Color image thresholding is a well-known approach for image segmentation. An objective
function, based on image entropy, is defined by threshold numbers and locations in the color …

Multilevel thresholding has been long considered as one of the most popular techniques for
image segmentation. Multilevel thresholding outputs a gray scale image in which more …

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 …

Optimal multilevel thresholding for image segmentation got much importance in recent
years. Several entropic and non-entropic objective functions with evolutionary computing …

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 …

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

Color image segmentation is a vital preprocessing stage in various image processing
applications. In threshold-based segmentation, the success of the image segmentation …

One of the most important methods of image processing is image thresholding, which is
based on image histogram analysis. These methods analyze the image histogram diagram …

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

The multi-level thresholding is one of the most important issues in image segmentation. It is
a time consuming problem, ie finding appropriate threshold values could take exceptionally …