# Wolfram Language & System 11.0 (2016)|Legacy Documentation

This is documentation for an earlier version of the Wolfram Language.
BUILT-IN WOLFRAM LANGUAGE SYMBOL

# RegionBinarize

RegionBinarize[image,marker,d]
gives a binary version of image that includes the foreground pixels of marker and also connected regions whose pixel values are within a distance d.

RegionBinarize[image,marker,d,{t1,t2}]
grows regions in marker by adding pixels whose average intensity is also constrained within an interval {t1,t2}.

## Details and OptionsDetails and Options

• RegionBinarize implements a variety of region-growing methods to find a binary segmentation of an image.
• RegionBinarize works with arbitrary 2D as well as 3D images.
• The target region marker can be any of the following:
•  markerimage a marker image {pos1,pos2,…} a list of positions
• Positions posi are assumed to be in the standard image coordinate system.
• RegionBinarize takes a Method option to specify how to compute the distance between the values of pixels to be added and the image region to be grown. Pixels are included in the segmentation only if the distance is less than or equal to d. Possible settings are:
•  "MeanEuclidean" Euclidean distance to the mean of the region to be grown "Mahalanobis" Mahalanobis distance
• The default setting is Method->"MeanEuclidean".
• The "Mahalanobis" distance is a Euclidean distance with a metric that is the inverse of the covariance matrix of pixel values in the region to be grown. If the initial region consists of only one or two pixels, then the covariance matrix is computed from a range-1 neighborhood around those pixels.
• RegionBinarize[image,marker,d,backgroundmarker] grows regions starting from marker by adding only pixels that are not connected to backgroundmarker.
• The possible range for the distance parameter d depends on the distance method used as well as the dimension of the color space.
• With a setting , RegionBinarize is applied up to n times, using the previous result as the marker in each iteration.

## ExamplesExamplesopen allclose all

### Basic Examples  (2)Basic Examples  (2)

Binary segmentation of a color image:

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Binary segmentation of a 3D image:

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