Equi-affine differential invariants for invariant feature point detection†

Stanley L. Tuznik, Peter J. Olver, Allen Tannenbaum

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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 languageEnglish (US)
Pages (from-to)277-296
Number of pages20
JournalEuropean Journal of Applied Mathematics
Volume31
Issue number2
DOIs
StatePublished - Apr 2020

Bibliographical note

Publisher Copyright:
© Cambridge University Press 2019.

Keywords

  • Differential invariant
  • equi-affine group
  • feature detection
  • moving fram

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