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])
*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*
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。
• gallery2d_segmentation family guide
• 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.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
sg_watershed_gradient 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_segmentation — py -3.11 examples/gallery2d_segmentation.py
region as input)identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small
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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.