segmentation op• Data kinds: image → region
• Call: fullseye.apply(img, "cv_adaptive_gauss", 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 real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*
Thresholding based on a locally Gaussian-weighted average (adaptive threshold, Gaussian variant, OpenCV implementation). Same framework as cv_adaptive_mean, but since the local average is taken as a Gaussian-weighted average rather than a simple average, abrupt changes near the window boundary are less likely to appear.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の local_threshold(Segment an image using local thresholding.)に相当。実装は `cv2.adaptiveThreshold(_u8(v), 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, blockSize=2*int(a*6)+3, C=int(b*10))` —— a は blockSize を 3〜15(奇数)に、b は定数 C を 0〜10 に振る。
• 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.
cv_adaptive_gauss 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.