edges op• Data kinds: image → image
• Call: fullseye.apply(img, "dots_image", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: dots_image (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).*
A Laplacian of Gaussian (LoG) filter. Takes the Laplacian of a Gaussian kernel with sigma = 0.5+2.5a, normalized as signed01 (a signed value mapped to [0,1], with 0.5 = zero response). b is unused. Because circular dot-like patterns produce a strong LoG response due to the isotropy of the Gaussian, this is used to enhance circular dots.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の `dots_image`（画像中の円形ドットを強調する演算）に相当する近似で、専用のドット検出カーネルではなく一般的な LoG フィルタで代用している。
• 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.
dots_image 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.