sk_hysteresis — 2D segmentation op

Data kinds: imageregion

Call: fullseye.apply(img, "sk_hysteresis", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

HALCON equivalent: hysteresis_threshold (the HALCON reference is a useful guide to its meaning and parameters)

Usage

Hysteresis thresholding. Uses two threshold levels: pixels above the higher one are confirmed first, then pixels above the lower one that are connected to a confirmed pixel are also adopted -- the same idea as Canny's edge-linking step, applied to general response images.

> The detailed description below is the original text — the summary and the headings are translated.

HALCON の hysteresis_threshold(Perform a hysteresis threshold operation on an image.)に相当。実装は `filters.apply_hysteresis_threshold(v, 0.2+0.3*a, 0.5+0.3*b)` —— a は低い方のしきい値を 0.2〜0.5 に、b は高い方のしきい値を 0.5〜0.8 に振る。a を大きく・b を小さくすると 2 つが逆転しうる(low > high)ので、極端な組み合わせでは skimage 側の挙動に委ねられる点に注意。

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.

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_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.