Abstract
In this paper we introduce affine invariants based on a multiscale framework combined with nonlinear comparison operations. The resulting descriptors are histograms, which are computed from a set of comparison results using binary coding. The new constructions are analogous to other multiscale affine invariants, but the use of highly nonlinear operations yields clear advantages in discriminability. This is also demonstrated by the experiments, where comparable recognition rates are achieved with only a fraction of the computational load. The new methods are straightforward to implement and fast to evaluate from given image patches.
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Rahtu, E., Salo, M., Heikkilä, J. (2007). Nonlinear Functionals in the Construction of Multiscale Affine Invariants. In: Ersbøll, B.K., Pedersen, K.S. (eds) Image Analysis. SCIA 2007. Lecture Notes in Computer Science, vol 4522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73040-8_49
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DOI: https://doi.org/10.1007/978-3-540-73040-8_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73039-2
Online ISBN: 978-3-540-73040-8
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