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.
Corresponds to HALCON's lines_gauss(Detect lines and their width.) (approximation; it returns neither line widths nor XLD contours, only an image of the response strength). On 2026-08-30 a and b were wired up: a is the scale range (sigmas=range(1, 2+round(a*4)) — sweeps the maximum σ over 1-5; at a=0.5 it is bit-identical to the old fixed range range(1,4)), b sweeps Frangi's blobness sensitivity β over 0.15-0.85 (at b=0.5 it matches skimage's default of 0.5, so the default output does not change). Because black_ridges=True by default (it detects dark tubes on a bright background), note that the response comes out weak unless the image has black lines on a white background.
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.