Thresholding is a fundamental approach to segmentation that utilizes a significant degree of
pixel popularity or intensity. Otsu's thresholding employed the normalized histogram as a …

Colored satellite images are difficult to segment due to their low illumination, dense features,
uncertainties, etc. Rényi's entropy is a famous entropy criterion that provides excellent …

Multilevel thresholding technique is popular and extensively used in the field of image
processing. In this paper, a multilevel threshold selection is proposed based on edge …

Multilevel image segmentation involves large computation and time-consuming. The firefly
algorithm (FA) has been applied to emerging the efficiency of multilevel image …

Automatic thresholding has been widely used in machine vision for automatic image
segmentation. Otsu's method selects an optimum threshold by maximizing the between …

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) …

Thresholding is one of the highly accepted methods for image segmentation because of its
simplicity in nature. The selection of optimal threshold values in threshold-based image …

In this study, we have proposed an efficient automatic multilevel thresholding method for
image segmentation. An effective criterion for measuring the separability of the homogenous …

In this chapter, an alternative image segmentation method is proposed to find the multi-level
thresholding values. The proposed method is based on the tree seed algorithm (TSA) which …

Image segmentation is a method of subdividing an image into numerous meaningful regions
or objects, which shows the image more informative for further analysis. Thresholding based …