halcon_ext op• Data kinds: image → image
• Call: fullseye.apply(img, "hx_gen_bandfilter", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: gen_bandfilter (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.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_gen_bandfilter: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_gen_bandfilter: knob b sweep (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ hx_gen_bandfilter: 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).*
An ideal band-filter image (an annulus in frequency, centre radius a and width b). A different operator from gen_bandpass.
For the same fftshift-ed normalised frequency radius r (centre = DC) as hx_gen_lowpass, returns a 0/1 float image (frequency-domain mask) with the annulus c - half <= r <= c + half set to 1. The input v is used only to obtain the shape.
• a → centre radius of the annulus c = 0.05 + 0.4*a (0.05 to 0.45).
• b → half-width half = 0.03 + 0.15*b (0.03 to 0.18). Combinations where the inner radius c - half becomes negative (small a and
large b) give a disc containing DC, effectively a low-pass.
Whereas hx_gen_bandpass uses "inner radius and width", this one specifies the same annulus by "centre and half-width". Build a mask that extracts only a specific spatial frequency (stripe period 1/c pixels) and use it as a pixel-wise product with centre = DC spectra such as fft_generic.
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.
• 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_gen_bandfilter 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_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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.