• DocumentCode
    3448640
  • Title

    A Novel Approach to Image Enhancement and Thresholding Based on Fuzzy Theory

  • Author

    Zhen-Gang, Shi ; Li-Qun, Gao ; Kun, Wan

  • Author_Institution
    Northeastern Univ., Shenyang
  • fYear
    2007
  • fDate
    23-25 May 2007
  • Firstpage
    2201
  • Lastpage
    2205
  • Abstract
    Image processing has to deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or uncertainty. In order to apply the fuzzy theory, selecting the fuzzy region of membership function is a fundamental and important task. In this paper, a new method of membership function based on fuzzy theory by PSO algorithm optimized was proposed by analyzing the deficiencies of traditional enhancement algorithm. A new entropy definition of a fuzzy set was proposed. The new entropy definition of a fuzzy set was not only related to the membership (fuzzy domain) but also related to the probability distribution (space domain), it can respond to the variety of image input information. In addition, by quoting a novel particle swarm optimization (PSO) algorithm to find the optimization parameters for membership. We have employed the new proposed approach to perform image enhancement and thresholding and obtained satisfactory results.
  • Keywords
    entropy; fuzzy set theory; image enhancement; image segmentation; particle swarm optimisation; entropy definition; fuzzy set theory; image enhancement; image thresholding; mathematical tool; particle swarm optimization; probability distribution; Algorithm design and analysis; Entropy; Fuzzy set theory; Fuzzy sets; Image enhancement; Image processing; Optimization methods; Particle swarm optimization; Probability distribution; Uncertainty; fuzzy enhancement; fuzzy entropy; membership function; particle swarm optimization (PSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-0737-8
  • Electronic_ISBN
    978-1-4244-0737-8
  • Type

    conf

  • DOI
    10.1109/ICIEA.2007.4318801
  • Filename
    4318801