thinning_golay — 2D `region` op

• Data kinds: region → region

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

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

Usage

Thins a region. The implementation uses skimage's `thin` (Guo-Hall-type iterative thinning), repeated until the region is completely 1 pixel wide; a and b are unused.

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

HALCON の `thinning_golay`（Golay アルファベットの構造要素を使ったヒット・オア・ミス変換で 1 ステップぶんだけ細線化する演算、通常は反復して使う）とはアルゴリズムも粒度も異なる近似 —— 単一ステップではなく収束するまで細線化してしまう。

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_region — py -3.11 examples/gallery2d_region.py

Ops the type connects to (they accept `region` as input)

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

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).*

thinning_golay — 2D region op