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Attributed Graph Matching using Local Descriptions

Salim Jouili 1 Salvatore Tabbone 1
1 QGAR - Querying Graphics through Analysis and Recognition
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In the pattern recognition context, objects can be represented as graphs with attributed nodes and edges involving their relations. Consequently, matching attributed graphs plays an important role in objects recognition. In this paper, a node signatures extraction is combined with an optimal assignment method for matching attributed graphs. In particular, we show how local descriptions are used to define a node-to-node cost in an assignment problem using the Hungarian method. Moreover, we propose a distance formula to compute the distance between attributed graphs. The experiments demonstrate that the newly presented algorithm is well-suited to pattern recognition applications. Compared with well-known methods, our algorithm gives good results for retrieving images.
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https://hal.inria.fr/inria-00404340
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Submitted on : Thursday, July 16, 2009 - 11:18:31 AM
Last modification on : Friday, February 26, 2021 - 3:28:06 PM
Long-term archiving on: : Thursday, June 30, 2011 - 11:44:47 AM

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Salim Jouili, Salvatore Tabbone. Attributed Graph Matching using Local Descriptions. Advanced Concepts for Intelligent Vision Systems - Acivs 2009, SEE, Sep 2009, Bordeaux, France. ⟨inria-00404340⟩

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