Abstract
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.
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References
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)
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)
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)
Tang, K.W., Kak, S.: A new corner classification approach to neural network training. Circuits Systems and Signal Processing 17(3), 459–469 (1998)
Zhou, H.X.: Application of neural network in automatic recognition of vehicle style. Microcomputer Applications 24(3), 161–164 (2003)
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)
Liu, S.F., Liu, Y.B.: Research of Vehicle Type Recognition Technology. Computer and Digital Engineering 33(1), 71–76 (2005)
Zhang, Y.X., Fan, D.Q., et al.: Study on Automatic Vehicle Recognition System. Traffic and Transport 33(1), 45–48 (2006)
Shen, Q., Wang, T.: A Learning Algorithms for Optimizing RBF Neural Network Structure. Microelectronics and Computer 23(4), 14–18 (2000)
Feisi R&D centre of technological product. Neural network theory and MATLAB 7 realization. The electronic industry publishing house, Beijing (2005)
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Zhu, Z., Guo, Y. (2012). Vehicle Style Recognition Based on Image Processing and Neural Network. In: Jin, D., Lin, S. (eds) Advances in Computer Science and Information Engineering. Advances in Intelligent and Soft Computing, vol 169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30223-7_1
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DOI: https://doi.org/10.1007/978-3-642-30223-7_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30222-0
Online ISBN: 978-3-642-30223-7
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