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Journal of Real-Time Image Processing

, Volume 11, Issue 3, pp 559–569 | Cite as

A hardware/software prototyping system for driving assistance investigations

  • Jakob Anders
  • Michael Mefenza
  • Christophe BobdaEmail author
  • Franck Yonga
  • Zeyad Aklah
  • Kevin Gunn
Original Research Paper

Abstract

A holistic design and verification environment to investigate driving assistance systems is presented, with an emphasis on system-on-chip architectures for video applications. Starting with an executable specification of a driving assistance application, subsequent transformations are performed across different levels of abstraction until the final implementation is achieved. The hardware/software partitioning is facilitated through the integration of OpenCV and SystemC in the same design environment, as well as OpenCV and Linux in the run-time system. We built a rapid prototyping, FPGA-based camera system, which allows designs to be explored and evaluated in realistic conditions. Using lane departure and the corresponding performance speedup, we show that our platform reduces the design time, while improving the verification efforts.

Keywords

System on chip  Prototyping Hardware/software system Image processing Design flow Driver assistance FPGA Hardware acceleration 

References

  1. 1.
    Aghajan, H., Cavallaro, A.: Multi-Camera Networks: Principles and Applications. Academic Press, London (2009)Google Scholar
  2. 2.
    Appiah, K., Hunter, A., Kluge, T., Aiken, P., Dickinson, P.: Fpga-based anomalous trajectory detection using sofm. In: Proceedings of the 5th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications, ARC ’09, pp. 243–254. Springer, Berlin (2009)Google Scholar
  3. 3.
    Becker, J., Vorbach, M.: Pact xpp architecture in adaptive system-on-chip integration. In: Plaks, T.P. (ed.) Proceedings of the International Conference on Engineering of Reconfigurable Systems and Algorithms, June 23–26, 2003, Las Vegas, Nevada, pp. 21–30. CSREA Press (2003)Google Scholar
  4. 4.
    Blackham, B.: The Development of a Hardware Platform for Real-Time Image Processing. The University of Western Australia, Australia (2006)Google Scholar
  5. 5.
    Bramberger, M., Doblander, A., Maier, A., Rinner, B., Schwabach, H.: Distributed embedded smart cameras for surveillance applications. IEEE Comput. Soc. 39, 68–75 (2006)CrossRefGoogle Scholar
  6. 6.
    Chen, P., Ahammad, P., Boyer, C., Huang, S., Lin, L., Lobaton, E., Meingast, M., Oh, S., Wang, S., Yan, P., Yang, A.Y., Yeo, C., Chang, L.-C., Tygar, D., Shankar Sastry, S.: Citric: A low-bandwidth wireless camera network platform. In: Second ACM/IEEE International Conference on Distributed Smart Cameras, pp. 1–10 (2008)Google Scholar
  7. 7.
    Filippov, A.: Encoding high-resolution ogg/theora video with reconfigurable fpgasGoogle Scholar
  8. 8.
    Hengstler, S., Prashanth, D., Fong, S., Aghajan, H.: Mesheye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance. In: IPSN’07, pp. 360–369 (2007)Google Scholar
  9. 9.
    Mirsky, E., DeHon, A.: MATRIX: a reconfigurable computing architecture with configurable instruction distribution and deployable resources. In: Field-Programmable Custom Computing Machines (1996)Google Scholar
  10. 10.
    Pham, D.T., Alcock, R.J.: Smart vision applications. In: Smart Inspection Systems, pp. 157–191. Academic Press, London (2003)Google Scholar
  11. 11.
    Rahimi, M., Baer, R., Iroezi, O.I., Garcia, J.C., Warrior, J., Estrin, D., Srivastava, M.: Cyclops: In situ image sensing and interpretation in wireless sensor networks. In: SenSys, pp. 192–204. ACM Press, New york (2005)Google Scholar
  12. 12.
    Rinner, B., Winkler, T., Schriebl, W., Quaritsch, M., Wolf, W.: The evolution from single to pervasive smart cameras. In: Distributed Smart Cameras, 2008. ICDSC 2008. Second ACM/IEEE International Conference on, pp. 1–10 (2008)Google Scholar
  13. 13.
    Shi, Y., Tsui, T.: An fpga-based smart camera for gesture recognition in hci applications. In: ACCV (1), pp. 718–727 (2007)Google Scholar
  14. 14.
    Wilson, A.: Auto cameras benefit from cmos imagers (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jakob Anders
    • 1
  • Michael Mefenza
    • 2
  • Christophe Bobda
    • 2
    Email author
  • Franck Yonga
    • 2
  • Zeyad Aklah
    • 2
  • Kevin Gunn
    • 2
  1. 1.Department of Computer ScienceUniversity of PotsdamPotsdamGermany
  2. 2.CSCE DepartmentUniversity of ArkansasFayettevilleUSA

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