This is documentation for Mathematica 8, which was
based on an earlier version of the Wolfram Language.
View current documentation (Version 11.1)
Segmentation Analysis
Mathematica includes a variety of image segmentation techniques such as clustering, watershed, region growing, and level set as well as a rich set of functions for post-processing and analyzing the result of the segmentation.
Image Preparation
ColorQuantize reduce the number of distinct colors in an image
FillingTransform reduce noise to create smooth regions in an image
GradientFilter, RangeFilter create an edge map from an image
Binary Segmentation
Binarize segmentation by thresholding pixel intensities
ArrayComponents find identical components
MorphologicalComponents find morphologically connected components
ImageForestingComponents image segmentation using various methods
ClusteringComponents segmentation based on cluster analysis
WatershedComponents segmentation based on watershed methods
Component Analysis
ComponentMeasurements shape and color analysis
Colorize color every segment differently