sp_local_max_sub_pix — 2D `subpix` op

• Data kinds: image → contour

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

Usage

Detects local maxima of the gray-value surface with sub-pixel accuracy (an alternative implementation of HALCON `local_max_sub_pix. halcon=""`: not double-claimed under that name because an existing core op already covers the same coordinates).

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

3x3 近傍に 2 次曲面 `z = a0+a1 x+a2 y+a3 x^2+a4 y^2+a5 xy を最小二乗フィットし、勾配 0 の点へのオフセットを解いてサブピクセル位置を求める（ヘッセ行列が退化する場合は 1 次元放物線補間にフォールバック）。aは極大の顕著さ（周囲の最小値からの深さ）のしきい値を 0.01〜0.31 に振る（thr = 0.01 + 0.30*a）。b は未使用。戻り値は CONTOUR、座標の単位は入力画像のピクセル（小数値＝サブピクセル）。検出点数はcount_contours` で数えられる。

Detailed usage guide

• gallery2d_geometry family guide

Background guides (the physics and conventions behind this op)

• measurement_uncertainty — 計測の不確かさと校正の知識 — 「測れている」を主張するために

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_geometry — py -3.11 examples/gallery2d_geometry.py

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

identity · select_contours · smooth_contours · fit_line_contours · contours_to_region · count_contours · total_length · select_contours_xld

Same category (`subpix`)

sp_local_min_sub_pix · sp_saddle_points_sub_pix · sp_critical_points_sub_pix · sp_plateaus · sp_lowlands_center

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

sp_local_max_sub_pix — 2D subpix op