cv_hough_lines — 2D `features` op

• Data kinds: image → feature

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

• HALCON equivalent: hough_lines (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.

確率的 Hough 変換による直線(線分)検出(1 スカラー特徴量、OpenCV 実装)。まず Canny でエッジ画像を作り、そこから直線状に並ぶエッジ画素の集合を投票方式で探して線分として検出する —— ここでは検出できた線分の本数だけを返す(0 本なら 0)。

HALCON の hough_lines(Detect lines in edge images with the help of the Hough transform and returns it in HNF.)に相当(近似。線のパラメータではなく本数のみ)。実装は `cv2.HoughLinesP(Canny(_u8(v),50,150), 1, pi/180, threshold=int(20+40*a), minLineLength=int(10+20*b), maxLineGap=5)` —— a は投票数のしきい値(直線と認める最低票数)を 20〜60 に、b は最小線分長を 10〜30 に振る。Canny の内部しきい値(50, 150)と maxLineGap(5)は固定。

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).*

cv_hough_lines — 2D features op