Component-graphs are defined as the generalization of component-trees to images taking their values in partially ordered sets. Similarly to component-trees, component-graphs are a lossless image model, and can allow for the development of various image processing approaches (antiextensive filtering, segmentation by node selection). However, component-graphs are not trees, but directed acyclic graphs. This induces a structural complexity associated to a higher combinatorial cost. These properties make the handling of component-graphs a non-trivial task. We propose a preliminary discussion on a new way of building and manipulating component-graphs, with the purpose of reaching reasonable space and time costs. Tackling these complexity issues is indeed required for actually involving component-graphs in efficient image processing approaches.
CITATION STYLE
Passat, N., Naegel, B., & Kurtz, C. (2017). Implicit component-graph: A discussion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10225 LNCS, pp. 235–248). Springer Verlag. https://doi.org/10.1007/978-3-319-57240-6_19
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