Skip to main content

An Efficient Moving Object Extraction Algorithm for Video Surveillance

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3683))

Abstract

In this paper, an efficient moving object extraction algorithm for surveillance application is proposed which employ change detection strategy to obtain motion information of moving-object instead of complex operator. In addition, background subtraction is introduced to solve the problems of still object and uncovered background which is generally ill-inherency existed in conventional method. After that, the internal part region of moving-object may be confused with real-static region due to frame difference used. Hence, we use the concept of region adjacent graphic to overcome it. Finally, a post-processing step is used to remove noise regions and refine the shape of objects segmented. Moreover shadow effects can be suppressed in the pre-processing step. Experimental results demonstrate various results of segmented video sequence for both indoor and outdoor scenes and show that the proposed algorithm is superior to others in terms of obviating static region of internal part of moving-object and edge defects.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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.

References

  1. Sikora, T.: The MPEG-4 video standard verification model. IEEE Trans. on Circuits Syst. Video Technol. 7, 19–31 (1997)

    Article  Google Scholar 

  2. Aach, T., Kaup, A., Mester, R.: Statisticl model-based change detection in moving video. Signal Processing 31, 165–180 (1993)

    Article  MATH  Google Scholar 

  3. Pan, J., Lin, C.-W., Gu, C., Sun, M.-T.: A robust video object segmentation scheme with prestored background information. In: IEEE International Symposium on Circuits and Systems ISCAS 2002, May 26-29, vol. 3, pp. 803–806 (2002)

    Google Scholar 

  4. Jain, R., Kasturi, R., Schunck, B.G.: Machine Vision. McGraw-Hill, Reading (1995)

    Google Scholar 

  5. Caplier, A., Bonnaud, L., Chassery, J.-M.: Robust Fast Extraction of Video Object s Combining Frame Differences and Adaptive Frame Reference Image. In: IEEE International Conference on Image Processing, vol. 2, pp. 785–788 (2001)

    Google Scholar 

  6. Cavallaro, A., Ebrahimi, T.: Video object extraction based on adaptive background and statistical change detection. In: Proc. of IEEE Visual Communications and Image Processing, January 2001, pp. 465–475 (2001)

    Google Scholar 

  7. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice-Hall Inc., Englewood Cliffs (2002)

    Google Scholar 

  8. Haralick, R.M., Shapiro, L.G.: Computer and Robot Vision, pp. 28–48. Addison-Wesley, Reading (1992)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, DJ., Chen, TH., Chiou, YC., Liau, HS. (2005). An Efficient Moving Object Extraction Algorithm for Video Surveillance. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_50

Download citation

  • DOI: https://doi.org/10.1007/11553939_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28896-1

  • Online ISBN: 978-3-540-31990-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics