hx_split_skeleton_region — 2D `halcon_ext` op

• Data kinds: region → region

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

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

hx_split_skeleton_region: input → output

*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*

*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

Stages (the ops that come before → this op, left to right):

▸ hx_split_skeleton_region: stages (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ hx_split_skeleton_region: other inputs (docs site)

Usage

Split a one-pixel-wide skeleton at its branch points: remove the junctions (>=3 neighbours) and take the connected components.

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

`v > 0.5 の骨格画素ごとに 8 近傍の骨格画素数 nb を数え、nb >= 3` の画素(分岐点)を取り除いた

0/1 の float 配列を返す。分岐点を抜くことで骨格が枝ごとの連結成分に分かれる。

• `a, b` は未使用。

前提は 1 画素幅の骨格(`skeleton の出力)。太い線や塊を渡すと内部の画素はすべて nb >= 3` となり

ほぼ全部が消える。分岐点そのものは出力に含まれない(分岐の位置が要るなら `junctions_skeleton`)。

分かれた枝を個別に扱うには後段で `hx_region_to_label` を掛ける。分岐点の隣接画素は除かないので、

多方向が集まる太めの交差では 1 画素の残骸がつながったまま残ることがある。同系の op に `r2_split_skeleton_lines`。

Border handling: treat everything outside the image as background (0) (measured; tools/impl2/border_probe.py).

Detailed usage guide

• gallery2d_halcon_ext 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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

threshold 0.50 0.50
hx_split_skeleton_region 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py

• poc_fresco_craquelure — py -3.11 examples/poc_fresco_craquelure.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 (`halcon_ext`)

hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_gabor · hx_fit_surface1 · hx_fit_surface2

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

hx_split_skeleton_region — 2D halcon_ext op