Skip to main content
SpringerLink
Log in

Moving shadow detection and removal for traffic sequences

  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

Segmentation of moving objects in a video sequence is a basic task for application of computer vision. However, shadows extracted along with the objects can result in large errors in object localization and recognition. In this paper, we propose a method of moving shadow detection based on edge information, which can effectively detect the cast shadow of a moving vehicle in a traffic scene. Having confirmed shadows existing in a figure, we execute the shadow removal algorithm proposed in this paper to segment the shadow from the foreground. The shadow eliminating algorithm removes the boundary of the cast shadow and preserves object edges firstly; secondly, it reconstructs coarse object shapes based on the edge information of objects; and finally, it extracts the cast shadow by subtracting the moving object from the change detection mask and performs further processing. The proposed method has been further tested on images taken under different shadow orientations, vehicle colors and vehicle sizes, and the results have revealed that shadows can be successfully eliminated and thus good video segmentation can be obtained.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Y. Sonoda, T. Ogata. Separation of Moving Objects and Their Shadows, and Application to Tracking of Loci in the Monitoring Images. In Proceedings of 1998 Fourth International Conference on Signal Processing, Beijing, China, vol. 2, pp. 1261–1264, 1998.

    Google Scholar 

  2. K. Onoguchi. Shadow Elimination Method for Moving Object Detection. In Proceedings of Fourteenth International Conference on Pattern Recognition, Los Alamitos, California, vol. 1, pp. 583–587, 1998.

    Article  Google Scholar 

  3. G. S. K. Fung, N. H. C. Yung, G. K. H. Pang, A. H. S. Lai. Effective Moving Cast Shadows Detection for Monocular Color Image Sequences. In Proceedings of 11th International Conference on Image Analysis and Processing, Los Alamitos, California, pp. 404–409, 2001.

  4. R. Cucchiara, C. Grana, M. Piccardi, A. Prati. Detecting Objects, Shadows and Ghosts in Video Streams by Exploiting Color and Motion Information. In Proceedings of 11th International Conference on Image Analysis and Processing, Los Alamitos, California, pp. 360–365, 2001.

  5. O. Schreer, I. Feldmann, U. Goelz, P. Kauff. Fast and Robust Shadow Detection in Videoconference Applications. In Proceedings of International Symposium on Video/Image Processing and Multimedia Communications 2002, Zadar, Croatia, pp. 371–375, 2002.

  6. A. Bevilacqua, M. Roffilli. Robust Denoising and Moving Shadows Detection in Traffic Scenes. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Kauai Marriott, Hawaii, pp. 1–4, 2001.

  7. S. Nadimi, B. Bhanu. Physical Models for Moving Shadow and Object Detection in Video. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 8, pp. 1079–1087, 2004.

    Article  Google Scholar 

  8. A. Branca, G. Attolico, A. Distante. Cast Shadow Removing in Foreground Segmentation. In Proceedings of 16th International Conference on Pattern Recognition, Los Alamitos, California, pp. 214–217, 2002.

  9. J. M. Wang, Y. C. Chung, C. L. Chang, S. W. Chen. Shadow Detection and Removal for Traffic Images. In Proceedings of the 2004 IEEE International Conference on Networking, Sensing and Control, Piscataway, United States, vol. 1, pp. 649–654, 2004.

    Article  Google Scholar 

  10. Y. M. Wu, X. Q. Ye, W. K. Gu. A Shadow Handler in Traffic Monitoring System. In Proceedings of IEEE Vehiclar Technology Conference, Piscataway, NJ, vol. 1, pp. 303–307, 2002.

    Google Scholar 

  11. G. D. Finlayson, S. D. Hordley, M. S. Drew. Removing Shadows from Images Using Retinex. In Proceedings of the 10th Color Imaging Conference: Color Science, Systems, and Applications, Scottsdale, AZ, United States, pp. 73–79, 2002.

