pouring — 2D `segmentation` op

• Data kinds: image → region

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

• HALCON equivalent: pouring (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.

分水嶺法（watershed）による領域分割の境界抽出。勾配画像（Sobel 振幅）を地形とみなし、暗い領域（`x < 0.2+0.3a）を種（マーカー）として分水嶺を計算、skimage.segmentation.find_boundaries` で境界を前景として返す。b は未使用。

HALCON の `pouring（水を注ぐように画素値の低い場所から領域を満たしていく古典的な pouring アルゴリズムで分割する演算）に相当する近似 —— アルゴリズムの詳細は異なるが、低輝度領域を起点に領域を広げるという発想は共通。watersheds/watersheds_threshold` と実装を共有する。

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).*

pouring — 2D segmentation op