segmentation op• Data kinds: image → image
• Call: fullseye.apply(img, "xsk2_multiotsu", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
Quantizes tonal levels using multi-level Otsu's method, an extension of Otsu's discriminant analysis method to multiple thresholds. Uses `skimage.filters.threshold_multiotsu`.
> The detailed description below is the original text — the summary and the headings are translated.
a はクラス数を 3 または 4 に切り替える（`3 + int(a > 0.5)`）。
5 クラス以上は実装していない——多値大津はしきい値の全探索コストが
`bins ** (classes - 1)` で増えるため、実測（128x128）で 3 クラス
0.0008 秒に対し 5 クラスは 2.435 秒（3239 倍）かかり、進化ループ 1 世代
だけで実行が止まって見えるほど遅い（画像サイズにはほぼ依らない）。
4 クラスなら 0.025 秒に収まる。b は未使用。しきい値で量子化した後
`(cls-1)` で割って [0,1] に正規化する。
• 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
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
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.