sp_critical_points_sub_pix — 2D subpix op

• Data kinds: image → contour

• Call: fullseye.apply(img, "sp_critical_points_sub_pix", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: critical_points_sub_pix (the HALCON reference is a useful guide to its meaning and parameters)

sp_critical_points_sub_pix: input → output

*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):

▸ sp_critical_points_sub_pix: knob a sweep (docs site)

*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ sp_critical_points_sub_pix: 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).*

Usage

Detects the sub-pixel positions of maxima, minima, and saddle points together (equivalent to HALCON critical_points_sub_pix).

Runs sp_local_max_sub_pix / sp_local_min_sub_pix / sp_saddle_points_sub_pix with the same threshold a (3 ops) and concatenates the detected points into 1 CONTOUR in the order maxima → minima → saddle points. b is unused. Returned coordinates are in pixels of the input image (sub-pixel fractional values). Use it when you only want to know "where the critical points are" without distinguishing the individual kinds.

Detailed usage guide

• gallery2d_geometry family guide

Background guides (the physics and conventions behind this op)

• measurement_uncertainty — Measurement uncertainty and calibration — what it takes to claim you are measuring

References (sample data, literature)

• 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.

Try it in Studio

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.

sp_critical_points_sub_pix 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_geometry — py -3.11 examples/gallery2d_geometry.py

Ops the type connects to (they accept contour as input)

identity · select_contours · smooth_contours · fit_line_contours · contours_to_region · count_contours · total_length · select_contours_xld

Same category (subpix)

sp_local_max_sub_pix · sp_local_min_sub_pix · sp_saddle_points_sub_pix · sp_plateaus · sp_lowlands_center


*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.