Soft thresholding for image segmentation
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
Citation pour cette source
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. Récupéré le .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Segmentation > Image Thresholding >
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Inspiré par : elmat+ 2.2
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fth/fth/
Version | Publié le | Notes de version | |
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4.0.0.0 | Reference to the published paper added. |
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1.6.0.0 | - The centroids are now searched by a fuzzy c-means.
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1.5.0.0 | Small change to correct a bug in 3D |
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1.4.0.0 | A bug in shiftmat is corrected |
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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 |
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1.2.0.0 | Bug corrected for more than 5 maxima in smoothed histogram |
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1.0.0.0 |