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Autores
  • Santos, José
  • Ibáńez Panizo, Óscar
  • Barreira, Noelia
  • Penedo, Manuel G.
Categoria WoS
Area
  • Genetic Algorithms
Titulo: Genetic-Greedy Hybrid Approach for Topological Active Nets Optimization
Tipo: revista internacional
Fecha: 4,2007
Revista: LNCS. Adaptative and Natural Computing Algorithms Editorial
JCR Journal; Impact Factor: 0.402
SCIMago SJR:
Volumen: LNCS 4431
Paginas: 202-210
ISSN: 0302-9743
Editorial: Springer-Verlag
Warsaw (Poland)

Abstract:

In this paper we propose a genetic and greedy algorithm combination for the optimization of the Topological Active Nets (TAN) model. This is a deformable model used for image segmentation that integrates features of region-based and edge-based segmentation techniques, being able to fit the edges of the objects and model their inner topology. The hybrid approach we propose can optimize the active nets through the minimization of the model energy functions and, moreover, it can provide some segmentation results unreachable by the GA method alone such as changes in the net topology.

SABIA
    .: SABIA :.  Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial