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.