Skip to main content

A Real Time Vehicle Detection Algorithm for Vision-Based Sensors

  • Conference paper
Computer Vision and Graphics (ICCVG 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6375))

Included in the following conference series:

Abstract

A vehicle detection plays an important role in the traffic control at signalised intersections. This paper introduces a vision-based algorithm for vehicles presence recognition in detection zones. The algorithm uses linguistic variables to evaluate local attributes of an input image. The image attributes are categorised as vehicle, background or unknown features. Experimental results on complex traffic scenes show that the proposed algorithm is effective for a real-time vehicle detection.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Kim, Z., Malik, J.: Fast vehicle detection with probabilistic feature grouping and its application to vehicle tracking. In: IEEE Int. Conf. Comp. Vision, pp. 524–531 (2003)

    Google Scholar 

  2. Liu, A., Yang, Z.: Video Vehicle Detection Algorithm through Spatio-Temporal Slices Processing. In: IEEE Int. Conf. Mechatronic Embedded Systems, pp. 1–5 (2006)

    Google Scholar 

  3. Płaczek, B., Staniek, M.: Model Based Vehicle Extraction and Tracking for Road Traffic Control. In: Kurzyński, M., et al. (eds.) Computer Recognition Systems, Advances in Soft Computing, vol. 2, pp. 844–851. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Płaczek, B.: Vehicles Recognition Using Fuzzy Descriptors of Image Segments. In: Kurzyński, M., et al. (eds.) Computer Recognition Systems, Advances in Soft Computing, vol. 3, pp. 79–86. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  5. Wang, Y., Ye, G.: Joint random fields for moving vehicle detection. In: British Machine Vision Conf., vol. 1, pp. 13–22 (2008)

    Google Scholar 

  6. Xu, S., Zhao, Y., Yu, C., Shen, L.: Vehicle Detection Algorithm Based on Shadow Feature. In: IEEE Int. Colloquium ISECS, vol. 1, pp. 105–109 (2008)

    Google Scholar 

  7. Yin, M., Zhang, H., Meng, H., Wang, X.: An HMM-Based Algorithm for Vehicle Detection in Congested Traffic Situations. In: IEEE ITS Conf., pp. 736–741 (2007)

    Google Scholar 

  8. Yue, Y.: A Traffic-Flow Parameters Evaluation Approach Based on Urban Road Video. Int. J. of Intelligent Engineering and Systems 2(1), 33–39 (2009)

    Google Scholar 

  9. Zhang, G., Avery, R.P., Wang, Y.: Video-based Vehicle Detection and Classification System for Real-time Traffic Data Collection Using Uncalibrated Video Cameras. TRB Transportation Research Record, no. 1993, pp. 138–147 (2007)

    Google Scholar 

  10. Zhang, W., Wu, J., Yin, H.: Moving vehicles detection based on adaptive motion histogram. Digital Signal Processing, 1–13 (2009), doi:10.1016/j.dsp.2009.10.006

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Płaczek, B. (2010). A Real Time Vehicle Detection Algorithm for Vision-Based Sensors. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15907-7_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15907-7_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15906-0

  • Online ISBN: 978-3-642-15907-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics