halcon_ext op• Data kinds: contour → feature
• Call: fullseye.apply(img, "hx_distance_pc", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: distance_pc (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_distance_pc: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ hx_distance_pc: knob b sweep (docs site)
Stages (the ops that come before → this op, left to right):
▸ hx_distance_pc: stages (docs site)
The minimum distance from the query point (normalised a, b) to the contour (a feature).
Returns the minimum Euclidean distance from the query point q = (a*H, b*W) in normalised coordinates (a, b) to the vertices of all contours, divided by max(H, W) and capped at 1, as np.float64.
• a → row of the query point (0 to 1).
• b → column of the query point (0 to 1).
• 0.0 if the contours have no points (indistinguishable from the point lying on a contour).
The distance is to the vertices, not to the segments, so for contours with coarse point spacing it comes out larger than the true distance by up to about "half the point spacing". For fine contours (edges_sub_pix with 1-pixel steps) it almost matches. The distance to a region is hx_distance_pr, the distance from a horizontal line hx_distance_sc, and selecting the contours containing a point hx_select_xld_point.
• 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.
threshold 0.50 0.50 sk_find_contours 0.50 0.50 hx_distance_pc 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.py
feature as input)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.