hx_select_xld_point — 2D `halcon_ext` op

• Data kinds: contour → contour

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

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

hx_select_xld_point: 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.*

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

Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):

▸ hx_select_xld_point: knob b sweep (docs site)

Stages (the ops that come before → this op, left to right):

▸ hx_select_xld_point: stages (docs site)

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

▸ hx_select_xld_point: other inputs (docs site)

Usage

Keep only the contours whose bounding box contains the query point (normalised a, b) — a filter.

Keeps and returns only the contours whose axis-parallel bounding rectangle [min row, max row] × [min col, max col] contains the query point (qy, qx) = (a*H, b*W) given in normalised coordinates (a, b).

• a → row of the query point (0 to 1 mapped onto the height).

• b → column of the query point (0 to 1 mapped onto the width).

The test uses the bounding rectangle, not the inside of the contour (polygon inside/outside), so for L-shaped or ring-shaped contours a point outside the contour can still select it. If you need an exact inside/outside test, turn it into a region with contours_to_region and use hx_test_region_point. The distance to the contour nearest the point is hx_distance_pc. If nothing matches, an empty contour set.

Detailed usage guide

• gallery2d_halcon_ext family guide

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.

threshold 0.50 0.50
sk_find_contours 0.50 0.50
hx_select_xld_point 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_halcon_ext — py -3.11 examples/gallery2d_halcon_ext.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 (`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).*

hx_select_xld_point — 2D halcon_ext op