sg_watershed_gradient — 2D `segment` op

• Data kinds: image → region

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

Usage

Returns the boundaries of a watershed segmentation seeded from h-minima markers on the gradient image (`skimage`; no corresponding HALCON operator).

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

Sobel 勾配の大きさを正規化し、深さ `h = 0.02 + a*0.3 の h-minima 変換で生き残った領域極小をマーカーとして（a が大きいほどマーカーが少なく・粗い分割になる）、その勾配画像に対するウォーターシェッドを計算する。b` は未使用。戻り値は集水域（catchment basin/物体）を分けるダムライン（境界）を表す region。

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 (`segment`)

sg_slic_superpixels · sg_felzenszwalb · sg_gmm_segment · sg_kmeans_intensity · sg_region_growing_seeded · sg_normalized_cut_2

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

sg_watershed_gradient — 2D segment op