Generic polar harmonic transforms for invariant image representation

Abstract : This paper introduces four classes of rotation-invariant orthogonal moments by generalizing four existing moments that use harmonic functions in their radial kernels. Members of these classes share beneficial properties for image representation and pattern recognition like orthogonality and rotation-invariance. The kernel sets of these generic harmonic function-based moments are complete in the Hilbert space of square-integrable continuous complex-valued functions. Due to their resemble definition, the computation of these kernels maintains the simplicity and numerical stability of existing harmonic function-based moments. In addition, each member of one of these classes has distinctive properties that depend on the value of a parameter, making it more suitable for some particular applications. Comparison with existing orthogonal moments defined based on Jacobi polynomials and eigenfunctions has been carried out and experimental results show the effectiveness of these classes of moments in terms of representation capability and discrimination power.
Type de document :
Article dans une revue
Image and Vision Computing, Elsevier, 2014, 32 (8), pp.497 - 509. 〈10.1016/j.imavis.2014.04.016〉
Liste complète des métadonnées

Littérature citée [34 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01083722
Contributeur : Thai V. Hoang <>
Soumis le : lundi 17 novembre 2014 - 17:50:22
Dernière modification le : mardi 24 avril 2018 - 13:29:16
Document(s) archivé(s) le : mercredi 18 février 2015 - 12:35:55

Fichier

Moment_har_def_final.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Thai V. Hoang, Salvatore Tabbone. Generic polar harmonic transforms for invariant image representation. Image and Vision Computing, Elsevier, 2014, 32 (8), pp.497 - 509. 〈10.1016/j.imavis.2014.04.016〉. 〈hal-01083722〉

Partager

Métriques

Consultations de la notice

245

Téléchargements de fichiers

244