On a relation between graph edit distance and maximum common subgraph
Pattern Recognition Letters
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Computer Vision and Image Understanding
Topological model for 3D image representation: Definition and incremental extraction algorithm
Computer Vision and Image Understanding
A Polynomial Algorithm for Submap Isomorphism
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
From maximum common submaps to edit distances of generalized maps
Pattern Recognition Letters
A distance measure between labeled combinatorial maps
Computer Vision and Image Understanding
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Generalized maps are widely used to model the topology of nD objects (such as images) by means of incidence and adjacency relationships between cells (vertices, edges, faces, volumes, ...). In this paper, we define a first error-tolerant distance measure for comparing generalized maps, which is an important issue for image processing and analysis. This distance measure is defined by means of the size of a largest common submap, in a similar way as a graph distance measure may be defined by means of the size of a largest common subgraph. We show that this distance measure is a metric, and we introduce a greedy randomized algorithm which allows us to efficiently compute an upper bound of it.