• DocumentCode
    3336133
  • Title

    Genetic Algorithm for distorted point set matching

  • Author

    Jinwei Xu ; Jiankun Hu ; Xiuping Jia

  • Author_Institution
    Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
  • Volume
    03
  • fYear
    2013
  • fDate
    16-18 Dec. 2013
  • Firstpage
    1724
  • Lastpage
    1729
  • Abstract
    For image registration, point matching is still a fundamental problem because of the complex distortion such as transformation, missing and irrelevant points involved in two point sets detected from images. In this paper, a new method based on Genetic Algorithm (GA) is proposed to find the optimal affine transformation between two different point sets. In order to deal with the influence of the missing and spurious points, we define a fitness function in the combination of global topology of point set and individual point property. The experimental results on randomly generated 2D point sets demonstrate that the proposed GA-based point matching algorithm can achieve good performance in terms of correct matching (CM), false matching (FM), and missing matching (MM).
  • Keywords
    genetic algorithms; image matching; image registration; CM; FM; GA-based point matching algorithm; MM; complex distortion; correct matching; distorted point set matching; false matching; fitness function; genetic algorithm; global topology; image registration; individual point property; missing matching; optimal affine transformation; point set; Biological cells; Feature extraction; Frequency modulation; Genetic algorithms; Image registration; Measurement; Robustness; genetic algorithm; image registration; point matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2013 6th International Congress on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-2763-0
  • Type

    conf

  • DOI
    10.1109/CISP.2013.6743954
  • Filename
    6743954