r3_background_seg — 2D `region` op

• Data kinds: region → region

• Call: fullseye.apply(img, "r3_background_seg", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

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

Usage

Splits the region's background (the complement of the foreground) into connected components, discards components that are too small, and returns the rest (equivalent to HALCON `background_seg`).

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

背景を連結成分ラベリングし、`a（0〜1）を「最大背景成分の面積に対する相対しきい値」としてそれ未満の成分を除去する（a=0 で全背景＝正真正銘のbackground_seg 結果）。b` は未使用。

Detailed usage guide

• gallery2d_region 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_region — py -3.11 examples/gallery2d_region.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 (`region`)

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

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

r3_background_seg — 2D region op