ncc_locate — 2D `matching` op

• Data kinds: image → match

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

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

Usage

Finds the best position using template matching based on normalized cross-correlation (NCC). Equivalent to HALCON's `find_ncc_model` (Find the best matches of an NCC model in an image.).

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

`a, b は未使用——テンプレートは引数ではなく set_match_template でスレッドローカルな _MATCH_CTX に事前登録しておく（マッチング系 op 共通の作法、_MatchCtx の docstring 参照）。_ncc_map（NCC 相関マップ、Lewis 1995 の定義で [-1,1]）を計算し、その最大値の位置を [相関値, y, x] で返す。テンプレート未設定、または入力が 2 次元画像でない場合は [0,0,0]（no-match）を返す——fail-closed。回転・スケール変化には非対応（_shape_locate` は回転を扱う）。

Detailed usage guide

• gallery2d_contour_measure 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_contour_measure — py -3.11 examples/gallery2d_contour_measure.py

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

identity

Same category (`matching`)

shape_locate

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

ncc_locate — 2D matching op