• DocumentCode
    3542212
  • Title

    Genetic Algorithms: A tool for image segmentation

  • Author

    Sheta, Alaa ; Braik, Malik S. ; Aljahdali, Sultan

  • Author_Institution
    Comput. Sci. Dept., WISE Univ., Amman, Jordan
  • fYear
    2012
  • fDate
    10-12 May 2012
  • Firstpage
    84
  • Lastpage
    90
  • Abstract
    Genetic Algorithms (GAs) are increasingly being explored in many areas of image analysis to solve complex optimization problems. They rapidly gained acceptance in the scientific community as powerful statistical search method which allows us to consider the segmentation problem as an optimization problem. In this paper, we propose the use of GAs in an integrated manner with traditional image segmentation techniques to provide an efficient segmentation and edges detection for selected natural images. The developed experimental results are compared with the results of other known existing segmentation algorithms such as K-mean clustering, and global threshold methods. The proposed method is capable of achieving a satisfactory results. Accordingly, the GAs based image segmentation method will definitely help in solving various complex image processing tasks.
  • Keywords
    edge detection; genetic algorithms; image segmentation; natural scenes; pattern clustering; search problems; statistical analysis; K-mean clustering; complex optimization problem; edges detection; genetic algorithm; global threshold method; image analysis; image segmentation; natural image; statistical search method; Image edge detection; Image segmentation; Marine animals; Sociology; Statistics; edge detection; genetic algorithms; image segmentation; optimization; thresholding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Computing and Systems (ICMCS), 2012 International Conference on
  • Conference_Location
    Tangier
  • Print_ISBN
    978-1-4673-1518-0
  • Type

    conf

  • DOI
    10.1109/ICMCS.2012.6320144
  • Filename
    6320144