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.
Original language | English (US) |
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Pages (from-to) | 277-296 |
Number of pages | 20 |
Journal | European Journal of Applied Mathematics |
Volume | 31 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2020 |
Bibliographical note
Publisher Copyright:© Cambridge University Press 2019.
Keywords
- Differential invariant
- equi-affine group
- feature detection
- moving fram