A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution

Version 1.0.0.0 (40.1 KB) by Sujoy Paul
Implementation of a Global Image Thresholding Algorithm
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Updated 8 Oct 2014

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Image thresholding is one of the most important task in image analysis and pattern recognition. In this code a multi-level image thresholding algorithm is implemented. The algorithm is based on fuzzy partition of the image histogram, and optimization of the defined fuzzy entropy measure by Differential Evolution to obtain the optimal thresholds.
The algorithm is proposed in :
S.Sarkar, S.Paul, R.Burman, S.Das, S.S.Chaudhuri, "A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution," ACCEPTED for presentation at 5th International Conference on Swarm, Evolutinary and Memetic Computing (SEMCCO) 2014. To be published soon.

Please cite this paper, if you use it.

Cite As

Sujoy Paul (2026). A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution (https://in.mathworks.com/matlabcentral/fileexchange/48055-a-fuzzy-entropy-based-multi-level-image-thresholding-using-differential-evolution), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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1.0.0.0