• DocumentCode
    2577150
  • Title

    Matching Images Using Invariant Level-line Primitives under Projective Transformation

  • Author

    Almehio, Yasser ; Bouchafa, Samia

  • Author_Institution
    Inst. d´´Electron. Fondamentale, Univ. Paris-Sud XI, Orsay, France
  • fYear
    2010
  • fDate
    May 31 2010-June 2 2010
  • Firstpage
    130
  • Lastpage
    135
  • Abstract
    This paper deals with a new registration method based on a specific level-line grouping. Because of its contrast-change invariance, our approach is an appropriate method for matching outdoor image sequences. Moreover, it does not require any estimation of the unknown transformation between images and handle well the critical cases that usually lead to pairing ambiguities, such as repetitive patterns in the images. This study focuses on invariants primitive construction under projective transformation, using level-lines. The registration by itself is performed through an efficient level-line cumulative matching based on a multi-stage primitive election procedure. Each stage provides a coarse estimate of the transformation that the next stage gets to refine. Experiments on real outdoor road scene show the accuracy and efficiency of this approach, using several image sequences covering different pertaining cases with different type of motion.
  • Keywords
    image matching; image registration; image sequences; contrast-change invariance; image matching; invariant level-line primitives; level-line cumulative matching; multistage primitive election procedure; outdoor image sequences; projective transformation; registration method; Computer vision; Image sequences; Layout; Level set; Motion control; Nominations and elections; Roads; Robot vision systems; Robust control; Voting; Image Registration; Level-lines; Motion analysis; Projective Transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Robot Vision (CRV), 2010 Canadian Conference on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4244-6963-5
  • Type

    conf

  • DOI
    10.1109/CRV.2010.24
  • Filename
    5479478