• DocumentCode
    175624
  • Title

    Rapid vehicle edge detection based on cellular neural network

  • Author

    Deshui Hao ; Luping Ji ; Long Zhou

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2014
  • fDate
    19-21 Aug. 2014
  • Firstpage
    118
  • Lastpage
    122
  • Abstract
    This paper presents a rapid edge detection method for vehicle using the two-dimensional cellular neural network (CNN). In the method, two adaptive templates for edge detection are experimentally designed, and background noise elimination is also concerned. Finally, the performance of the proposed CNN detector is evaluated on different vehicle images, and it is also compared with some other edge detectors. Simulation experiment results shows that the CNN method could achieve good performance in vehicle edge detection.
  • Keywords
    cellular neural nets; edge detection; image denoising; road vehicles; traffic engineering computing; CNN; adaptive templates; background noise elimination; rapid vehicle edge detection method; two-dimensional cellular neural network; vehicle images; Cellular neural networks; Detectors; Digital images; Image edge detection; Noise; Particle swarm optimization; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2014 10th International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4799-5150-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2014.6975820
  • Filename
    6975820