xsk_hessian_eig — 2D `edges` op

• Data kinds: image → image

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

Usage

Blob/ridge strength based on the largest eigenvalue (absolute value) of the Hessian matrix.

> The detailed description below is the original text — the summary and the headings are translated.

skimage.feature.hessian_matrix(ガウス微分によるヘッセ行列)から

固有値を求め、絶対値が最大の成分 `ev[0] を _norm` で正規化して

返す。曲率が強い箇所(ブロブの中心や稜線)ほど値が大きくなる。

`a が微分のスケール sigma` を 0.5〜3.0 に振る(大きいほど太い

構造に反応)。`b` は未使用。符号は捨てているため、山(明るい

blob)と谷(暗い blob)を区別しない。

Detailed usage guide

• gallery2d_edges 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_edges — py -3.11 examples/gallery2d_edges.py

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

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

Same category (`edges`)

sobel_mag · prewitt_mag · roberts_mag · dog · grad_dir · log · corner_response · sk_scharr

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

xsk_hessian_eig — 2D edges op