sk_clear_border — 2D `region` op

• Data kinds: region → region

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

Usage

Removal of components touching the image border. Drops all connected components of the foreground region that touch the image's outer edge back to background -- a standard preprocessing step for excluding objects cut off at the edge of the field of view (not fully captured) from analysis.

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

HALCON に直接対応するものは無い。実装は `segmentation.clear_border(binm(v))`。a, b は未使用 —— 除去判定に使う縁の幅(buffer_size)は既定の 0(画像端そのものに触れている成分のみ対象)。

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).*

sk_clear_border — 2D region op