• DocumentCode
    2301147
  • Title

    Kernel based image registration versus MLESAC: A comparative study

  • Author

    Fuiorea, Daniela ; Gui, Vasile ; Pescaru, Dan ; Toma, Corneliu

  • Author_Institution
    Commun. Dept., Politeh. Univ. of Timisoara, Timisoara, Romania
  • fYear
    2009
  • fDate
    28-29 May 2009
  • Firstpage
    255
  • Lastpage
    260
  • Abstract
    This paper evaluates the performance of a nonparametric robust image registration method based on the mean shift algorithm, which could successfully replace the random sampling algorithms. Therefore it realizes a comparative study between the proposed nonparametric method and other two important robust random sampling methods, RANSAC and MLESAC. These techniques are analyzed and tested for performance evaluation in several image registration scenarios.
  • Keywords
    image registration; image sampling; maximum likelihood estimation; MLESAC; kernel based image registration method; maximum likelihood estimation sample consensus; mean shift algorithm; performance evaluation; random sampling method; Cost function; Image registration; Image sampling; Iterative algorithms; Kernel; Maximum likelihood estimation; Noise robustness; Parameter estimation; Probability density function; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Computational Intelligence and Informatics, 2009. SACI '09. 5th International Symposium on
  • Conference_Location
    Timisoara
  • Print_ISBN
    978-1-4244-4477-9
  • Electronic_ISBN
    978-1-4244-4478-6
  • Type

    conf

  • DOI
    10.1109/SACI.2009.5136252
  • Filename
    5136252
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2301147