• DocumentCode
    1562530
  • Title

    Zernike moment-based image registration scheme utilizing feedforward neural networks

  • Author

    Wu, Jianzhen ; Xie, Jianying

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., China
  • Volume
    5
  • fYear
    2004
  • Firstpage
    4046
  • Abstract
    A novel image registration scheme is proposed. Low order Zernike moments are used as image global pattern features and feed into feedforward neural networks to provide translation, rotation and scaling parameters. Experimental results show that the proposed registration scheme is accurate and robust to noise.
  • Keywords
    feature extraction; feedforward neural nets; image registration; Zernike moment based image registration; feedforward neural networks; image global pattern features; low order Zernike moments; rotation parameters; scaling parameters; translation parameters; Automation; Feedforward neural networks; Feeds; Image registration; Neural networks; Noise robustness; Parameter estimation; Polynomials; Registers; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
  • Print_ISBN
    0-7803-8273-0
  • Type

    conf

  • DOI
    10.1109/WCICA.2004.1342260
  • Filename
    1342260
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1562530