hough_circle_trans — 2D `features` op

• Data kinds: image → image

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

• HALCON equivalent: hough_circle_trans (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.

円検出のための Hough 変換。エッジマスクに対して半径 4〜19(3 刻み)の

円テンプレート群で `skimage.transform.hough_circle` を計算し、全半径での

最大応答を [0,1] に正規化して返す。HALCON の `hough_circle_trans`

（Return the Hough-Transform for circles with a given radius.）に相当

(HALCON は半径を明示指定するが、ここでは固定レンジを総当たりする近似)。

`a がエッジ抽出の閾値を振る。b` は未使用 ―― 探索する半径レンジは

コード側に固定されており、`b` で半径を選ぶことはできない。

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 `image` as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

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).*

hough_circle_trans — 2D features op