frei_amp — 2D edges op

Data kinds: imageimage

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

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

frei_amp: 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

Frei-Chen isotropic edge detection. It computes the magnitude via `hypot from a pair of two kernels weighted by √2 -- a classic kernel said to have smaller sensitivity differences across directions (i.e., more isotropic) than Sobel. Equivalent to HALCON's frei_amp` (Detect edges (amplitude) using the Frei-Chen operator.).

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

`a, b` は未使用。固定カーネル 2 本のみ(Frei-Chen 本来の全 9 基底の

一部だけを使った近似)。

Detailed usage guide

gallery2d_edges 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.

frei_amp 0.40 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

gallery2d_edgespy -3.11 examples/gallery2d_edges.py

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

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (edges)

sobel_mag · prewitt_mag · roberts_mag · dog · grad_dir · log · corner_response · sk_scharr


*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.