Multilevel thresholding is one of the most commonly used methods in image segmentation.
However, the exhaustive search methods are costly in determining optimal thresholds and …

In the normal image thresholding methods based on two-dimensional histogram, the edge
information of the regions is not maintained because of the local averaging activity used …

Multilevel image thresholding is an important operation in many analyses which is used in
many applications. Selecting correct thresholds is a critical issue. In this paper, Bacterial …

A metaheuristic algorithm called Harris hawks optimization (HHO) is gaining its popularity
among its clan and useful for optimization. In this algorithm, the prey gets completely …

Image segmentation is a very important and pre-processing step in image analysis. The
conventional multilevel thresholding methods are efficient for bi-level thresholding because …

This paper proposes a global multi-level thresholding method for image segmentation. As a
criterion for this, the traditional method uses the Shannon entropy, originated from …

The digital image segmentation is an open problem that is growing day by day and is
attracting the attention of researchers from last few years. Image resolution and their speed …

In this paper, optimal thresholds for multi-level thresholding in an image are obtained by
maximizing the Tsallis entropy using cuckoo search algorithm. The method is considered as …

Satellite image segmentation is challenging due to the presence of weakly correlated and
ambiguous multiple regions of interest. Several bio-inspired algorithms were developed to …

Medical imaging techniques play a critical role in diagnosing diseases and patient
healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is …