Multilevel thresholding image segmentation using meta-heuristic optimization algorithms: Comparative analysis, open challenges and new trends

L Abualigah, KH Almotairi, MA Elaziz - Applied Intelligence, 2023 - Springer
This paper studied the multilevel threshold image segmentation-based metaheuristics
optimization methods and their applications. Image segmentation is a common problem in …

Image segmentation using multilevel thresholding: a research review

S Pare, A Kumar, GK Singh, V Bajaj - Iranian Journal of Science and …, 2020 - Springer
Image segmentation is a basic problem in computer vision and various image processing
applications. Over the years, commonly used image segmentation has become quite …

An improved African vultures optimization algorithm using different fitness functions for multi-level thresholding image segmentation

FS Gharehchopogh, T Ibrikci - Multimedia Tools and Applications, 2024 - Springer
Image segmentation is one of the most significant and required procedures in pre-
processing and analyzing images. Metaheuristic optimization algorithms are used to solve a …

HSMA_WOA: A hybrid novel Slime mould algorithm with whale optimization algorithm for tackling the image segmentation problem of chest X-ray images

M Abdel-Basset, V Chang, R Mohamed - Applied soft computing, 2020 - Elsevier
Recently, a novel virus called COVID-19 has pervasive worldwide, starting from China and
moving to all the world to eliminate a lot of persons. Many attempts have been experimented …

A hybrid COVID-19 detection model using an improved marine predators algorithm and a ranking-based diversity reduction strategy

M Abdel-Basset, R Mohamed, M Elhoseny… - IEEE …, 2020 - ieeexplore.ieee.org
Many countries are challenged by the medical resources required for COVID-19 detection
which necessitates the development of a low-cost, rapid tool to detect and diagnose the …

Multilevel thresholding using grey wolf optimizer for image segmentation

AKM Khairuzzaman, S Chaudhury - Expert Systems with Applications, 2017 - Elsevier
Multilevel thresholding is one of the most important areas in the field of image segmentation.
However, the computational complexity of multilevel thresholding increases exponentially …

A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems

M Abdel-Basset, V Chang, R Mohamed - Neural Computing and …, 2021 - Springer
Image segmentation is considered a crucial step required for image analysis and research.
Many techniques have been proposed to resolve the existing problems and improve the …

Research on k-means clustering algorithm: An improved k-means clustering algorithm

S Na, L Xumin, G Yong - 2010 Third International Symposium …, 2010 - ieeexplore.ieee.org
Clustering analysis method is one of the main analytical methods in data mining, the method
of clustering algorithm will influence the clustering results directly. This paper discusses the …

Otsu method and K-means

D Liu, J Yu - 2009 Ninth International conference on hybrid …, 2009 - ieeexplore.ieee.org
Otsu method is one of the most successful methods for image thresholding. This paper
proves that the objective function of Otsu method is equivalent to that of K-means method in …

Tsallis entropy based multilevel thresholding for colored satellite image segmentation using evolutionary algorithms

AK Bhandari, A Kumar, GK Singh - Expert systems with applications, 2015 - Elsevier
In this paper, a new technique for color image segmentation using CS algorithm supported
by Tsallis entropy for multilevel thresholding has been proposed toward the effective colored …