medial_match — 3D `medial` op

• Data kinds: voxel × voxel → measurement

• Call: import fullseye as fs; fs.ledger.medial_match(vol_a, vol_b, w_topology=0.6, w_radius=0.4, n_bins=12) (to call the implementation directly, import medial; medial.medial_match(vol_a, vol_b, w_topology=0.6, w_radius=0.4, n_bins=12); from the registry, ops3d.get("medial_match"))

Usage

A coarse matching score between two voxel shapes based on their medial (topology + radius distribution). Returns [0,1].

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

骨格の位相記述子(端点/分岐/通常/孤立の割合)の距離と、medial 半径分布(内接半径の

ヒストグラム)の距離を重み付き合成し、類似度 = 1 - 距離として返す。1 に近いほど似ている。

平行移動・回転(90 度)に対して概ね不変で、位相ベースの初期照合(粗いふるい)に使う。

Args:

vol_a, vol_b: バイナリ voxel(bool / 0-1 の 3D)。

w_topology: 位相距離の重み(既定 0.6)。

w_radius: 半径分布距離の重み(既定 0.4)。

n_bins: 半径ヒストグラムの bin 数。

Returns:

float: 類似スコア [0,1] (大きいほど類似)。

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)

• medial_topology — py -3.11 examples_3d/medial_topology.py

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

vol_gaussian_psf · fuse_to_voxel · fresnel_reflectance · snell_angle

Same category (`medial`)

distance_ridge · skeletonize_vol · medial_axis_points · topology_signature · skeleton_junctions3d · skeleton_endpoints3d · skeleton_prune3d · skeleton_branches3d

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

medial_match — 3D medial op