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)
*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*
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.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
monotony 0.50 0.50
▸ Load this pipeline · Load & run
• 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.