InforLorV4, Hal, Corpus, bibRecord, 006B34

Invariant image descriptors and affine morphological scale-space

Identifieur interne : 006B34 ( Hal/Corpus ); précédent : 006B33; suivant : 006B35

Invariant image descriptors and affine morphological scale-space

Auteurs : Frédéric Sur

Source :

RBID : Hal:inria-00164802

Descripteurs français

mix :
- Interest points, affine morphological scale-space, local descriptors, scale-space representation.

Abstract

In this research report we propose a novel approach to build interest points and descriptors which are invariant to a subclass of affine transformations. Scale and rotation invariant interest points are usually obtained via the linear scale-space representation, and it has been shown that affine invariance can be achieved by warping the smoothing kernel to match the local image structure. Our approach is instead based on the so-called Affine Morphological Scale-Space, a non-linear filtering which has been proved to be the natural equivalent of the classic linear scale-space when affine invariance is required. Simple local image descriptors are then derived from the extracted interest points. We demonstrate the proposed approach by robust matching experiments.

Url:

https://hal.inria.fr/inria-00164802

Links to Exploration step

Hal:inria-00164802

Le document en format XML

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<front><div type="abstract" xml:lang="en">In this research report we propose a novel approach to build interest points and descriptors which are invariant to a subclass of affine transformations. Scale and rotation invariant interest points are usually obtained via the linear scale-space representation, and it has been shown that affine invariance can be achieved by warping the smoothing kernel to match the local image structure. Our approach is instead based on the so-called Affine Morphological Scale-Space, a non-linear filtering which has been proved to be the natural equivalent of the classic linear scale-space when affine invariance is required. Simple local image descriptors are then derived from the extracted interest points. We demonstrate the proposed approach by robust matching experiments.</div>
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<abstract xml:lang="en">In this research report we propose a novel approach to build interest points and descriptors which are invariant to a subclass of affine transformations. Scale and rotation invariant interest points are usually obtained via the linear scale-space representation, and it has been shown that affine invariance can be achieved by warping the smoothing kernel to match the local image structure. Our approach is instead based on the so-called Affine Morphological Scale-Space, a non-linear filtering which has been proved to be the natural equivalent of the classic linear scale-space when affine invariance is required. Simple local image descriptors are then derived from the extracted interest points. We demonstrate the proposed approach by robust matching experiments.</abstract>
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Invariant image descriptors and affine morphological scale-space

Invariant image descriptors and affine morphological scale-space

Source :

Descripteurs français

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri