sk_blur_effect — 2D `features` op

• Data kinds: image → feature

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

Usage

> This operator's description has not been translated yet. The original text follows as it is.

ぼけ具合の推定(1 スカラー特徴量)。画像を意図的に少し再ぼかしして、元と再ぼかし後でどれだけエッジの鋭さが変わるかを比較する手法で、0(ぼけ無し)〜1(最大限ぼけている)のスコアを返す —— 参照画像なしでピント/ブレを定量化できる。

HALCON に直接対応するものは無い。実装は `measure.blur_effect(v)`。a, b は未使用 —— 再ぼかしフィルタのサイズは既定値(11)のまま。

Detailed usage guide

• gallery2d_features 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_features — py -3.11 examples/gallery2d_features.py

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

identity

Same category (`features`)

blob_count · area_frac · count_contours · total_length · vol_count · sk_euler · sk_entropy_feat · cv_cc_count

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

sk_blur_effect — 2D features op