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)
Returns, in [0,1], how large a pixel value ranks among its 8 neighbors (monotony). It counts the number of neighbors smaller than the center and divides by 8, so a value of 1.0 indicates a local maximum where the center exceeds all neighbors, and 0.0 indicates something close to a local minimum. a and b are unused.
> The detailed description below is the original text — the summary and the headings are translated.
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。
• gallery2d_gray_arith family guide
• 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.
• gallery2d_gray_arith — py -3.11 examples/gallery2d_gray_arith.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
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.