features op• Data kinds: image → image
• Call: fullseye.apply(img, "hough_line_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_line_trans (the HALCON reference is a useful guide to its meaning and parameters)
The Hough transform accumulator for line detection. First creates an edge mask from the Sobel gradient, computes the accumulator space (angle x distance) with `skimage.transform.hough_line, normalizes it, then resizes it to the same pixel shape as the input before returning (visualized as an image rather than in the accumulator's own coordinate system). Corresponds to HALCON's hough_line_trans` (Produce the Hough transform for lines within regions.).
> 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(0.2〜0.6)を振る。b` は未使用。半径・角度分解能
は skimage の既定値に固定されている。
• gallery2d_features family guide
• 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.
• gallery2d_features — py -3.11 examples/gallery2d_features.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
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.