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Multilevel thresholding image segmentation using meta-heuristic optimization algorithms: Comparative analysis, open challenges and new trends
This paper studied the multilevel threshold image segmentation-based metaheuristics
optimization methods and their applications. Image segmentation is a common problem in …
optimization methods and their applications. Image segmentation is a common problem in …
Image segmentation using multilevel thresholding: a research review
Image segmentation is a basic problem in computer vision and various image processing
applications. Over the years, commonly used image segmentation has become quite …
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
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 …
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
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 …
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
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 …
which necessitates the development of a low-cost, rapid tool to detect and diagnose the …
Multilevel thresholding using grey wolf optimizer for image segmentation
Multilevel thresholding is one of the most important areas in the field of image segmentation.
However, the computational complexity of multilevel thresholding increases exponentially …
However, the computational complexity of multilevel thresholding increases exponentially …
A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems
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 …
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 …
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 …
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
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 …
by Tsallis entropy for multilevel thresholding has been proposed toward the effective colored …