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.
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
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
ComponentMeasurements — shape and color analysis
Colorize — color every segment differently
