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

You might also read

Related Articles

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

Sort by

Same author

Optimization and Microstructural Studies on the Machining of Inconel 600 in WEDM Using Untreated and Cryogenically Treated Zinc Electrodes.

Materials (Basel, Switzerland)·2023

Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026

Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026

Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026

Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026

Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026

Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 1, 2025

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

Efficient Approach to Color Image Segmentation Based on Multilevel Thresholding Using EMO Algorithm by Considering

Srikanth Rangu¹, Rajagopal Veramalla¹, Surender Reddy Salkuti²

¹Department of ECE, Kakatiya Institute of Technology and Science, Warangal 506015, India.

Journal of Imaging

|April 27, 2023

Summary

This summary is machine-generated.

A new multilevel thresholding approach using electromagnetism optimization (EMO) and an energy curve (MTEMOE) improves color image segmentation. This method enhances feature extraction by considering spatial relationships, outperforming existing algorithms.

Keywords:

Otsu’s and Kapur’s methods color image entropy inter-class variance multilevel thresholding spatial contextual information

More Related 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

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Related Experiment Videos

Last Updated: Aug 1, 2025

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

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

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Area of Science:

Computer Vision
Image Processing
Optimization Algorithms

Background:

Image segmentation is crucial for feature extraction but challenging, especially for color images.
Existing histogram-based methods lack spatial contextual information, limiting segmentation accuracy.
Multilevel thresholding is a key technique for image segmentation.

Purpose of the Study:

To propose a novel multilevel thresholding approach for color image segmentation.
To enhance segmentation by incorporating spatial contextual information.
To improve the efficiency and accuracy of image segmentation using optimization techniques.

Main Methods:

A novel multilevel thresholding approach based on electromagnetism optimization (EMO) and an energy curve (MTEMOE) is introduced.
Otsu's variance and Kapur's entropy are used as fitness functions to determine optimal threshold values.
An energy curve is utilized to capture spatial relationships between neighboring pixels, overcoming histogram limitations.

Main Results:

The proposed MTEMOE approach demonstrated superior performance in color image segmentation.
Evaluations using metrics like MSE, PSNR, and SSIM showed significant improvements over other meta-heuristic algorithms.
The method effectively utilized spatial contextual information for enhanced segmentation results.

Conclusions:

The MTEMOE approach offers a significant advancement in color image segmentation.
This method provides a robust solution for complex image segmentation tasks in various engineering fields.
The integration of EMO and energy curves effectively addresses limitations of traditional segmentation techniques.