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])

xsk_hessian_eig: 入力 → 出力

*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).*

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.

Try it in Studio

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.

xsk_hessian_eig 0.40 0.50

▸ Load this pipeline · Load & run

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