xkor_canny — 2D segmentation op

Data kinds: imageregion

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

xkor_canny: 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

Edge (binary region) detection by the Canny method. Calls `kornia.filters.canny and adopts the binary edge map (edges`) among its return values (the gradient-magnitude side is discarded).

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

a が低いしきい値(`0.1 + 0.3 * a`)、b が高いしきい値

(`max(低いしきい値 + 1e-3, 0.3 + 0.4 * b)`、低い方を必ず上回るよう

下駄を履かせている)を振る。出力の sort は region

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.

xkor_canny 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_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.