Vehicle Style Recognition Based on Image Processing and Neural Network

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 169)


A vehicle style recognition method using computer vision, image processing and RBF neural network is presented in the paper. First, a vehicle side image is acquired by using a high-speed vidicon. Then a vehicle edge outline image was obtained by a series of image processing and the vehicle features are extracted from the edge outline image. Finally, the vehicle is recognized and classified using a RBF neural network. Experimental results show that the proposed method has a good classification effect in the practical application of vehicle style recognition at vehicle toll stations.


vehicle style recognition feature extraction image processing RBF neural network 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Petrovic, V.S., Cootes, T.F.: Vehicle type recognition with match refinement. In: Proceedings of the 17th International Conference on Pattern Recognition, UK, pp. 956–961 (2004)Google Scholar
  2. 2.
    Zheng, M.X., Gotoh, T., Shiohara, M.: A hierarchical algorithm for vehicle model type recognition on time-sequence road images. In: Proceedings of the IEEE ITSC 2006, Canada, pp. 542–547 (2006)Google Scholar
  3. 3.
    Gupte, S., Masoud, O., Martin, R.F.K., Papanikolopoulos, N.P.: Detection and classification of vehicles. IEEE Trans. Intell. Transport Syst. 3(1), 37–47 (2002)CrossRefGoogle Scholar
  4. 4.
    Tang, K.W., Kak, S.: A new corner classification approach to neural network training. Circuits Systems and Signal Processing 17(3), 459–469 (1998)MATHCrossRefGoogle Scholar
  5. 5.
    Zhou, H.X.: Application of neural network in automatic recognition of vehicle style. Microcomputer Applications 24(3), 161–164 (2003)Google Scholar
  6. 6.
    Zhang, X.J., Feng, H.W.: Automatic vehicle classification based on radial basis function neural network. Science Journal of Northwest University Online 4(2), 1–7 (2006)Google Scholar
  7. 7.
    Liu, S.F., Liu, Y.B.: Research of Vehicle Type Recognition Technology. Computer and Digital Engineering 33(1), 71–76 (2005)MATHGoogle Scholar
  8. 8.
    Zhang, Y.X., Fan, D.Q., et al.: Study on Automatic Vehicle Recognition System. Traffic and Transport 33(1), 45–48 (2006)Google Scholar
  9. 9.
    Shen, Q., Wang, T.: A Learning Algorithms for Optimizing RBF Neural Network Structure. Microelectronics and Computer 23(4), 14–18 (2000)Google Scholar
  10. 10.
    Feisi R&D centre of technological product. Neural network theory and MATLAB 7 realization. The electronic industry publishing house, Beijing (2005)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.College of Information EngineeringSouthwest University of Science and TechnologyMianyangChina

Personalised recommendations