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

FindThreshold   ▪ Threshold   ▪ ImageClip

Binary Segmentation

Binarize — segmentation by thresholding pixel intensities

MorphologicalBinarize   ▪ RegionBinarize   ▪ ChanVeseBinarize

Segmentation

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

SelectComponents   ▪ DeleteSmallComponents   ▪ DeleteBorderComponents

Colorize — color every segment differently

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