One of the critical tasks in image processing is image segmentation. Image thresholding is
the simplest technique of segmentation in two forms of bi‐level and multilevel. One …

The image thresholding methods consume a lot of time due to computational complexity
when the number of threshold levels increases. In order to reduce computation time and …

Today, image segmentation methods are widely used for various applications, including
object detection. Multilevel Thresholding Image Segmentation (MTIS) methods are among …

Particle Swarm Optimization (PSO) is a well-known meta-heuristic. It has been widely used
in both research and engineering fields. However, the original PSO generally suffers from …

Image segmentation is the process of separating pixels of an image into multiple classes,
enabling the analysis of objects in the image. Multilevel thresholding (MTH) is a method …

Multilevel thresholding has got more attention in recent years with various successful
applications. However, the implementation becomes more and more complex and time …

In this paper, a novel context-based 3D Otsu algorithm using human learning optimization
(HLO) is proposed for multilevel color image segmentation. The performance of 3D Otsu …

Amongst all the multilevel thresholding techniques, standard histogram based thresholding
approaches are very impressive for bi-level thresholding. But, it is not effective to select …

In this paper, multi-threshold image segmentation approaches using an improved teaching–
learning-based optimization algorithm (DI-TLBO) are presented and the proposed DI-TLBO …

Image segmentation is a basic problem in computer vision and various image processing
applications. Over the years, commonly used image segmentation has become quite …