Meta-heuristic moth swarm algorithm for multilevel thresholding image segmentation
Y Zhou, X Yang, Y Ling, J Zhang - Multimedia Tools and Applications, 2018 - Springer
Multilevel thresholding is a very important image processing technique in the field of image
segmentation. However, the computational complexity of determining the optimal threshold …
segmentation. However, the computational complexity of determining the optimal threshold …
[HTML][HTML] Multi-level thresholding image segmentation based on improved slime mould algorithm and symmetric cross-entropy
Y Jiang, D Zhang, W Zhu, L Wang - Entropy, 2023 - mdpi.com
Multi-level thresholding image segmentation divides an image into multiple regions of
interest and is a key step in image processing and image analysis. Aiming toward the …
interest and is a key step in image processing and image analysis. Aiming toward the …
An improved teaching–learning-based optimization for multilevel thresholding image segmentation
Z Jiang, F Zou, D Chen, J Kang - Arabian Journal for Science and …, 2021 - Springer
Due to its successful application image processing or computer vision system, image
segmentation plays a significant role and has become a hot research hotspot. In this paper …
segmentation plays a significant role and has become a hot research hotspot. In this paper …
A novel hybrid algorithm of gravitational search algorithm with genetic algorithm for multi-level thresholding
G Sun, A Zhang, Y Yao, Z Wang - Applied Soft Computing, 2016 - Elsevier
The multi-level thresholding is a popular method for image segmentation. However, the
method is computationally expensive and suffers from premature convergence when level …
method is computationally expensive and suffers from premature convergence when level …
Swarm selection method for multilevel thresholding image segmentation
Multilevel thresholding is one of the most popular approaches used for image segmentation.
Several methods have been used to find the threshold values; however, metaheuristic (MH) …
Several methods have been used to find the threshold values; however, metaheuristic (MH) …
HCS-BBD: An effective population-based approach for multi-level thresholding
SJ Mousavirad, G Schaefer, D Oliva… - Proceedings of the …, 2021 - dl.acm.org
Thresholding is one of the most common techniques for image segmentation where an
image is partitioned into several parts based on its histogram of pixel intensities …
image is partitioned into several parts based on its histogram of pixel intensities …
A Novel Hybrid CS-BFO Algorithm for Optimal Multilevel Image Thresholding Using Edge Magnitude Information
Thresholding is the key to simplify image classification. It becomes challenging when the
number of thresholds is more than two. Most of the existing multilevel thresholding …
number of thresholds is more than two. Most of the existing multilevel thresholding …
Image segmentation using multilevel thresholding based on modified bird mating optimization
Multilevel thresholding using Otsu or Kapur methods is widely used in the context of image
segmentation. These methods select optimal thresholds in gray level images by maximizing …
segmentation. These methods select optimal thresholds in gray level images by maximizing …
How effective are current population-based metaheuristic algorithms for variance-based multi-level image thresholding?
SJ Mousavirad, G Schaefer, H Zhou… - Knowledge-Based …, 2023 - Elsevier
Multi-level image thresholding is a common approach to image segmentation where an
image is divided into several regions based on its histogram. Otsu's method is the most …
image is divided into several regions based on its histogram. Otsu's method is the most …