Multilevel image thresholding is effectually technique used to segment many types of
images. It usually applied in image preprocessing phase. In this chapter, a review of gray …

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

Image segmentation is an important problem for image processing. The image processing
applications are generally affectedfromthe segmentation success. There is noany image …

Thresholding is an important approach for image segmentation and it is the first step in the
image processing for many applications. Segmentation is a low level operation that can …

Multilevel thresholding is a very important image processing technique in the field of image
segmentation. However, the computational complexity of determining the optimal threshold …

Multilevel thresholding is a popular image segmentation technique. However, computational
complexity of multilevel thresholding increases very rapidly with increasing number of …

In this paper, five successful nature inspired algorithms; the artificial tree algorithm (AT), the
particle swarm optimization (PSO), the genetic algorithm (GA), the cultural algorithm (CA) …

Multilevel thresholding is one of the most broadly used approaches to image segmentation.
However, the traditional techniques of multilevel thresholding are time-consuming …

This paper introduces the comparison of evolutionary and swarm-based optimization
algorithms for multilevel color image thresholding problem which is a process used for …

Thresholding is a popular image segmentation method that converts gray-level image into
binary image. The selection of optimum thresholds has remained a challenge over decades …