• DocumentCode
    1722003
  • Title

    Four-layer cellular neural networks in consideration of color and luminosity

  • Author

    Kato, Yoshihiro ; Ueda, Yasuhiro ; Uwate, Yoko ; Nishio, Yoshifumi

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Tokushima Univ., Tokushima, Japan
  • fYear
    2011
  • Firstpage
    845
  • Lastpage
    848
  • Abstract
    Human´s retina has the capability to identify color and luminosity. The cell identifies color is called a cone cell and identifies luminosity is called a rod cell. The color image processing using CNN was proposed by Roska et al. Additionally, Inoue et al. have used three-layer CNN based on cone cell, and performed edge enhancement. They have confirmed that edge had been detected under three-layer CNN influencing each other. However, the edge of a low luminosity portion is not detected. In this study, we propose four-layer cellular neural networks in consideration of three primary colors of light and luminosity, respectively. In this research, we show some edge detection results and confirm that the proposed CNN is effective compared with the conventional CNN and the existing CNN.
  • Keywords
    brightness; cellular neural nets; edge detection; eye; image colour analysis; image enhancement; color identification; color image processing; cone cell; edge detection; edge enhancement; four-layer cellular neural networks; luminosity identification; three-layer CNN; Color; Computer architecture; Gray-scale; Image color analysis; Image edge detection; Microprocessors; Simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuit Theory and Design (ECCTD), 2011 20th European Conference on
  • Conference_Location
    Linkoping
  • Print_ISBN
    978-1-4577-0617-2
  • Electronic_ISBN
    978-1-4577-0616-5
  • Type

    conf

  • DOI
    10.1109/ECCTD.2011.6043827
  • Filename
    6043827