m1_measure_pos — 2D `measure1d` op

• Data kinds: image → contour

• Call: fullseye.apply(img, "m1_measure_pos", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: measure_pos (the HALCON reference is a useful guide to its meaning and parameters)

Usage

Extracts sub-pixel edge positions along a caliper line through the centre (equivalent to HALCON `measure_pos`: detects straight edges perpendicular to a rectangle/arc).

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

線は画像中心を通り、`a で向きを theta = a*pi に振る。輝度プロファイルをガウシアンで軽く平滑化してから |d/ds gray| のピークをサブピクセル（3 点放物線補間）で検出し、b（0〜1）を最大振幅に対する相対しきい値として弱いエッジを捨てる。戻り値は CONTOUR（{"shape": (H,W), "cs": [1x2 の (row, col) 点, ...]}）、座標単位は入力画像のピクセル。主な使い道はエッジ数を count_contours`で数えること。

Detailed usage guide

• gallery2d_contour_measure 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_contour_measure — py -3.11 examples/gallery2d_contour_measure.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 (`measure1d`)

m1_measure_projection · m1_measure_thresh · m1_measure_pairs · m1_fuzzy_measure_pos

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

m1_measure_pos — 2D measure1d op