world_gradient_illumination — 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_gradient_illumination(seed: 'int' = 0, *, size=(160, 220), n_objects: 'int' = 8, gradient=(0.45, 0.2), i0: 'float' = 0.3, reflectance: 'float' = 0.35, noise: 'float' = 0.03) -> 'Dict[str, object]' (to call the implementation directly, import segworld; segworld.world_gradient_illumination(seed: 'int' = 0, *, size=(160, 220), n_objects: 'int' = 8, gradient=(0.45, 0.2), i0: 'float' = 0.3, reflectance: 'float' = 0.35, noise: 'float' = 0.03) -> 'Dict[str, object]'; from the registry, opssegmentation.get("world_gradient_illumination"))

Usage

World of dark objects over an illumination gradient plus noise (global thresholding breaks; local thresholding / flat-field cut it) (world_gradient_illumination).

I(x, y) = i0 + g_x x/(W−1) + g_y y/(H−1) (i0 + g_x + g_y ≤ 1), image = I · R + noise. R = 1 for background, reflectance for objects. Objects are circles (radius 8-14) and rectangles with integer sides (14-28), kept apart from each other.

Returns: image, labels (1..n), illumination, reflectance_map, truth = {n_objects, objects (kind, params), areas (πr² / w h), i0, gradient, reflectance, noise}.

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_thin_structures · 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.