edges op• Data kinds: image → image
• Call: fullseye.apply(img, "cv_scharr", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: edges_image (the HALCON reference is a useful guide to its meaning and parameters)
Scharr gradient magnitude (OpenCV implementation). Sums the absolute values of the horizontal and vertical Scharr derivatives to obtain the gradient magnitude - the same kind of edge detection as sk_scharr (the skimage version), but the combination method (sum of absolute values instead of the norm of the sum of squares) differs, so the results are not identical.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の edges_image に相当(近似)。実装は `|cv2.Scharr(v,CV_64F,1,0)| + |cv2.Scharr(v,CV_64F,0,1)|` を正規化したもの。a, b は未使用。
• gallery2d_edges 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_edges — py -3.11 examples/gallery2d_edges.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
edges)sobel_mag · prewitt_mag · roberts_mag · dog · grad_dir · log · corner_response · sk_scharr
*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.