lines_gauss — 2D `contour` op

• Data kinds: image → contour

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

• HALCON equivalent: lines_gauss (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.

線状構造(リッジ)検出。`skimage.filters.frangi`(血管様のリッジ強調

フィルタ)の応答をしきい値(`0.1+0.4*a`)で二値化し、連結成分を輪郭点群

として返す。HALCON の `lines_gauss`（Detect lines and their width.）が

本来行う「線の中心線+幅の推定」ではなく、リッジ強調画像のしきい値化に

単純化している(線幅の情報は返らない近似)。

`a がリッジ検出のしきい値を振る。b` は未使用。skimage が無い環境

ではこの分岐は呼べない。

Detailed usage guide

• gallery2d_contour_measure 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_contour_measure — py -3.11 examples/gallery2d_contour_measure.py

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

identity · select_contours · smooth_contours · fit_line_contours · contours_to_region · count_contours · total_length · select_contours_xld

Same category (`contour`)

select_contours · smooth_contours · fit_line_contours · contours_to_region · sk_find_contours · edges_sub_pix · select_contours_xld · smooth_contours_xld

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

lines_gauss — 2D contour op