texture op• Data kinds: image → image
• Call: fullseye.apply(img, "sk_frangi", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: lines_gauss (the HALCON reference is a useful guide to its meaning and parameters)

*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.*
*The output is shown in a viridis-like pseudo-colour (dark purple = low, yellow = high) so that a field of quantities — distance, phase, orientation, depth — can be read.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ sk_frangi: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ sk_frangi: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ sk_frangi: other inputs (docs site)
*No colour (H,W,3) input is shown: this op treats the colour channel as a third spatial axis (it crosses channels). Call it per channel.*
Frangi's tubular structure detection filter (vesselness filter). Detects elongated tubular structures such as blood vessels, wrinkles, or rivers from the eigenvalue ratios of the Hessian matrix.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の lines_gauss(Detect lines and their width.)に相当(近似。線の幅や XLD 輪郭は返さず、応答強度の画像のみを返す)。2026-08-30 に a, b を配線した: a はスケール範囲(`sigmas=range(1, 2+round(a*4)) —— 最大 σ を 1〜5 に振る。a=0.5 で旧来の固定範囲 range(1,4) とビット一致)、b は Frangi の blobness 感度 β を 0.15〜0.85 に振る(b=0.5 で skimage 既定の 0.5 と一致し、既定出力は変わらない)。既定で black_ridges=True`(明るい背景上の暗い管を検出する)ため、白い背景に黒い線が乗った画像でないと応答が弱く出る点に注意。
Value comparability (measured): the output is normalised by that image's own maximum (the output maximum is always 1.0, and scaling the input leaves the output unchanged). Values therefore cannot be compared across images — a feature of the same strength takes a different value depending on what the strongest feature in that image happens to be, and in an image holding only weak features the noise is lifted to 1.0. To compare across images, rescale by a common reference.
Blank frame (measured): feeding an image of uniform brightness gives an empty result — every pixel is background (0) — regardless of the brightness. Pure white and pure black behave alike; brightness by itself detects nothing.
• gallery2d_texture_freq family guide
• 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.
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_frangi 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
• poc_fresco_craquelure — py -3.11 examples/poc_fresco_craquelure.py
• poc_solar_el_inspection — py -3.11 examples/poc_solar_el_inspection.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
texture)std_filter · local_bimodality · local_std · scale_select_std · bootstrap_std_error · structure_tensor_orientation · structure_tensor_coherence · gabor
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.