gray_histo_abs — 2D `features` op

• Data kinds: image → feature

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

• HALCON equivalent: gray_histo_abs (the HALCON reference is a useful guide to its meaning and parameters)

Usage

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

画像の階調の標準偏差(`x.std())を返す。HALCON の gray_histo_abs`

（Calculate the gray value distribution.）は本来ヒストグラム全体

(各階調のビン度数)を返す演算子だが、この代役ではヒストグラムそのものでは

なく分布の広がりを表す標準偏差 1 個のスカラーに要約している(近似 ―― この

パイプラインの `feature` ソートが 1 スカラーである契約上の制約)。

`a, b` は未使用。

Detailed usage guide

• gallery2d_features 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_features — py -3.11 examples/gallery2d_features.py

Ops the type connects to (they accept `feature` as input)

identity

Same category (`features`)

blob_count · area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat · sk_blur_effect

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

gray_histo_abs — 2D features op