halcon_ext op• Data kinds: image → image
• Call: fullseye.apply(img, "hx_gabor", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: convol_gabor (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):
▸ hx_gabor: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_gabor: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ hx_gabor: other inputs (docs site)
*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*
A Gabor filter (orientation theta = a*pi, frequency freq = 0.08 + 0.35b). Returns the magnitude of the response.
The orientation convention is the same as core gabor: a=0 (θ=0) responds most to vertical stripes, a=0.5 (θ=90°) to horizontal stripes.
★Normalisation (fix of 2026-09-02): a fixed scale dividing by the L1 norm of the kernel. Previously it was _norm01 (stretching that image's min-max to [0,1]), so the relative size of responses by orientation was not just flattened but the order was reversed -- measured (96×96 horizontal stripes, b=0.5): against the mean 0.34663 of the horizontal-stripe detector (a=0.5), the vertical-stripe detector (a=0), which should hardly respond, came out higher at 0.58434 (because the weaker the response, the larger the stretch factor). If |v| <= 1 then |v * g| <= sum|g|, so dividing by L1 keeps [0,1] while allowing comparison across orientations and images.
Border handling: mirror repeating the edge pixel (d c b a | a b c d — scipy's default reflect) (measured; tools/impl2/border_probe.py).
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_halcon_ext 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.
hx_gabor 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
halcon_ext)hx_gen_circle · hx_gen_ellipse · hx_gen_rectangle2 · hx_gen_checker_region · hx_gen_grid_region · hx_fit_surface1 · hx_fit_surface2 · hx_cooc_feature
*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.