segmentation op• Data kinds: image → region
• Call: fullseye.apply(img, "zero_crossing", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: zero_crossing (the HALCON reference is a useful guide to its meaning and parameters)
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ zero_crossing: knob a sweep (docs site)
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ zero_crossing: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
Detects pixels where the sign of the Laplacian (with built-in Gaussian smoothing, sigma `0.5+2*a) flips (zero crossings). LoG zero crossings are a classic detection method known for locating edges with high precision. Corresponds to HALCON's zero_crossing` (Extract zero crossings from an image.).
> The detailed description below is the original text — the summary and the headings are translated.
`a がガウス平滑化のシグマを振る。b` は未使用。上下・左右いずれかの
方向で符号が変わればゼロ交差とみなす(斜め方向は直接見ていない)。
Border handling: mirror repeating the edge pixel (d c b a | a b c d — scipy's default `reflect) (measured; tools/impl2/border_probe.py`).
Blank frame (measured): feeding an image of uniform brightness gives an empty result — every pixel is background (0) — regardless of the brightness. Pure white and pure black behave alike; brightness by itself detects nothing.
• gallery2d_segmentation 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.
zero_crossing 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_segmentation — py -3.11 examples/gallery2d_segmentation.py
region as input)identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small
segmentation)threshold · otsu · canny · adaptive_gauss_thresh · sk_otsu · sk_li · sk_yen · sk_sauvola
*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.