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On Graphs with Unique Node Labelsnumber of matching algorithms for graphs with unique node labels are developed. It is shown that problems such as graph isomorphism, subgraph isomorphism, maximum common subgraph and others have a computational complexity that is only quadratic in the number of nodes. We also discuss some potential

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Functional Modeling of Structured Imagesesent, code, and analyze many problems in computer vision. By explicitly modeling functional dependences by a hypergraph, we obtain a structure well-adapted to information retrieval and processing. Thanks to the functional dependences, we show how all the variables involved in a functional graphical

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Self-Organizing Graph Edit Distancee a system of self-organizing maps representing attribute distance spaces that encode edit operation costs. The self-organizing maps are iteratively adapted to minimize the edit distance of those graphs that are required to be similar. To demonstrate the learning effect, the distance model is applie

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Anthem

Orthonormal Kernel Kronecker Product Graph MdatchingM) algorithm is based on the recently introduced Kronecker Product Graph Matching (KPGM) formulation. However, unlike previous algorithms based on the KPGM formulation which avoided explicit compatibility calculations, the OKKPGM algorithm obtains an estimate to the Kronecker Match Matrix (KMM) usin

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Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filteringimilar prototype in the database. Graph matching is a powerful yet computationally expensive procedure. If the sample graph is matched against a large database of model graphs, the size of the database is introduced as an additional factor into the overall complexity of the matching process. Databas