topology_signature — 3D medial op

• Data kinds: voxel → table

• Call: import fullseye as fs; fs.ledger.topology_signature(skeleton) (to call the implementation directly, import medial; medial.topology_signature(skeleton); from the registry, ops3d.get("topology_signature"))

Usage

Build a topology descriptor from the 26-neighbourhood degrees of a skeleton. Returns the counts of end points, junctions, ordinary points and isolated points.

For each skeleton voxel, counts the number of skeleton voxels in its 26-neighbourhood (degree) and

degree 1 = endpoint

degree 2 = normal point (middle of the skeleton)

degree>=3 = branch point (branch)

degree 0 = isolated point (isolated)

classifies it accordingly. The counts are invariant to translation and rotation (90 degrees), giving a descriptor that coarsely summarises the shape's topology.

Caution (honest): the 26-neighbourhood degree can be overcounted near branches due to diagonal adjacency (a known property of discrete skeletons). The endpoint count is exact at each branch tip, but the branch-point count can lean somewhat high.

Args:

skeleton: skeleton voxels (bool / 0-1 3D).

Returns:

dict: endpoints, branches, normal, isolated, total (total number of skeleton voxels),

degree_hist (degree -> count).

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 table as input)

fuse_to_voxel · mesh_select_lod

Same category (medial)

distance_ridge · skeletonize_vol · medial_axis_points · medial_match · 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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.