world_thin_structures — SEGMENTATION world op

• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)

• Call: import fullseye as fs; fs.ledger.world_thin_structures(seed: 'int' = 0, *, size=(200, 200), n: 'int' = 6, widths: 'Sequence[float]' = (1.0, 2.0, 3.0), noise: 'float' = 0.03) -> 'Dict[str, object]' (to call the implementation directly, import segworld; segworld.world_thin_structures(seed: 'int' = 0, *, size=(200, 200), n: 'int' = 6, widths: 'Sequence[float]' = (1.0, 2.0, 3.0), noise: 'float' = 0.03) -> 'Dict[str, object]'; from the registry, opssegmentation.get("world_thin_structures"))

Usage

World of 1-3 px lines (straight) and cracks (polylines); ground truth = centrelines and widths (world_thin_structures).

Structure k alternates between a straight line (2 points) and a polyline (a random walk of 7 points); widths cycle through widths. A pixel belongs to the structure if its distance from the centerline ≤ w/2. Image = bright background (0.82 + gentle gradient) with dark lines that are fainter the thinner they are (w = 1: 0.5, 2: 0.38, 3: 0.26), edges anti-aliased by distance, slight blur + noise.

Returns: image, labels, distance (distance from each pixel to the nearest centerline), truth = {n, kinds, widths, lengths (Σ segments), length_total, polylines (list of (m, 2) [y, x]), areas_stadium (L w + π w²/4)}.

Detailed usage guide

• halcon_segmentation family guide

Background guides (the physics and conventions behind this op)

• segmentation_scoring_and_worlds — Scoring segmentations and synthetic worlds with ground truth — which metric is blind to which failure

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)

• poc_active_contours — py -3.11 examples/poc_active_contours.py

• poc_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py

• poc_segmentation_gauntlet — py -3.11 examples/poc_segmentation_gauntlet.py

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

class_ndim_norm

Same category (world)

world_blobs_touching · world_grains_voronoi · world_parts_with_shadow · world_texture_regions · world_gradient_illumination · lens_area · voronoi_cells

*Provenance: segworld.py — SEGMENTATION 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.