Abstract
Different from conventional sensor networks, video sensor networks are distinctly characterized by their immense information and directional sensing models. In this paper, we propose an innovative, systematic method for image processing in video sensor networks in order to reduce the workload for individual sensors. Given the severe resource constraints on individual sensor nodes, our approach is to employ the redundancy among sensor nodes by partitioning the sensing task among highly correlated sensors. For an object of interest, each sensor only needs to capture and deliver a fraction of the scene of interests and these partial images can be fused at the sink to reconstruct a composite image. In particular, we detail how the sensing task can be partitioned among the sensors and propose an image fusion algorithms based on epipolar line constraint to fuse the received partial images at the sink. The experimental results show that our approach can achieve satisfactory results and we give detailed discussions on the effects of different system parameters.
This work reported in this paper is supported by the NSFC under Grant 60242002, and the NCET program of MOE, China.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Computer Networks 38, 393–422 (2002)
Vieira, M., Coelho, C.: Survey on wireless sensor network devices. In: Proceedings IEEE ETFA 2003, September 2003, vol. 1, pp. 16–19 (2003)
Le Moigne, J., Cole-Rhodes, A., Eastman, R., El Ghazawi, T., Johnson, K.: Multiple sensor image registration, image fusion and dimension reduction of earth science imagery. In: Proceedings of the Fifth International Conference on Information Fusion, July 2002, vol. 2, pp. 8–11 (2002)
Gao, Y., Wu, K., Li, F.: Analysis on the redundancy of wireless sensor networks. In: Proceedings of ACM WSNA 2003, San Diego, September 2003, pp. 108–114 (2003)
Chandramohan, V., Christensen, K.: A first look at wired sensor networks for video surveillance systems. In: Proceedings of the High Speed Local Networks Workshop at the IEEE Conference in Local Computer Networks, Tampa, FL, November 2002, pp. 728–729 (2002)
Foresti, G., Snidaro, L.: A distributed sensor network for video surveillance of outdoor environments. In: Proceedings of IEEE International Conference on Image Processing, New York, pp. 525–528 (2002)
Chang, C.-K., Huang, J.: Video surveillance for Hazardous Conditions Using Sensor Networks. In: Proceedings of the 2004 IEEE International Conference on Networking, Sensing & Control, March 2004, pp. 1008–1013 (2004)
Feng, W., Walpole, J., Feng, W., Pu, C.: Moving towards massively scalable video-based sensor networks. In: Proceedings of the Workshop on New Visions for LargeScale Networks: Research and Applications, Washington, DC (March 2001)
Ma, H., Liu, Y.: Correlation Based Video Processing in Video Sensor Networks. In: Proceedings of IEEE WirelessCom 2005, Maui, HI (June 2005)
Tian, D., Georganas, N.: A coverage-preserving node scheduling scheme for large wireless sensor networks. In: Proceeding of ACM WSNA, Atlanta, GA, pp. 32–41 (2002)
Wang, X., Xing, G., Zhang, Y., Lu, C., Pless, R., Gill, C.: Integrated coverage and connectivity configuration in wireless sensor networks. In: Proceeding of ACM Sensys, Los Angeles, CA, November 2003, pp. 28–39 (2003)
Heinzelman, W., Kulik, J., Balakrishnan, H.: Adaptive protocol for information dissemination in wireless sensor networks. In: Proceedings of ACM Mobicom, Seattle,WA, pp. 178–185 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tao, D., Ma, H., Liu, Y. (2005). Energy-Efficient Cooperative Image Processing in Video Sensor Networks. In: Ho, YS., Kim, HJ. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11582267_50
Download citation
DOI: https://doi.org/10.1007/11582267_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30040-3
Online ISBN: 978-3-540-32131-6
eBook Packages: Computer ScienceComputer Science (R0)