sg_kmeans_intensity — 2D segment op

• Data kinds: image → region

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

Usage

Applies k-means clustering to the intensity values and returns the brightest cluster as the region (a self-contained Lloyd's-algorithm implementation; no corresponding HALCON operator).

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

`a（0〜1）からクラスタ数 k = 2 + round(4*a)（2〜6）を決める。初期値はパーセンタイルから決定論的に置くので乱数は使わない。b` は未使用。重心が最も高いクラスタに属する画素を領域として返す。

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 (segment)

sg_slic_superpixels · sg_felzenszwalb · sg_gmm_segment · 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.