• DocumentCode
    3003298
  • Title

    Two-Dimensional Arimoto Entropy Image Thresholding based on Ellipsoid Region Search Strategy

  • Author

    Liu, Yaoyong ; Li, Shuguang

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a novel image thresholding based on Two-Dimensional Arimoto Entropy (TDAE), called Ellipsoid Region Search Strategy (ERSS), is proposed. The basic idea is to search the optimal threshold from the reference point obtained by one-dimensional OTSU algorithm. Different from existing approaches, our approach provides a scheme to reduce the number of samples through the existing relatively easy and efficient algorithm. Additionally, this approach improves the performance of image segmentation. The experimental results on image segmentation demonstrate that our method is not only significantly more efficient but also accelerates the computation speed of two-dimensional Arimoto entropic thresholding algorithms.
  • Keywords
    entropy; image segmentation; query formulation; ellipsoid region search strategy; image segmentation; one dimensional OTSU algorithm; optimal threshold; reference point; two dimensional Arimoto entropy image thresholding; Algorithm design and analysis; Artificial neural networks; Entropy; Histograms; Image segmentation; Pattern recognition; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Technology (ICMT), 2010 International Conference on
  • Conference_Location
    Ningbo
  • Print_ISBN
    978-1-4244-7871-2
  • Type

    conf

  • DOI
    10.1109/ICMULT.2010.5631047
  • Filename
    5631047