cv_adaptive_gauss — 2D `segmentation` op

• Data kinds: image → region

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

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

Usage

Thresholding based on a locally Gaussian-weighted average (adaptive threshold, Gaussian variant, OpenCV implementation). Same framework as cv_adaptive_mean, but since the local average is taken as a Gaussian-weighted average rather than a simple average, abrupt changes near the window boundary are less likely to appear.

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

HALCON の local_threshold(Segment an image using local thresholding.)に相当。実装は `cv2.adaptiveThreshold(_u8(v), 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, blockSize=2*int(a*6)+3, C=int(b*10))` —— a は blockSize を 3〜15(奇数)に、b は定数 C を 0〜10 に振る。

Detailed usage guide

• gallery2d_segmentation 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_segmentation — py -3.11 examples/gallery2d_segmentation.py

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

identity · reg_erode · reg_dilate · reg_open · reg_close · fill_holes · select_largest · remove_small

Same category (`segmentation`)

threshold · otsu · canny · adaptive_gauss_thresh · sk_otsu · sk_li · sk_yen · sk_sauvola

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

cv_adaptive_gauss — 2D segmentation op