descriptor_distance — SHAPE2D `descriptor` op

• Data kinds: efdmodel × efdmodel → measurement

• Call: import fullseye as fs; fs.ledger.descriptor_distance(m1, m2, n_harmonics=None, scale_invariant=True) (to call the implementation directly, import fourierdesc; fourierdesc.descriptor_distance(m1, m2, n_harmonics=None, scale_invariant=True); from the registry, opsshape2d.get("descriptor_distance"))

Usage

Distance between 2 shapes (smaller means more similar). Invariant to rotation/translation/starting point/(optionally) scale.

L2 distance of the (major axis, minor axis) singular-value invariants of each harmonic's ellipse (invariants). m1, m2 are output dicts of elliptic_fourier.

Detailed usage guide

• shape_description_2d 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.

Runnable examples (verified samples that actually call this op)

• contour_fourier — py -3.11 examples/contour_fourier.py

• shape2d_morph_descriptor_tour — py -3.11 examples/shape2d_morph_descriptor_tour.py

Ops the type connects to (they accept `measurement` as input)

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Same category (`descriptor`)

elliptic_fourier · reconstruct · invariants · normalize · fourier_smooth · from_xld · contour_fourier_complex · contour_epicycle_chain

*Provenance: fourierdesc.py — SHAPE2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

descriptor_distance — SHAPE2D descriptor op