[HTML][HTML] Human-inspired optimization algorithms: Theoretical foundations, algorithms, open-research issues and application for multi-level thresholding
Humans take immense pride in their ability to be unpredictably intelligent and despite huge
advances in science over the past century; our understanding about human brain is still far …
advances in science over the past century; our understanding about human brain is still far …
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 …
An efficient Harris hawks-inspired image segmentation method
E Rodríguez-Esparza, LA Zanella-Calzada… - Expert Systems with …, 2020 - Elsevier
Segmentation is a crucial phase in image processing because it simplifies the
representation of an image and facilitates its analysis. The multilevel thresholding method is …
representation of an image and facilitates its analysis. The multilevel thresholding method is …
A novel hybrid harris hawks optimization for color image multilevel thresholding segmentation
X Bao, H Jia, C Lang - Ieee Access, 2019 - ieeexplore.ieee.org
Multilevel thresholding has got more attention in recent years with various successful
applications. However, the implementation becomes more and more complex and time …
applications. However, the implementation becomes more and more complex and time …
An improved marine predators algorithm with fuzzy entropy for multi-level thresholding: real world example of COVID-19 CT image segmentation
Medical imaging techniques play a critical role in diagnosing diseases and patient
healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is …
healthcare. They help in treatment, diagnosis, and early detection. Image segmentation is …
A feature level image fusion for Night-Vision context enhancement using Arithmetic optimization algorithm based image segmentation
Images are fused to produce a composite image by combining key characteristics of the
source images in image fusion. It makes the fused image better for human vision and …
source images in image fusion. It makes the fused image better for human vision and …
Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation
First, this study develops an enhanced slime mould algorithm (MGSMA). The main idea is to
combine the new movement strategy and Gaussian kernel probability strategy to improve …
combine the new movement strategy and Gaussian kernel probability strategy to improve …
Improved artificial bee colony using sine-cosine algorithm for multi-level thresholding image segmentation
Multilevel-thresholding is an efficient method used in image segmentation. This paper
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …
presents a hybrid meta-heuristic approach for multi-level thresholding image segmentation …
[HTML][HTML] Harris hawks optimization for COVID-19 diagnosis based on multi-threshold image segmentation
Digital image processing techniques and algorithms have become a great tool to support
medical experts in identifying, studying, diagnosing certain diseases. Image segmentation …
medical experts in identifying, studying, diagnosing certain diseases. Image segmentation …
A review of image fusion: Methods, applications and performance metrics
The same sensor or a number of image sensors are used to take a series of photographs in
order to gather as much data as possible about the scene. Several imaging techniques are …
order to gather as much data as possible about the scene. Several imaging techniques are …