vol_label_color_flicker — VOLCOLOR diagnose op

• Data kinds: voxel → table

• Call: import fullseye as fs; fs.ledger.vol_label_color_flicker(vol_binary, axis='z', seed: 'int' = 0, connectivity: 'int' = 26, connectivity_2d: 'int' = 8) (to call the implementation directly, import volcolor; volcolor.vol_label_color_flicker(vol_binary, axis='z', seed: 'int' = 0, connectivity: 'int' = 26, connectivity_2d: 'int' = 8); from the registry, opsvolcolor.get("vol_label_color_flicker"))

Usage

Count the difference between "segment then colour" and "colour then segment".

Takes 2 procedures on the same 2-valued (binary) volume:

A. Per slice -- each section is connected-component labelled in 2-D and

coloured with the same palette as imgio.colorize_labels.

Numbers are reassigned per section, so even the same part can change colour when the layer changes.

B. On the volume -- labelled with volops.vol_label, then

coloured with vol_colorize_labels, and sliced afterwards.

Returns a dict:

n_components number of 3-D components · n_slices number of sections ·

slices_with_change number of sections in which the colour of at least 1 component changed under A ·

changed_pairs number of (component, section) pairs whose colour changed under A ·

changed_components number of components whose colour changed at least once under A ·

volume_slices_with_change / volume_changed_pairs /

volume_changed_components the same quantities for B (0 by construction) ·

pairs_checked total number of (component, section) pairs compared ·

flicker_rate changed_pairs / pairs_checked.

Definition of the comparison: for each 3-D component c, the colour in the first section where c appears is the reference, and in each later section, if the most frequent colour of c's pixels differs from the reference, it counts as 1 (1 3-D component can split into several 2-D pieces in 1 section, so the representative is the most frequent colour; ties go to the smaller in RGB lexicographic order = deterministic).

Measured ((24, 48, 48), reference phantom of 16 spheres, seed=0, axis="z", connectivity=26 / connectivity_2d=8): pairs_checked=108, slices_with_change=20 / 24, changed_pairs=62 (57.4 %), changed_components=16 / 16. On side B all 3 are 0 -- 0 by construction, not 0 by chance (because label numbers are unique across the whole volume).

Raises ValueError for a bad volume, an unknown *axis*, or a *connectivity* that is not 6 / 18 / 26 (2-D: 4 / 8).

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.

Runnable examples (verified samples that actually call this op)

• voxel_labels_color — py -3.11 examples/voxel_labels_color.py

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

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Same category (diagnose)

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*Provenance: volcolor.py — VOLCOLOR 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.