• DocumentCode
    507329
  • Title

    A Threshold Segmentation Method for Sparse Histogram Image

  • Author

    Zhang, Hong ; Fan, Jiulun

  • Author_Institution
    Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
  • Volume
    5
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    340
  • Lastpage
    344
  • Abstract
    Maximum entropy thresholding method is a common image segmentation technology, several optimization algorithms are proposed based on maximum entropy objective function, these algorithms use subtraction instead of logarithm and multiplication and which are used in image segmentation. But for sparse histogram images, the segmentation based on the existing optimize methods is ineffective. In this paper, for sparse histogram image segmentation, an improved maximum entropy optimization algorithm is presented. Sparse histogram image segmentation experimental results show that more reasonable segmentation results can be obtained through using the algorithm.
  • Keywords
    image segmentation; maximum entropy methods; optimisation; common image segmentation technology; maximum entropy objective function; optimization algorithms; sparse histogram image; threshold segmentation method; Computational complexity; Control systems; Entropy; Fuzzy systems; Histograms; Image segmentation; Knowledge engineering; Optimization methods; Telecommunication computing; Telecommunication control; algorithm; image segmentation; maximum entropy; optimization; sparse histogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.557
  • Filename
    5360602