xmh_bernsen — 2D `segmentation` op

• Data kinds: image → region

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

Usage

> This operator's description has not been translated yet. The original text follows as it is.

Bernsen 局所二値化(`mahotas.thresholding.bernsen`)。近傍の最大輝度と最小輝度の中間値をローカル閾値とし、コントラストが低い領域だけ大域しきい値にフォールバックする。

`a は近傍半径(3〜15 px)、b` はコントラスト閾値(5〜55。これを下回る低コントラスト域はグローバル閾値 128 で代用)を振る。濃淡ムラのある照明下でのエッジ二値化に向く。

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).*

xmh_bernsen — 2D segmentation op