normalized-cut segmentation using color and texture data

Versión 1.0.0.0 (21.5 KB) por Alireza
This code implemented a “normalized-cut” segmentation using color and texture information
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Actualizado 27 Aug 2015

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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.

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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. Recuperado .

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Se creó con R2011a
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Versión Publicado Notas de la versión
1.0.0.0

image added