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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 09 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 (2021). Soft thresholding for image segmentation (https://www.mathworks.com/matlabcentral/fileexchange/36918-soft-thresholding-for-image-segmentation), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (21)

Naufal Aldy Pradana

Samar Ragab

I have this error : MG=fth(I,0,2,1,0.02);
Error using smooth (line 73)
SMOOTH needs at least one argument.

Error in maxima_search (line 27)
sig = smooth.*[1 1 1]; % 1.5 in each dimension

paramveer sran

would you please tell me how you show the threshold image after running the code?

Peps Reynoso

Hello, Santiago. This code is helping me immensely. I'm still trying to understand the code and paper, but I wanted to thank you for sharing this.

Khaing Zin Htwe

DaDu

Martin

Answer to Arnold: Your output will strongly depend on the input image. COntact me by mail and I can check where it is failing.

arnold

doesn't work for me. Gives 'S' and 'MG' which contains just ones.

Muhammad Bilal

Kindly tell me the steps to follow run this code
Regards
Bilal

Xidian NO.1

Ramkumar

thank u for sharing

Omar Al Okashi

Dear Sir..
Thanx alot about sharing... I can not run it because of this error:

??? Error using ==> shiftmat
Too many input arguments.

Error in ==> seg_fuzzy at 207
M_tmp = shiftmat(Mx,i,1);

can you explain us how to implement it..
with my Regards...

Edwin

Thanks for your sharing. would you please tell me how you show the threshold image after running the code?

Thanks for your help in advanced!

Darlis Herumurti

Thank you so much for your sharing code, it is very impressive.
I've read your paper and I would like to ask about the median MG (step 6). I confuse the use of MG and about calculating the MX in step 5 and step 6, since in your code, you didn't do anything about MG.
Thank you very much for your kind response.

Modify anything you want, of course. It should be easy. I cannot say when next version will be ready, sorry. I'll try to do it along these months.

leila

thank you. I want to try it on 3d US images, can I change it? when the next version will be written?
thanks.

The function is a basic implementation thought for 2D, but with very small changes it could work for 3D. The square neighborhoods used for smoothing and aggregation must be replaced by 3D neighborhoods. (I'll do it for the next version...)

leila

does the function support 3d images?

The original file lacks of a control for more than 5 output sets. New version with problem corrected is added.

Sven

Your example itself fails with an error:

>> [S,MG,Nmax]=seg_fuzzy(I,1,2)

Undefined function or variable "Mx".

Error in seg_fuzzy (line 196)
Mx2(:,:,1)=Mx;

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

Inspired by: elmat+ 2.2

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