11.14. ITK Binary Thinning Image Filter

Reduces the foreground objects of a binary image to a one-pixel-wide skeleton.

Group (Subgroup)

ITKBinaryMathematicalMorphology (BinaryMathematicalMorphology)

Description

This filter computes the skeleton (medial axis) of the foreground objects in a binary image: it repeatedly removes boundary pixels until each object is reduced to a connected, one-pixel-wide line that still captures the object’s overall shape and connectivity. Skeletons are useful for analyzing the topology of elongated structures — measuring branch lengths, counting junctions, or tracing networks of fibers, cracks, or vessels.

The input is treated as a binary image; if the foreground pixels are not already valued 1 they are rescaled to 1 internally. In the output, background pixels are 0 and the skeleton pixels are 1.

Caveat: this is a sequential 2D thinning algorithm (the classic Gonzalez & Woods method). On a 3D volume it operates slice by slice rather than producing a true 3D skeleton, and its run time grows with image size.

Required Input Sources

Operates on a binary image — typically the output of a thresholding filter such as ITK Binary Threshold Image Filter or Multi-Threshold Objects.

Reference

Rafael C. Gonzalez and Richard E. Woods. Digital Image Processing. Addison Wesley, 491-494 (1993).

Input Cell Data

Parameter Name

Parameter Type

Parameter Notes

Description

Image Geometry

Geometry Selection

Image

Select the Image Geometry Group from the DataStructure.

Input Cell Data

Array Selection

Allowed Types: int8, uint8, int16, uint16, int32, uint32, int64, uint64

The image data that will be processed by this filter.

Output Cell Data

Parameter Name

Parameter Type

Parameter Notes

Description

Output Cell Data

DataObjectName

The result of the processing will be stored in this Data Array inside the same group as the input data.

Example Pipelines

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