Soft thresholding for image segmentation

Version 4.0.0.0 (14.5 KB) by SANTIAGO AJA-FERNANDEZ
Image segmentation based on histogram soft thresholding
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Updated 9 Jun 2015

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FTH is a fuzzy thresholding method for image segmentation. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived from a fuzzy c-means centroid search. As a consequence, each pixel will belong to different regions with a different level of membership. This feature is exploited through spatial processing to make the thresholding robust to noisy environments.
Method proposed in:
Aja-Fernández, S., A. Hernán Curiale, and G. Vegas-Sánchez-Ferrero, "A local fuzzy thresholding methodology for multiregion image segmentation", Knowledge-Based Systems, vol. 83, pp. 1-12, 07/2015.
URL http://www.sciencedirect.com/science/article/pii/S095070511500129X
DOI 10.1016/j.knosys.2015.02.029

This new version is highly improved.

New Version, 4.0

Cite As

SANTIAGO AJA-FERNANDEZ (2026). Soft thresholding for image segmentation (https://www.mathworks.com/matlabcentral/fileexchange/36918-soft-thresholding-for-image-segmentation), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R14
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Acknowledgements

Inspired by: elmat+ 2.2

fth/fth/

Version Published Release Notes
4.0.0.0

Reference to the published paper added.
1.6.0.0

- The centroids are now searched by a fuzzy c-means.
- 5 different spatial aggregations are considered.
- The optimization step has been avoided.
- A threshold to prune output sets has been added.
1.5.0.0

Small change to correct a bug in 3D
1.4.0.0

A bug in shiftmat is corrected
1.3.0.0

Version 3: It admits 3D data and rgb images. It has no limit of number of output sets. Some minor bugs were corrected
1.2.0.0

Bug corrected for more than 5 maxima in smoothed histogram
1.0.0.0