edges op• Data kinds: image → image
• Call: fullseye.apply(img, "cv_precorner", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: corner_response (the HALCON reference is a useful guide to its meaning and parameters)

*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).*
Corner candidate detection (preCornerDetect, OpenCV implementation). Scores "corner-ness" with a signed value using a special formula that combines first- and second-order derivatives - originally a function meant to be used as a preceding candidate-detection stage for sub-pixel refinement via `cv2.cornerSubPix`.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の corner_response(Searching corners in images.)に相当(近似)。実装は `|cv2.preCornerDetect(v, ksize=3)|` を正規化したもの。a, b は未使用 —— ksize(Sobel 開口)は 3 に固定。
• 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.
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_precorner 0.40 0.50
▸ Load this pipeline · Load & run
• 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.