New algorithms for multivalued component-trees - Laboratoire de Recherche en Nanosciences - EA 4682
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.
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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.1-17, ⟨10.1007/978-3-031-78347-0_2⟩. ⟨hal-04668027⟩
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