region_growing — 3D `segment` op

• Data kinds: points → labels

• Call: import fullseye as fs; fs.ledger.region_growing(points, normals=None, angle_thresh_deg: 'float' = 15.0, k: 'int' = 20, min_region_size: 'int' = 3) -> 'np.ndarray' (to call the implementation directly, import segment3d; segment3d.region_growing(points, normals=None, angle_thresh_deg: 'float' = 15.0, k: 'int' = 20, min_region_size: 'int' = 3) -> 'np.ndarray'; from the registry, ops3d.get("region_growing"))

Usage

Grow regions by normal similarity and give the connected smooth regions the same label (the variant without a curvature gate).

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

各点を k 近傍グラフ上で BFS 成長させ、隣接点 q を「法線 n_p と n_q の成す角が

`angle_thresh_deg` 未満」のときだけ同領域に加える。平面内の法線はほぼ平行なので

同一領域に連結し、向きの違う面の境界では角度が開いて連結が切れる → 面ごとに別領域。

法線は符号不定(PCA 由来)なので `|n_p·n_q|` で判定(表裏を同一視)。

Args:

points: (N,3) 点群。

normals: (N,3) 単位法線。None なら :func:pointcloud.estimate_normals で PCA 推定。

angle_thresh_deg: 隣接法線角度の許容上限[度]。(0,180) の範囲。

k: 近傍数(kNN グラフの次数)。

Returns:

labels: (N,) int。連結平滑領域ごとに 0,1,2,... を付与。**min_region_size 未満の

小領域(孤立点・向き不一致のゴミ)は -1(ノイズ/未割当)** = 統一契約(-1=ノイズ)に従う。

空入力は shape (0,) を返す。

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.

Runnable examples (verified samples that actually call this op)

• sensor_seg — py -3.11 examples_3d/sensor_seg.py

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

fuse_to_voxel · vol_region_props

Same category (`segment`)

euclidean_cluster · plane_segmentation · vol_watershed

*Provenance: segment3d.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

region_growing — 3D segment op