tb_mean_curvature — 2D `typed` op

• Data kinds: points → signal

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

*No figure: this op takes points as input. A Studio program starting from an image cannot reach that type — see the runnable examples below for how it is used.*

Usage

Mean curvature H=(k1+k2)/2. → (N,). An orientation-dependent quantity.

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

normals(向き付き参照法線, (N,3))未指定時は凸側ヒューリスティクス(開面の凹/凸符号は不定)。

向き付き法線を渡すと大域向きに整合し正しい符号を出す。

2-D 進化レジストリへ橋渡しした 3d の op `mean_curvature。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。a が k(既定 25)を振る。b` は未使用。

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)

• (none yet)

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

identity · tb_create_funct_1d_array · tb_smooth_funct_1d_gauss · tb_smooth_funct_1d_mean · tb_derivate_funct_1d · tb_integrate_funct_1d · tb_zero_crossings_funct_1d · tb_abs_funct_1d

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

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

tb_mean_curvature — 2D typed op