to improve the calculation efficiency …