• DocumentCode
    2658248
  • Title

    Feature grouping and figure/ground discrimination: a recursive neural network approach

  • Author

    Hérault, Laurent ; Horaud, Radu

  • Author_Institution
    CEA-LETI, Grenoble, France
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    2606
  • Abstract
    The authors cast the feature grouping and figure/ground discrimination problems into a combinatorial optimization problem. The cost function for which a global minimum is to be sought is of the same mathematical structure as the energy function of a spin-glass system or of a recursive neural network. Hence, the global minimization problem can be solved by mean field annealing (MFA). The experimental results obtained with an MFA asynchronous implementation show that the method advocated is well suited to solve the problem
  • Keywords
    combinatorial mathematics; neural nets; optimisation; pattern recognition; picture processing; asynchronous implementation; combinatorial optimization; cost function; energy function; feature grouping; figure/ground discrimination; global minimum; mean field annealing; recursive neural network approach; spin-glass system; Computational modeling; Computer networks; Computer vision; Cost function; Image edge detection; Neural networks; Noise shaping; Psychology; Shape; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170782
  • Filename
    170782