segmentation op• Data kinds: image → region
• Call: fullseye.apply(img, "sk_chan_vese", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
Chan-Vese segmentation. An active contour model that iteratively moves a level set so that the brightness variance within each region is minimized, allowing detection of regions even for objects without sharp edges.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON に直接対応するものは無い。実装は `segmentation.chan_vese(v, mu=0.1+0.4*a, max_num_iter=60)` —— a は'edge length' 重み mu を 0.1〜0.5 に振る(大きいほど輪郭が丸く滑らかになり細部を無視しやすくなる)。反復回数は 60 に固定。b は未使用。初期レベルセットは既定の 'checkerboard'(チェッカーボード状)。
• 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.