Communications - Scientific Letters of the University of Zilina 2010, 12(11):86-92 | DOI: 10.26552/com.C.2010.3A.86-92

Intelligent Traffic System: Cooperation of Manet and Image Processing

Stefan Badura1, Anton Lieskovsky1
1 Faculty of Management Science and Informatics, University of Zilina, Slovakia

This paper presents a model for intelligent traffic system. Proposed methods describe ideas of information computing from images and its distribution to different nodes in traffic system. Two algorithms for foreground extraction forwarded by classification of extracted objects are discussed in the paper.. These approaches serve as a basis for information computing. Communication framework over MANET is presented for efficient information delivery. Appropriate protocol is designed at first, and then some algorithms for efficient data delivery are discussed.

Keywords: no keywords

Published: October 31, 2010  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Badura, S., & Lieskovsky, A. (2010). Intelligent Traffic System: Cooperation of Manet and Image Processing. Communications - Scientific Letters of the University of Zilina, 12(3A), 86-92. doi: 10.26552/com.C.2010.3A.86-92
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. BADURA, S., LIESKOVSKY, A.: Advanced Utilization of Image Processing from Industrial Cameras in Traffic. In: Proc. EURO-Zel Zilina 18th International Symposium, ISBN: 978-80-554-0198-0, pp. 153-160, 2010.
    2. YILMAZ, A., JAVED, O., SHAH, M.: Object Tracking: A Survey. In: ACM Comput. Surv. 38, 4, Article 13, p. 45, 2006. Go to original source...
    3. LOWE, D. G.: Object Recognition from Local Scale-invariant Features. In: Proc. of the International Conference on Computer Vision, pp. 1150-1157, 1999. Go to original source...
    4. BAY, H., ESS, A., TUYTELAARS, T., VAN GOOL, L.: SURF: Speeded Up Robust Features. In: Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346-359, 2008. Go to original source...
    5. STAUFFER, CH., GRIMSON, W.E.L.: Adaptive background mixture models for real-time tracking [online].
    6. OASIS: Common Alerting Protocol, v. 1.0. OASIS Standard 200402, March 2004. http://www.terena.org/activities/tf-storage/storage/meetings/1/NDS_PSNC_collaboration_on_storage_services.ppt [online].

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content