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A Chaotic Electromagnetic Field Optimization Algorithm Based on Fuzzy Entropy for Multilevel Thresholding Color Image

Suhang Song¹, Heming Jia¹, Jun Ma¹

¹College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China.

Entropy (Basel, Switzerland)

|December 3, 2020

Summary

This summary is machine-generated.

A new Chaotic Electromagnetic Field Optimization (CEFO) algorithm enhances multilevel thresholding for color images. This method offers superior segmentation accuracy and efficiency compared to traditional techniques.

Keywords:

chaotic strategy color image segmentation electromagnetic field optimization fuzzy entropy multilevel thresholding

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Area of Science:

Computer Vision
Image Processing
Artificial Intelligence

Background:

Multilevel thresholding is crucial for color image segmentation.
Traditional methods for optimal threshold selection are time-consuming.
Meta-heuristic algorithms offer efficient solutions for threshold optimization.

Purpose of the Study:

Propose an effective Electromagnetic Field Optimization (EFO) algorithm for multilevel thresholding.
Introduce a novel chaotic strategy into EFO, creating the CEFO algorithm.
Evaluate CEFO's robustness and segmentation performance against other algorithms.

Main Methods:

Developed a Chaotic Electromagnetic Field Optimization (CEFO) algorithm.
Utilized fuzzy entropy as the fitness function for optimization.
Compared CEFO with Artificial Bee Colony (ABC), Bat Algorithm (BA), Wind Driven Optimization (WDO), and Bird Swarm Algorithm (BSA).
Benchmarked against Otsu's variance and Kapur's entropy methods.
Conducted experiments on Berkeley benchmark images at multiple threshold levels.

Main Results:

CEFO demonstrated superior performance in multilevel thresholding color image segmentation.
Quantitative metrics including PSNR, MSSIM, and FSIM confirmed CEFO's accuracy.
CEFO achieved competitive computational time (CPU Time) compared to other algorithms.
The proposed method effectively handles complex segmentation tasks.

Conclusions:

The proposed CEFO algorithm provides an excellent solution for multilevel thresholding color image segmentation.
CEFO offers a robust and efficient alternative to existing methods.
The integration of chaotic strategy significantly enhances EFO's optimization capabilities.