Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jul 12, 2026

Automated Analysis of C. elegans Fluorescence Images using SegElegans
06:27

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

Hybrid strategy improved dung beetle optimization algorithm based 2D kapur entropy image segmentation method.

Meiyu Liang1, Jinjin Li1, Lei Zhang2

  • 1School of Electrical and Electronic Engineering, Anhui Institute of Information Technology, Wuhu, 241000, China.

Scientific Reports
|July 10, 2026
PubMed
Summary

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

Microstructure and Mechanical Properties of In Situ Al<sub>3</sub>Zr/Al-5Cu-0.6Mn-0.15Ti Heat-Resistant Aluminum Matrix Composites Based on Nominal Al<sub>3</sub>Zr Contents.

Materials (Basel, Switzerland)·2026
Same author

LysePred: A Multiscale Convolutional Neural Network for Predicting Hemolytic Activity of Antimicrobial Peptides.

ACS synthetic biology·2026
Same author

Cod protein modifications induced by lipid oxidation-derived aldehydes: Insights into multi-aldehydes environment.

Food chemistry·2026
Same author

Noninvasive PPROM risk stratification with explainable AI using routine antenatal CRP and albumin.

NPJ digital medicine·2026
Same author

Precision-Guarded Graph-Text Alignment for Universal Chemical Understanding.

Journal of chemical information and modeling·2026
Same author

Tocilizumab as a novel bridging therapy for surgery in dedifferentiated liposarcoma complicated by paraneoplastic leukemoid reaction, severe anemia, and thrombocytopenia: a case report.

Frontiers in oncology·2026

This study introduces an Improved Dung Beetle Optimization algorithm for multi-threshold image segmentation, enhancing accuracy and efficiency. The new method, IDBOKS, shows superior performance on complex images.

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Image Processing

Background:

  • Multi-threshold image segmentation is crucial for image analysis but faces challenges in balancing computational efficiency and accuracy.
  • Existing swarm intelligence algorithms often struggle with convergence speed and escaping local optima in complex segmentation tasks.

Purpose of the Study:

  • To develop an efficient and accurate multi-threshold image segmentation method.
  • To introduce a novel hybrid optimization algorithm, the Improved Dung Beetle Optimization (IDBO), for Kapur thresholding.
  • To enhance segmentation performance using advanced population initialization and information sharing strategies.

Main Methods:

  • The proposed IDBOKS method integrates an Improved Dung Beetle Optimization (IDBO) algorithm with Kapur's multi-threshold image segmentation.
Keywords:
2D Kapur entropyDung beetle optimizationHybrid strategyMulti-threshold image segmentationQuadratic interpolation

Related Experiment Videos

Last Updated: Jul 12, 2026

Automated Analysis of C. elegans Fluorescence Images using SegElegans
06:27

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

  • Population initialization uses the SPM-DE mechanism (SPM sequence and Differential Evolution) for diversity.
  • A rolling dung beetle group information sharing strategy and a dynamic scaling factor improve cooperative search.
  • A global quadratic interpolation mechanism enhances convergence and local optima avoidance.

    • Main Results:

    • Comparative experiments using FSIM, SSIM, and PSNR metrics demonstrate superior segmentation performance.
    • The IDBOKS method exhibited stronger robustness when processing complex images compared to other swarm intelligence algorithms.
    • The hybrid strategies effectively improved computational efficiency and segmentation accuracy.

    Conclusions:

    • The proposed IDBOKS method offers a significant advancement in multi-threshold image segmentation.
    • The integration of IDBO with Kapur entropy provides an effective solution for accurate and efficient image segmentation.
    • The algorithm's enhanced search strategies contribute to improved performance on challenging image datasets.