self-similarity op• Data kinds: image → image
• Call: fullseye.apply(img, "xmh_selfmatch", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*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).*
Self-similarity map (self-template matching using `mahotas.template_match`). Template-matches a small patch cut from the center of the image against the whole image, and normalizes the result so that locations more similar to the patch approach 1.
> The detailed description below is the original text — the summary and the headings are translated.
`a はパッチの半径(3+8 px 相当)を振る —— 大きくするほど広い範囲の類似度になる。b` は未使用。周期的なテクスチャや繰り返しパターンの検出に使える。
• gallery2d_features 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.
xmh_selfmatch 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_features — py -3.11 examples/gallery2d_features.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
self-similarity)—
*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.