New algorithms for multivalued component trees
In Proceedings of the 27th international conference on pattern recognition
Abstract
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 or- dered valued graphs. Ten years ago, the notion of a multivalued component tree was introduced to relax this grey-level / total order constraint. In this algorith- mic 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 com- ponent trees of images / graphs relying on such value sets. Codes available at: https://github.com/bnaegel/multivalued_component_tree.