xcv2_hitmiss — 2D `region` op

• Data kinds: region → region

• Call: fullseye.apply(img, "xcv2_hitmiss", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Detects the cross pattern 'center is background, up/down/left/right are foreground' using the hit-or-miss transform (`cv2.MORPH_HITMISS`).

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

固定カーネル `[[0,1,0],[1,-1,1],[0,1,0]]` を使う（1=前景必須、-1=背景必須、

0=不問）。`a, b` は未使用。前景に囲まれた 1 画素の窪み（孤立した背景

画素）を拾うので、細線化後の欠け検出や形状のノッチ検出に使える。入力は

しきい値 0.5 で二値化してから判定する。

Detailed usage guide

• gallery2d_region 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_region — py -3.11 examples/gallery2d_region.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 (`region`)

reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small · invert_region

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

xcv2_hitmiss — 2D region op