normalized-cut segmentation using color and texture data
This code segment an image using color, texture and spatial data
RGB color is used as an color data
Four texture features are used: 1. mean 2. variance 3. skewness 4. kurtosis
Normalized Cut (inherently uses spatial data)
ncut parameters are "SI" Color similarity, "ST" Texture similarity, "SX" Spatial similarity, "r" Spatial threshold (less than r pixels apart), "sNcut" The smallest Ncut value (threshold) to keep partitioning, and "sArea" The smallest size of area (threshold) to be accepted as a segment
an implementation by "Naotoshi Seo" with a small modification is used for “normalized-cut” segmentation, available online at: "http://note.sonots.com/SciSoftware/NcutImageSegmentation.html", It is sensitive in choosing parameters.
Citation pour cette source
Alireza (2024). normalized-cut segmentation using color and texture data (https://www.mathworks.com/matlabcentral/fileexchange/52699-normalized-cut-segmentation-using-color-and-texture-data), MATLAB Central File Exchange. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
Windows macOS LinuxCatégories
- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Segmentation > Color Segmentation >
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Remerciements
Inspiré par : k-means, mean-shift and normalized-cut segmentation
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Version | Publié le | Notes de version | |
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1.0.0.0 | image added |