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

Simrandeep Singh¹, Harbinder Singh², Seyed Jaleleddin Mousavirad³

¹Department of Electronics & Communication Engineering, UCRD, Chandigarh University, Gharuan, Punjab, India.

Scientific Reports

|November 21, 2025

Summary

This summary is machine-generated.

This study introduces an improved COOT (ICOOT) optimization algorithm for enhanced multilevel image thresholding. The ICOOT algorithm balances exploration and exploitation, outperforming existing methods in image segmentation tasks.

Keywords:

CT images Image segmentation Metaheuristics Multilevel thresholding

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Area of Science:

Computer Vision
Image Processing
Artificial Intelligence

Background:

Image thresholding is crucial for image segmentation and preprocessing in various applications.
Metaheuristic algorithms show promise for image segmentation, but standard COOT algorithm has limitations like stagnation.
Balancing exploration and exploitation is key for effective metaheuristic optimization.

Purpose of the Study:

To propose an improved COOT (ICOOT) optimization algorithm for multilevel image thresholding.
To enhance the exploration and exploitation capabilities of the COOT algorithm.
To evaluate the ICOOT algorithm's performance in image segmentation and complex optimization problems.

Main Methods:

Incorporating Lévy flights to improve COOT's exploration.
Introducing quasi-opposition-based learning to enhance COOT's exploitation and balance.
Applying the ICOOT algorithm for multilevel image thresholding using Otsu's entropy.

Main Results:

The ICOOT algorithm demonstrated superior performance on CEC'17 benchmark optimization problems.
ICOOT achieved better results in multilevel image thresholding compared to state-of-the-art algorithms.
The algorithm showed effectiveness on benchmark images and COVID-19 CT scans.

Conclusions:

The proposed ICOOT algorithm effectively addresses the limitations of the standard COOT algorithm.
ICOOT offers an improved approach for image segmentation through enhanced multilevel thresholding.
The study validates ICOOT's efficiency and superiority in various image processing applications.