Soft thresholding for image segmentation

Image segmentation based on histogram soft thresholding
6K Downloads
Updated 9 Jun 2015

View License

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 (2024). 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
Acknowledgements

Inspired by: elmat+ 2.2

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
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