• DocumentCode
    2963620
  • Title

    A hierarchical genetic algorithm based approach for image segmentation

  • Author

    Lai, Chih-Chin ; Chang, Chuan-Yu

  • Author_Institution
    Dept. of Inf. Manage., Shu-Te Univ., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    1284
  • Abstract
    Image segmentation denotes a process by which an image is partitioned into non-intersecting regions and each region is homogeneous. Many approaches have been proposed for the monochrome image segmentation. Among these approaches, the clustering methods have been extensively investigated and used. In this paper, a clustering based approach using hierarchical genetic algorithm is proposed to tackle the problem of image segmentation. The main advantage of the proposed approach is that it can simultaneously estimate a proper number of regions and then partition the image into several homogeneous regions. The simulation results indicate that the proposed approach can produce more continuous and smoother images in comparison with two existing methods.
  • Keywords
    genetic algorithms; image segmentation; clustering methods; hierarchical genetic algorithm; image segmentation; Biological cells; Clustering methods; Genetic algorithms; Image processing; Image segmentation; Information management; Noise reduction; Pixel; Robustness; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2004 IEEE International Conference on
  • ISSN
    1810-7869
  • Print_ISBN
    0-7803-8193-9
  • Type

    conf

  • DOI
    10.1109/ICNSC.2004.1297132
  • Filename
    1297132