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])
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.
• 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.