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)

hough_circle_trans: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

The Hough transform for circle detection. Computes `skimage.transform.hough_circle on the edge mask with a set of circle templates of radius 4 to 19 (in steps of 3), and returns the maximum response across all radii normalized to [0,1]. Corresponds to HALCON's hough_circle_trans` (Return the Hough-Transform for circles with a given radius.) (HALCON explicitly specifies the radius, but this is an approximation that brute-forces a fixed range).

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

`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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

hough_circle_trans 0.50 0.50

▸ Load this pipeline · Load & run

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