edges op• Data kinds: image → image
• Call: fullseye.apply(img, "cv_min_eigen", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: points_harris (the HALCON reference is a useful guide to its meaning and parameters)
Corner strength via the minimum eigenvalue (Shi-Tomasi family, OpenCV implementation). Returns the smaller of the two eigenvalues of the gradient structure tensor - unlike Harris, there is no weighting (dependent on k), making it a more direct measure of "good feature point"-ness (the same kind of criterion used internally by cv_good_features).
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の points_harris に相当(近似。アルゴリズムは別物)。実装は `cv2.cornerMinEigenVal(v, blockSize=3+2*int(a*2))` を正規化したもの —— a は評価に使う近傍サイズ(blockSize)を 3, 5, 7 に振る。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.