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A Robust Fusion Method for Vehicle Detection in Road Traffic Surveillance

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6216))

Abstract

Vehicle detection is an essential task in the intelligent transportation system, which will affects the performance of surveillance directly. This paper presents an approach to detect vehicle from a sequence of traffic images obtained from expressway scenes. Firstly, inter-frame difference method was used to choose some frames with small traffic flow, and then pixels detected as background are being used to initialize background by calculating average value. Secondly, the vehicle is detected by fusing inter-frame difference, background subtraction and edge-based background subtraction methods together. Finally, the vehicle region can be obtained by implementing morphological processing. Meanwhile, the pixels detected as background were being used to update the background. The experimental results from highway scenes show that the algorithm is effective.

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References

  1. Ali, A.T., Dagless, E.L.: Alternative practical methods for moving object detection. In: International Conference on Image Processing and its Applications, pp. 77–80. IEEE Press, Maastricht (1992)

    Google Scholar 

  2. Lei, X., Guangxi, Z., Yuqi, W., Haixiang, X., Zhenming, Z.: Robust vehicles extraction in a video-based intelligent transportation system. In: IEEE 2005 International Conference on Communications, Circuits and Systems, vol. 2, pp. 887–890. IEEE, Hong Kong (2005)

    Google Scholar 

  3. Javed, O., Shah, M.: Tracking and object classification for automated surveillance. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 343–357. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  4. Baisheng, C., Yunqi, L., Wangwei, L.: A Novel Background Model for Real-time Vehicle Detection. In: 7th IEEE International Conference on Signal Processing, pp. 1276–1279. IEEE, Istanbul (2004)

    Google Scholar 

  5. Hao, C., Quanlin, C., Kan, W.: A new algorithm for extracting object from traffic images. J. Computer Applications and Software 21(4), 74–75 (2004)

    Google Scholar 

  6. Meyer, D., Denzler, J., Niemann, H.: Model based extraction of articulated objects in image sequences for gait analysis. In: Proceeding of the IEEE International Conference on Image Processing, vol. 3, pp. 78–81. IEEE, Santa Barbara (1998)

    Google Scholar 

  7. Odobez, J.M., Bouthemy, P.: Robust Multiresolution Estimation of Parametric Motion Models. J. Visual Comm. and Image Representation 6, 348–365 (1995)

    Article  Google Scholar 

  8. Rosin, P.: Thresholding for change detection. In: 6th IEEE international conference on Computer Vision, pp. 274–279. IEEE, Bombay (1998)

    Google Scholar 

  9. Gupte, S.: Detection and classification of vehicle. In: IEEE Intelligent Transport System, pp. 37–47. IEEE, Singapore (2002)

    Google Scholar 

  10. Bertozzi, M., Broggi, A., Castelluccio, S.: A real-time oriented system for vehicle detection. J. Syst. Arch. 43, 317–352 (1998)

    Article  Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Hu, Q., Li, S., He, K., Lin, H. (2010). A Robust Fusion Method for Vehicle Detection in Road Traffic Surveillance. In: Huang, DS., Zhang, X., Reyes García, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_23

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  • DOI: https://doi.org/10.1007/978-3-642-14932-0_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14931-3

  • Online ISBN: 978-3-642-14932-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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