cv_hough_lines — 2D features op

Data kinds: imagefeature

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)

cv_hough_lines: 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

Line (line-segment) detection via the probabilistic Hough transform (a single scalar feature, OpenCV implementation). First creates an edge image with Canny, then uses a voting scheme to find sets of edge pixels arranged in a line and detects them as segments - here, only the number of detected segments is returned (0 if none).

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

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.

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.

cv_hough_lines 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

gallery2d_featurespy -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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.