Abstract
Image feature points are detected as pixels which locally maximise a detector function, two commonly used examples of which are the (Euclidean) image gradient and the Harris–Stephens corner detector. A major limitation of these feature detectors is that they are only Euclidean-invariant. In this work, we demonstrate the application of a 2D equi-affine-invariant image feature point detector based on differential invariants as derived through the equivariant method of moving frames. The fundamental equi-affine differential invariants for 3D image volumes are also computed.
Publisher
Cambridge University Press (CUP)
Cited by
3 articles.
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1. Projective invariants of images;European Journal of Applied Mathematics;2022-09-26
2. The Moving-Frame Method for the Iterated-Integrals Signature: Orthogonal Invariants;Foundations of Computational Mathematics;2022-06-01
3. Feature Matching and Heat Flow in Centro-Affine Geometry;Symmetry, Integrability and Geometry: Methods and Applications;2020-09-29