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)
Boundary extraction via watershed segmentation. Treats a gradient image (Sobel amplitude) as terrain, computes the watershed using dark regions (`x < 0.2+0.3a) as seeds (markers), and returns the boundaries as foreground using skimage.segmentation.find_boundaries`. b is unused.
> The detailed description below is the original text — the summary and the headings are translated.
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。
• 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.
• 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
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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.