• DocumentCode
    3582855
  • Title

    Image segmentation based on PCNN model

  • Author

    Zhongyu Tao ; Xiaolong Tang ; Binyu Zhang ; Panshi Tang ; Yue Tan

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of Electron. & Technol. of China, Chengdu, China
  • fYear
    2014
  • Firstpage
    230
  • Lastpage
    233
  • Abstract
    Image segmentation is very important in image processing which can segment the images into the different parts, thus, we can focus on the parts in which we are interested. Recent years, there are many models using for the image segmentation, Pulse Coupled Neural Networks model is very popular model which is widely used among many models. Although, PCNN models needs trivial adaptive parameters and network iterations to set, but it has the advantages, such as rotation invariance, intensity invariance, scale invariance, etc. Above advantages make PCNN is very suitable for image segmentation.
  • Keywords
    image segmentation; neural nets; PCNN model; adaptive parameters; image processing; image segmentation; network iterations; pulse coupled neural network; Brain modeling; Equations; Firing; Image segmentation; Joining processes; Mathematical model; Neurons; Image segmentation; PCNN; adaptive parameters; iteration numbers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
  • Print_ISBN
    978-1-4799-7207-4
  • Type

    conf

  • DOI
    10.1109/ICCWAMTIP.2014.7073397
  • Filename
    7073397