sk_yen — 2D segmentation op

Data kinds: imageregion

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)

sk_yen: 入力 → 出力

*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).*

Usage

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。

Detailed usage guide

gallery2d_segmentation family guide

References (sample data, literature)

• 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.

Try it in Studio

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

Runnable examples (verified samples that actually call this op)

gallery2d_segmentationpy -3.11 examples/gallery2d_segmentation.py

Ops the type connects to (they accept region as input)

identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small

Same category (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.