sk_niblack — 2D `segmentation` op

• Data kinds: image → region

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

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

sk_niblack: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

Niblack's local adaptive thresholding. Like Sauvola, it determines the threshold from the local mean and standard deviation, but with a simpler (classic) way of setting the coefficients, and tends to judge the foreground more broadly than Sauvola (i.e. more prone to picking up noise).

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

HALCON の var_threshold に相当(近似)。実装は `v > filters.threshold_niblack(v, window_size=2*int(a*6)+3)` —— a は局所窓サイズを 3〜15(奇数)に振る。b は未使用。sk_sauvola と同じ入力・同じ a の振り方で並べ、結果を見比べる用途を想定。

Detailed usage guide

• gallery2d_segmentation 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.

sk_niblack 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_segmentation — py -3.11 examples/gallery2d_segmentation.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 (`segmentation`)

threshold · otsu · canny · adaptive_gauss_thresh · sk_otsu · sk_li · sk_yen · sk_sauvola

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

sk_niblack — 2D segmentation op