• DocumentCode
    507923
  • Title

    Detection of Straight Lines Using a Spiking Neural Network Model

  • Author

    Wu, QingXiang ; McGinnity, T.M. ; Maguire, Liam ; Valderrama-Gonzalez, G.D. ; Cai, Jianyong

  • Author_Institution
    Intell. Syst. Res. Centre, Univ. of Ulster at Magee, Londonderry, UK
  • Volume
    2
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    385
  • Lastpage
    389
  • Abstract
    Receptive fields of neurons play various roles in biological neural networks. Based on a receptive field with the function of Hough transform, a spiking neural network model is proposed to detect straight lines in a visual image. Through the network, straight lines transform to corresponding neurons with high firing rates in the output neuron array. Simulation results show that straight lines can be detected by the network and firing rates of the corresponding neurons are referred to lengths of the lines. This model can be used to explain how a spiking neuron-based network can detect straight lines, and furthermore the model can be used in an artificial intelligent system.
  • Keywords
    Hough transforms; neural nets; object detection; Hough transform; artificial intelligent system; biological neural networks; spiking neural network model; spiking neuron-based network; straight line detection; visual image; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological system modeling; Circuits; Intelligent networks; Intelligent systems; Neural networks; Neurons; Visual system; Hough transform; receptive field; spiking neural networks; straight line detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.484
  • Filename
    5363996