distance_transform — 2D region op

Data kinds: regionimage

Call: fullseye.apply(img, "distance_transform", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

HALCON equivalent: distance_transform (the HALCON reference is a useful guide to its meaning and parameters)

Usage

An image obtained by normalizing the Euclidean distance transform (`ndimage.distance_transform_edt) by its maximum value. It represents, for each foreground pixel, the distance to the nearest background pixel -- the larger the value, the "deeper" the pixel is inside the region. Note that the output type is image, not region. Equivalent to HALCON's distance_transform` (Compute the distance transformation of a region.).

> The detailed description below is the original text — the summary and the headings are translated.

`a, b` は未使用。

Detailed usage guide

gallery2d_region family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

gallery2d_regionpy -3.11 examples/gallery2d_region.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (region)

reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small · invert_region


*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.