regiongrowing_mean — 2D `segmentation` op

• Data kinds: image → region

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

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

Usage

> This operator's description has not been translated yet. The original text follows as it is.

実装は `regiongrowing` と同一(しきい値によるシード生成+膨張)。

HALCON の `regiongrowing_mean`（Perform a region growing using mean gray

values.）は本来、各領域の平均輝度との近さを基準に成長させる演算子だが、

この代役では平均輝度による判定を行わず `regiongrowing` と同じ処理を

返す(近似の限界)。

`a がシードのしきい値、b` が膨張の反復回数を振る。両方が使われる。

Detailed usage guide

• gallery2d_segmentation 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_segmentation — py -3.11 examples/gallery2d_segmentation.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 (`segmentation`)

threshold · otsu · canny · adaptive_gauss_thresh · sk_otsu · sk_li · sk_yen · sk_sauvola

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

regiongrowing_mean — 2D segmentation op