segmentation op• Data kinds: image → region
• Call: fullseye.apply(img, "adaptive_gauss_thresh", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: local_threshold (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):
▸ adaptive_gauss_thresh: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ adaptive_gauss_thresh: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ adaptive_gauss_thresh: 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).*
Adaptive thresholding based on a locally Gaussian-smoothed mean. Equivalent to HALCON's `local_threshold` (Segment an image using local thresholding.).
> The detailed description below is the original text — the summary and the headings are translated.
`a が基準を作るガウシアンの σ を 1.0〜4.0 に、b がオフセットを -0.15〜+0.15（(b-0.5)*0.3）に振る。v - gaussian_filter(v, σ) > offset を満たす画素を前景にする。**完全に平坦な面は(オフセットが 0 でも)前景にならない** —— 差が 1e-9 を超えたときだけ前景とするので、一様な面で平滑化が最下位 1 ビットずれても全面が前景に反転しない。照明ムラがある画像で大域しきい値（_threshold/_otsu）より安定する。近い op に _dyn_threshold があるが、そちらは箱型平均（uniform_filter）を基準にし、オフセット幅も異なる（±0.2`）——同じ「適応的しきい値」でも基準の平滑化方式とパラメータ範囲が違う別実装。
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.
adaptive_gauss_thresh 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_segmentation — py -3.11 examples/gallery2d_segmentation.py
• poc_matrix_code_reading — py -3.11 examples/poc_matrix_code_reading.py
region as input)identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small
segmentation)threshold · otsu · canny · sk_otsu · sk_li · sk_yen · sk_sauvola · sk_niblack
*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.