• DocumentCode
    179081
  • Title

    An Improved Algorithm of the Maximum Entropy Image Segmentation

  • Author

    Yan He ; Liu Jie ; Yang Dehong ; Wang Pu

  • Author_Institution
    Coll. of Comput. Sci., Chongqing Univ. of Technol., Chongqing, China
  • fYear
    2014
  • fDate
    15-16 June 2014
  • Firstpage
    157
  • Lastpage
    160
  • Abstract
    For improving the accuracy of the traditional maximum entropy threshold segmentation algorithm, an improved maximum entropy segmentation algorithm is proposed. Firstly, it determines the possible range of an optimal segmentation threshold according to a simple statistical method, so as to reduce the interference of the background and magnify the proportion of the target region. Secondly, in a certain range of threshold, does image segmentation according to an optimal segmentation threshold, which is obtained by using maximum entropy principle. Simulation experiments show that the improved algorithm not only can improve accuracy and noise immunity effectively, but also can better keep the details of the target region in comparison with the traditional maximum entropy threshold segmentation algorithm.
  • Keywords
    image segmentation; maximum entropy methods; statistical analysis; accuracy improvement; background interference reduction; improved maximum entropy segmentation algorithm; maximum entropy image segmentation; maximum entropy principle; maximum entropy threshold segmentation algorithm; noise immunity; optimal segmentation threshold; statistical method; Accuracy; Algorithm design and analysis; Entropy; Image edge detection; Image segmentation; Interference; Noise; Image Segmentation; Arithmetic Mean; Binarization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
  • Conference_Location
    Hunan
  • Print_ISBN
    978-1-4799-4262-6
  • Type

    conf

  • DOI
    10.1109/ISDEA.2014.255
  • Filename
    6977568