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Supporting Pedestrians with Visual Impairment During Road Crossing: A Mobile Application for Traffic Lights Detection

  • Sergio Mascetti
  • Dragan Ahmetovic
  • Andrea Gerino
  • Cristian Bernareggi
  • Mario Busso
  • Alessandro Rizzi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9759)

Abstract

Many traffic lights are still not equipped with acoustic signals. It is possible to recognize the traffic light color from a mobile device, but this requires a technique that is stable under different illumination conditions. This contribution presents TL-recognizer, an application that recognizes traffic lights from a mobile device camera. The proposed solution includes a robust setup for image capture as well as an image processing technique. Experimental results give evidence that the proposed solution is practical.

Keywords

Blind people Visual impairments Mobile device Smartphones Traffic lights Computer vision 

Notes

Acknowledgments

The work of Andrea Gerino, Cristian Bernareggi and Sergio Mascetti was partially supported by grant “fondo supporto alla ricerca 2015” under project “Assistive technologies on mobile devices”. The work of Alessandro Rizzi was partially supported by grant “fondo supporto alla ricerca 2015” under project “Discovering Patterns in Multi-dimensional Data”.

References

  1. 1.
    Kim, Y., Kim, K., Yang, X.: Real time traffic light recognition system for color vision deficiencies. In: Proceedings of the Fourth International Conference of Mechatronics and Automation, pp. 76–81. IEEE Computer Society (2007)Google Scholar
  2. 2.
    Ivanchenko, V., Coughlan, J., Shen, H.: Real-time walk light detection with a mobile phone. In: Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A. (eds.) ICCHP 2010, Part II. LNCS, vol. 6180, pp. 229–234. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  3. 3.
    Roters, J., Jiang, X., Rothaus, K.: Recognition of traffic lights in live video streams on mobile devices. Trans. Circuits Syst. Video Technol. 21(10), 1497–1511 (2011)CrossRefGoogle Scholar
  4. 4.
    Mascetti, S., Ahmetovic, D., Gerino, A., Bernareggi, C., Busso, M., Rizzi, A.: Robust traffic lights detection on mobile devices for pedestrians with visual impairment. Comput. Vis. Image Underst. (2015). http://dx.org/10.1016/j.cviu.2015.11.017
  5. 5.
    Technical Committee CEN/TC 226 “Road equipment”: European Standard EN 12368:2006 on “traffic control equipment - signal head” (2006)Google Scholar
  6. 6.
    Suzuki, S., Abe, K.: Topological structural analysis of digitized binary images by border following. Int. J. Comput. Vis. Graph. Image Process. 30(1), 32–46 (1985)CrossRefzbMATHGoogle Scholar
  7. 7.
    Lewis, J.P.: Fast normalized cross-correlation. Int. J. Vis. Interface 10(1), 120–123 (1995)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sergio Mascetti
    • 1
    • 2
  • Dragan Ahmetovic
    • 1
  • Andrea Gerino
    • 1
    • 2
  • Cristian Bernareggi
    • 1
    • 2
  • Mario Busso
    • 1
  • Alessandro Rizzi
    • 1
  1. 1.EveryWare Lab, Department of Computer ScienceUniversità degli Studi di MilanoMilanItaly
  2. 2.EveryWare TechnologiesMilanoItaly

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