sg_gmm_segment — 2D segment op

Data kinds: imageregion

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

Usage

Fits a 2-class Gaussian mixture model (EM algorithm) to the intensity values and returns the brighter cluster as the region (a self-contained EM implementation independent of `skimage`; no corresponding HALCON operator).

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

25/75 パーセンタイルで初期化した決定論的 EM で 1 次元 2 成分ガウス混合をフィットし、平均が高い方を「明るいクラス」とする。`a(0〜1)は事後確率のしきい値 t = 0.25 + 0.5*a を振り、大きいほど「確実に明るい」と判定された画素だけを拾うようになる。b` は未使用。乱数を使わないので再現性がある。

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_segmentationpy -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 (segment)

sg_slic_superpixels · sg_felzenszwalb · sg_kmeans_intensity · sg_region_growing_seeded · sg_normalized_cut_2 · sg_watershed_gradient


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

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.