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Thinning
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BUILT-IN MATHEMATICA SYMBOL
SkeletonTransform
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Pruning
MorphologicalGraph
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Image Processing & Analysis
Mathematical Morphology
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Thinning
Thinning
[
image
]
finds the skeletons of foreground regions in
image
by applying morphological thinning until convergence.
Thinning
performs
n
iterations of morphological thinning.
Thinning
treats values above
t
as foreground.
MORE INFORMATION
Thinning
yields a binary image in which pixels representing the morphological skeleton have value 1 and others have value 0.
Thinning
[
image
]
is equivalent to
Thinning
[
image
,
Infinity
]
.
Thinning
works with binary, grayscale, and arbitrary multichannel images, as well as real matrices.
Thinning
takes a
Padding
option that specifies the values to assume for pixels outside the image. The default setting is
Padding
.
Thinning supports a
Method
option which specifies what thinning algorithm to be used. Possible settings include:
"Morphological"
morphological thinning (default)
"MedialAxis"
approximate medial axis
EXAMPLES
CLOSE ALL
Basic Examples
(1)
Morphological thinning of an image:
Morphological thinning of an image:
In[1]:=
Out[1]=
Scope
(2)
Applying the morphological thinning to a label matrix:
Thinning a grayscale image using a specific foreground threshold:
Options
(3)
Find the approximate medial axis:
The padding value affects objects adjacent to the boundary:
Pad with the foreground value:
Applications
(2)
Simplify features in a fingerprint image:
Use the image skeleton to construct a graph:
Neat Examples
(2)
Extract possible paths through a maze:
Find the approximate Voronoi diagram of the foreground objects:
SEE ALSO
SkeletonTransform
DistanceTransform
Pruning
MorphologicalGraph
MORE ABOUT
Image Processing & Analysis
Mathematical Morphology
New in 8.0: Alphabetical Listing
New in 8.0: Data Manipulation
New in 8