monotony — 2D gray op

• Data kinds: image → image

• Call: fullseye.apply(img, "monotony", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: monotony (the HALCON reference is a useful guide to its meaning and parameters)

Usage

> This operator's description has not been translated yet. The original text follows as it is.

画素値がその 8 近傍の中で何番目に大きいか（単調性、monotony）を [0,1] で返す。中心より小さい近傍の数を数えて 8 で割るので、値 1.0 は中心が近傍全てより大きい局所最大、0.0 は局所最小に近いことを示す。a, b は未使用。

エッジの向き（明→暗か暗→明か）を区別できる非対称なエッジ検出に使う。HALCON の `monotony`（単調性演算の計算）に相当。

Detailed usage guide

• gallery2d_gray_arith family guide

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)

• gallery2d_gray_arith — py -3.11 examples/gallery2d_gray_arith.py

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

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (gray)

gamma · invert · scale_clip · equalize · sigmoid · clahe · sk_adapthist · sk_enhance_contrast

*Provenance: ops.py — 2D 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.