• DocumentCode
    1647796
  • Title

    Automatic design of W-operators using LVQ - application to morphological image segmentation

  • Author

    Flores, Franklin César ; Peres, Sarajane Marques ; Von Zuben, Fernando José

  • Author_Institution
    Dept. of Comput. Eng. & Ind. Autom., State Univ. of Campinas, Sao Paulo, Brazil
  • Volume
    1
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    755
  • Lastpage
    760
  • Abstract
    W-operators compose a family of translation invariant and locally defined operators. This work proposes a new approach to an automatic design of W-operators using learning vector quantization neural networks. It is also presented here some experimental results associated with the application of these operators in morphological image segmentation
  • Keywords
    image segmentation; learning (artificial intelligence); mathematical morphology; neural nets; vector quantisation; LVQ neural networks; W-operators; image segmentation; learning; learning vector quantization; morphological operators; watershed with markers; Apertures; Application software; Automation; Computer industry; Decision trees; Design optimization; Filtering; Image segmentation; Neural networks; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1005568
  • Filename
    1005568