• DocumentCode
    501414
  • Title

    Vehicle Types Recognition Based on Neural Network

  • Author

    Zhang, Xin-Bo ; Jiang, Li

  • Author_Institution
    Coll. of Inf. & Electron. Eng., ZheJiang Gongshang Univ., Hangzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    3
  • Lastpage
    6
  • Abstract
    As a key technology of intelligent transportation system, higher identification accuracy, robustness and real-time are needed in vehicle recognition. Therefore, in view of the features of vehicle types, this paper proposes a BP neural network car types classifier method based on fuzzy C-means clustering. First, on the basis of the pretreatment of the images of the vehicle, we abstract the features of car types from images and classify the massive data by fuzzy C- means clustering algorithm. Then, design the BP neural networks to train and test the classified data. Finally it is carried on compressive judgment by the computer. Experiments prove the validity of the classifier. It can recognize the highway vehicle types rapidly.
  • Keywords
    backpropagation; image recognition; traffic engineering computing; vehicles; BP neural network; fuzzy C-means clustering; intelligent transportation system; vehicle types recognition; Clustering algorithms; Fuzzy neural networks; Image coding; Intelligent transportation systems; Intelligent vehicles; Neural networks; Real time systems; Road transportation; Robustness; Testing; BP algorithm; character abstraction; fuzzy c-means clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.146
  • Filename
    5231735