New algorithms for multivalued component-trees - Laboratoire d'Informatique PAris DEscartes - EA 2517
Communication Dans Un Congrès Année : 2024

New algorithms for multivalued component-trees

Résumé

Tree-based structures can model images---and more generally valued graphs---for processing and analysis purpose. In this framework, the component tree was natively designed for grey-level images---and more generally totally ordered valued graphs. Ten years ago, the notion of a multivalued component tree was introduced to relax this grey-level / total order constraint. In this algorithmic paper, we provide new tools to handle multivalued component trees. Our contributions are twofold: (1) we propose a new algorithm for the construction of the multivalued component tree; (2) we propose two strategies for building hierarchical orders on value sets, required to further build the multivalued component trees of images / graphs relying on such value sets.
Fichier principal
Vignette du fichier
Passat_ICPR_2024.pdf (177.82 Ko) Télécharger le fichier
Passat_ICPR24_Poster.pdf (209.44 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04668027 , version 1 (18-08-2024)

Identifiants

Citer

Nicolas Passat, Romain Perrin, Jimmy Francky Randrianasoa, Camille Kurtz, Benoît Naegel. New algorithms for multivalued component-trees. International Conference on Pattern Recognition (ICPR), 2024, Kolkata, India. pp.19-35, ⟨10.1007/978-3-031-78347-0_2⟩. ⟨hal-04668027⟩
267 Consultations
39 Téléchargements

Altmetric

Partager

More