xsk3_rank_otsu — 2D `segmentation` op

• Data kinds: image → region

• Call: fullseye.apply(img, "xsk3_rank_otsu", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Local Otsu binarization (skimage `filters.rank.otsu`). Computes an Otsu's-method (discriminant analysis) threshold within a local disk neighborhood only, and binarizes by whether the pixel value exceeds that local threshold - unlike global Otsu, this can select a locally appropriate threshold even on images with uneven illumination.

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

`a は円盤半径(2+int(a*8) で 2〜10)を振る。b` は未使用。

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 (`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).*

xsk3_rank_otsu — 2D segmentation op