segmentation op• Data kinds: image → region
• Call: fullseye.apply(img, "sk_yen", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: binary_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).*
Global thresholding by Yen's maximum correlation criterion. Chooses the threshold by maximizing an entropy-based measure of the histogram -- yet another automatic thresholding method distinct from Otsu's and Li's methods.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の binary_threshold に相当(近似)。実装は `v > filters.threshold_yen(v)` —— a, b は未使用。同じ画像に大津/Li/Yen を並べて試し、しきい値が安定する方を選ぶ用途を想定。
• 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.
sk_yen 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_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.