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GRADUATED ASSIGNMENT ALGORITHM FOR MULTIPLE GRAPH MATCHING BASED ON A COMMON LABELING

  • Datos identificativos

    Identificador: imarina:9245871
    Autores:
    Sole-Ribalta, AlbertSerratosa, Francesc
    Resumen:
    In pattern recognition applications, with the aim of increasing efficiency, it is useful to represent the elements by attributed graphs (which consider their structural properties). Under this structural representation of the elements some graph matching problems need a common labeling between the vertices of a set of graphs. Computing this common labeling is a NP-Complete problem. Nevertheless, some methodologies have been presented which obtain a sub-optimal solution in polynomial time. The drawback of these methods is that they rely on pairwise labeling computations, causing the methodologies not to consider the global information during the entire process. To solve this problem, we present a methodology which generates the common labeling by matching all graph nodes to a virtual node set. The method has been tested using three independent datasets, one synthetic and two real. Experimental results show that the presented method obtains better performance than the most popular common labeling algorithm with the same computational cost.
  • Otros:

    Autor según el artículo: Sole-Ribalta, Albert; Serratosa, Francesc
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Serratosa Casanelles, Francesc d'Assís / Solé Ribalta, Albert
    Palabras clave: Retrieval Relaxation Pattern-recognition Multiple graph matching Median graphs Images Graph common labeling Graduated assignment Error tolerant graph isomorphism Distance Constellations Computation Classification Attributed graphs
    Resumen: In pattern recognition applications, with the aim of increasing efficiency, it is useful to represent the elements by attributed graphs (which consider their structural properties). Under this structural representation of the elements some graph matching problems need a common labeling between the vertices of a set of graphs. Computing this common labeling is a NP-Complete problem. Nevertheless, some methodologies have been presented which obtain a sub-optimal solution in polynomial time. The drawback of these methods is that they rely on pairwise labeling computations, causing the methodologies not to consider the global information during the entire process. To solve this problem, we present a methodology which generates the common labeling by matching all graph nodes to a virtual node set. The method has been tested using three independent datasets, one synthetic and two real. Experimental results show that the presented method obtains better performance than the most popular common labeling algorithm with the same computational cost.
    Áreas temáticas: Software Engenharias iv Educação Computer vision and pattern recognition Computer science, artificial intelligence Ciência da computação Astronomia / física Artificial intelligence
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: albert.sole@urv.cat francesc.serratosa@urv.cat
    Identificador del autor: 0000-0002-2953-5338 0000-0001-6112-5913
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.worldscientific.com/doi/abs/10.1142/S0218001413500018
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: International Journal Of Pattern Recognition And Artificial Intelligence. 27 (1): 1350001-
    Referencia de l'ítem segons les normes APA: Sole-Ribalta, Albert; Serratosa, Francesc (2013). GRADUATED ASSIGNMENT ALGORITHM FOR MULTIPLE GRAPH MATCHING BASED ON A COMMON LABELING. International Journal Of Pattern Recognition And Artificial Intelligence, 27(1), 1350001-. DOI: 10.1142/S0218001413500018
    DOI del artículo: 10.1142/S0218001413500018
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2013
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Artificial Intelligence,Computer Science, Artificial Intelligence,Computer Vision and Pattern Recognition,Software
    Retrieval
    Relaxation
    Pattern-recognition
    Multiple graph matching
    Median graphs
    Images
    Graph common labeling
    Graduated assignment
    Error tolerant graph isomorphism
    Distance
    Constellations
    Computation
    Classification
    Attributed graphs
    Software
    Engenharias iv
    Educação
    Computer vision and pattern recognition
    Computer science, artificial intelligence
    Ciência da computação
    Astronomia / física
    Artificial intelligence
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