• DocumentCode
    457242
  • Title

    Approximation of Digital Curves using a Multi-Objective Genetic Algorithm

  • Author

    Locteau, Hervé ; Raveaux, Romain ; Adam, Sébastien ; Lecourtier, Yves ; Héroux, Pierre ; Trupin, Eric

  • Author_Institution
    LITIS Labs., Rouen Univ.
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    716
  • Lastpage
    719
  • Abstract
    In this paper, a digital planar curve approximation method based on a multi-objective genetic algorithm is proposed. In this method, the optimization/exploration algorithm locates breakpoints on the digital curve by minimizing simultaneously the number of breakpoints and the approximation error. Using such an approach, the algorithm proposes a set of solutions at its end. The user may choose his own solution according to its objective. The proposed approach is evaluated on curves issued from the literature and compared successfully with many classical approaches
  • Keywords
    approximation theory; computational geometry; curve fitting; genetic algorithms; digital curves approximation; digital planar curve approximation; exploration algorithm; multiobjective genetic algorithm; optimization algorithm; Approximation algorithms; Approximation error; Approximation methods; Extremities; Genetic algorithms; Image processing; Optimization methods; Pattern recognition; Shape; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.276
  • Filename
    1699305