canny3d — 3D `edges` op

• Data kinds: voxel → voxel

• Call: import fullseye as fs; fs.ledger.canny3d(vol, low: 'float', high: 'float', sigma: 'float' = 1.0) -> 'np.ndarray' (to call the implementation directly, import edges3d; edges3d.canny3d(vol, low: 'float', high: 'float', sigma: 'float' = 1.0) -> 'np.ndarray'; from the registry, ops3d.get("canny3d"))

Usage

3-D Canny edge detection (non-maximum suppression + hysteresis).

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

Parameters

----------

vol : (D,H,W) array

グレー voxel。

low, high : float

ヒステリシスの下限 / 上限閾値(勾配の大きさに対して)。0 <= low <= high, high > 0。

sigma : float

平滑の標準偏差。

Returns

-------

edge_mask : (D,H,W) bool

1 voxel に細線化されたエッジ。

Notes

-----

(1) gradient3d で平滑勾配を得る → (2) 勾配方向に沿った NMS(三線形補間)で局所最大を残し

→ (3) high 閾値を種に low 閾値で 26 連結を伸長。閾値は絶対値なので、対象に応じて

gmag.max() のスケールで与えるとロバスト。

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.

Runnable examples (verified samples that actually call this op)

• edges_3d — py -3.11 examples_3d/edges_3d.py

Ops the type connects to (they accept `voxel` as input)

voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa

Same category (`edges`)

gradient3d · log_zero_crossings · link_edges · edge_points

*Provenance: edges3d.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

canny3d — 3D edges op