  12. K. Barnard, G. Finlayson. Shadow Identification Using Colour Ratios. In Proceedings of the 8th Color Imaging Conference: Color Science, Systems, and Applications, Scottsdale, AZ, United States, pp. 97–101, 2000.

  13. I. Mikic, P. C. Cosman, G. T. Kogut, M. M. Trivedi. Moving Shadow and Object Detection in Traffic Scenes. In Proceedings of IEEE International Conference on Pattern Recognition, Los Alamitos, California, vol. 1, pp. 321–324, 2000.

    Google Scholar 

  14. K. Onoguchi. Shadow Elimination Method for Moving Object Detection. In Proceedings of Fourteenth International Conference on Pattern Recognition, Brisbane, Australia, vol. 1, pp. 583–587, 1998.

    Article  Google Scholar 

  15. D. Xu, X. L. Li, Z. K. Liu, Y. Yuan. Cast Shadow Detection in Video Segmentation. Pattern Recognition Letters, vol. 26, no. 1, pp. 91–99, 2005.

    Article  Google Scholar 

  16. L. Wixson. Illumination Assessment for Vision-based Traffic Monitoring. In Proceedings of 13th International Conference on Pattern Recognition, Los Alamitos, California, vol. 3, pp. 56–62, 1996.

    Article  Google Scholar 

  17. L. Wixson, K. Hanna, D. Mishra. Improved Illumination Assessment for Vision-based Traffic Monitoring. In Proceedings of IEEE Workshop on Visual Sfurveillance, Los Alamitos, California, pp. 34–41, 1998.

  18. Z. Q. Hou, C. Z. Han. A Background Reconstruction Algorithm Based on Pixel Intensity Classification in Remote Video Surveillance System. In Proceedings of 7th International Conference on Information Fusion, Stockholm, Sweden, pp. 754–759, 2004.

  19. C. Kim, N. Hwang. Fast and Automatic Video Object Segmentation and Tracking for Content-based Applications. IEEE Transactions on Circuits and Systems for Video Technology, vol. 12, no. 2, pp. 122–128, 2002.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, 710049, PRC

    Mei Xiao & Chong-Zhao Han

  2. Taibai Campus, Chang’an University, Xi’an, 710064, PRC

    Lei Zhang

Authors
  1. Mei Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chong-Zhao Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mei Xiao.

Additional information

The work was supported by the National Natural Science Foundation of PRC (No. 60574033) and the National Key Fundamental Research & Development Programs (973) of PRC (No. 2001CB309403)

Mei Xiao received her B. Sc. degree from Chang’an University, China, in 2000, and the M. Sc degree from Chang’an University in 2003, China. She is currently a Ph. D. student of Xi’an Jiaotong University, China.

Her research interests include computer vision, image processing and information fusion.

Chong-Zhao Han received his B. Sc. degree in automation from Xi’an JiaoTong University, China, in 1968, and the M. Sc degree from Chinese Academy of Sciences, China, in 1981. He is currently a professor in the School of Electronic and Information Engineering at Xi’an JiaoTong University, China.

He has over 40 years of experience in industrial applications and academic research. He has published 7 books and more than 140 journal and conference papers. His research interests include stochastic system analysis, estimation theory, nonlinear analysis and information fusion.

Prof. Han is a member of board of directors in Chinese Association of Automation, and also the vice chair of Shanxi Provincial Association of Automation.

Lei Zhang received his B. Sc. degree from Chang’an University, China, in 1998, and the M. Sc degree from Chang’an University, China, in 2005. He is currently a Ph.D. student of Chang’an University, China.

His research interests include computer vision, image processing and intelligent vehicle.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xiao, M., Han, CZ. & Zhang, L. Moving shadow detection and removal for traffic sequences. Int J Automat Comput 4, 38–46 (2007). https://doi.org/10.1007/s11633-007-0038-z

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-007-0038-z

Keywords

Search

Navigation