threshold op• Data kinds: image2d → table
• Call: import fullseye as fs; fs.ledger.threshold_kittler(image, *, nbins: 'int' = 256) -> 'Dict[str, object]' (to call the implementation directly, import seggraph; seggraph.threshold_kittler(image, *, nbins: 'int' = 256) -> 'Dict[str, object]'; from the registry, opssegmentation.get("threshold_kittler"))
Minimum-error threshold (Kittler–Illingworth 1986): at each bin t, splits into a low side (bins ≤ t) and a high side and minimises J(t) = 1 + 2(P1 ln σ1 + P2 ln σ2) − 2(P1 ln P1 + P2 ln P2) (σ is the standard deviation of the bin centres on each side; bins where either side has σ = 0 are excluded). Returns: threshold = upper edge of that bin (the mask is decided by bin index > t = consistent at the edge values too), mask, bin, criterion (J, nan for excluded bins) (threshold_kittler).
• halcon_segmentation family guide
• graph_hierarchy_and_thresholds — Segmentation from graph, hierarchy and threshold theorems — what is exact, and where the partition breaks down
• 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.
• poc_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py
table as input)threshold)threshold_triangle · threshold_isodata · threshold_kapur
*Provenance: seggraph.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.