Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Lagrange Multipliers: Two Constraints

Lagrange Multipliers: Two Constraints

The method of Lagrange multipliers with two constraints is used to optimize a function subject to two independent constraints. In many applications, the objective function represents a quantity to be maximized or minimized, such as cost, area, distance, or energy. The two constraints represent requirements that the solution must satisfy, such as fixed volume, limited resources, or prescribed dimensions.For a function of three variables, each constraint forms a surface in three-dimensional space.

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Retraction Note: Plant disease recognition using residual convolutional enlightened Swin transformer networks.

Scientific reports·2026

Same author

An improved crayfish optimization algorithm for solving engineering optimization problems.

PloS one·2026

Same author

One-Step Deoxygenated Oxidative C-N Coupling of Azine <i>N</i>-Oxides with Alicyclic Amines via Copper(I) Catalyst-dppf Cooperation.

The Journal of organic chemistry·2026

Same author

IFIANet: Frequency Attention Network for Time-Frequency in sEMG-Based Motion Intent Recognition.

Sensors (Basel, Switzerland)·2026

Same author

Corrigendum to "Greater cane rat algorithm (GCRA): A nature-inspired metaheuristic for optimization problems" [Heliyon Volume 10, Issue 11, June 2024, Article e31629].

Heliyon·2025

Same author

Improved COOT optimization: An approach to multilevel thresholding in image segmentation.

Scientific reports·2025

Same journal

Mental health of healthcare workers in England during the first three years of the COVID-19 pandemic: The NHS CHECK study cohort.

PloS one·2026

Same journal

Research on trajectory tracking control of tracked vehicles based on hydraulic motor system identification and Laguerre-MPC.

PloS one·2026

Same journal

A collaborative cervical precancer screening strategy with concurrent HPV genotyping and visual inspection using alumni of a training centre across Ghana: The Rotary 'Protect Your Pearl' initiative.

PloS one·2026

Same journal

Removal efficiency of pesticide residues on pesticide-spiked Perilla Leaf and Broccoli surfaces using microplasma-treated water.

PloS one·2026

Same journal

Cross-domain zero-shot semantic segmentation for unstructured environments via EVA-CLIP model, ensemble prompt engineering, and optimized text-image matching.

PloS one·2026

Same journal

Adaptive robust sparse representation for face recognition based on weighted and fusion dictionary.

PloS one·2026

See all related articles

Search research articles

Home
Multi-strategy Remora Optimization Algorithm For Color Multi-threshold Image Segmentation.

Home
Multi-strategy Remora Optimization Algorithm For Color Multi-threshold Image Segmentation.

Related Experiment Video

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Published on: March 7, 2017

Multi-strategy remora optimization algorithm for color multi-threshold image segmentation.

Heming Jia¹, Changsheng Wen², Honghua Rao³

¹School of Information Engineering, Sanming University, Sanming, Fujian, China.

|February 18, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

A new Multi-Strategy Remora Optimization Algorithm (MSROA) enhances color image segmentation by preventing local optima and improving convergence. This method achieves superior segmentation accuracy and image quality compared to existing algorithms.

More Related Videos

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Related Experiment Videos

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Published on: March 7, 2017

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Area of Science:

Computer Vision
Artificial Intelligence
Image Processing

Background:

Multi-threshold image segmentation is crucial but computationally complex due to large search spaces.
Existing optimization algorithms often suffer from local optima and slow convergence.

Purpose of the Study:

To introduce the Multi-Strategy Remora Optimization Algorithm (MSROA) for efficient and accurate color image segmentation.
To enhance optimization performance by preventing local optima and accelerating convergence.

Main Methods:

MSROA integrates Beta random restarts with a "prior" property to avoid local optima.
A random walk with fast predation and elite learning strategies are employed to boost convergence speed and accuracy.
Performance evaluated on CEC2017 and CEC2020 benchmark suites and applied to Otsu's and Kapur's methods for image segmentation.

Main Results:

MSROA demonstrated statistically significant improvements over seven state-of-the-art algorithms via Wilcoxon rank-sum tests.
The algorithm accurately identified optimal threshold combinations, producing higher quality segmented images.
Consistently higher PSNR, FSIM, and SSIM values indicate superior preservation of image details.

Conclusions:

MSROA offers a robust and efficient solution for multi-threshold color image segmentation.
The algorithm effectively balances exploration and exploitation for improved optimization.
MSROA outperforms existing methods in segmentation accuracy and detail preservation.