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Real-Time Recognition of Blue Traffic Signs Designating Directions

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Abstract

In this research we propose a real-time system to recognize blue traffic signs designating directions. This research is complementary to the previous work done on six annular red signs. The system consists of several processing steps: We firstly label the blue objects in each frame and segment them from the background. After that we try to verify if the segmented blue object is a sign candidate, and then we segment white objects within the blue object. Finally we classify the white objects by matching them to arrow patterns according to geometrical features, or reject them if no arrow pattern is matched. Classification is done using a decision tree. Processing time is about 110 ms/frame, and recognition rate is about 81%.

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References

  1. Marmo, R., Lombardi, L.: Road Bridge sign detection and classification. IEEE Intelligent Transportation Systems Conference, pp. 823–826 (2006)

  2. Priese, L., Rehrmann, V., Schian, R., Lakmann, R.: Traffic sign recognition based on color image evaluation. IEEE Intelligent Vehicles Symposium, pp. 95–100 (1993)

  3. Priese, L., Klieber, J., Lakmann, R., Rehrmann, V., Schian, R.: New results on traffic sign recognition. IEEE Intelligent Vehicles Symposium, pp. 249–254 (1994)

  4. Shaposhnikov, D.G., Lubov, N., Golovan, E.V., Shevtsova, A.: Road sign recognition by single positioning of space-variant sensor window. In Proceedings of 15th International Conference on Vision Interface, (2002)

  5. Bahlmann, C., Zhu, Y., Ramesh, V., Pellkofer, M., Koehler, T.: A system for traffic sign detection, tracking, and recognition using color, shape, and motion information. In Proceedings of Intelligent Vehicles Symposium, 2005, pp. 255–260. IEEE, (2002)

  6. Ihara, A., Fujiyoshi, H., Takagi, M., Kumon, H., Tamatsu, Y.: Improved matching accuracy in traffic sign recognition by using different feature subspaces. Machine Vision Applications 2009 (MVA2009), 3–26, pp. 130–133 (2009)

  7. Kiran, C.G., Prabhu, L.V., Abdu Rahiman, V., Rajeev, K.: Traffic sign detection and pattern recognition using support vector machine. IEEE Seventh International Conference on Advances in Pattern Recognition, pp. 87–90 (2009)

  8. Vacek, S., Schimmel, C., Dillmann, R.: Road-marking analysis for autonomous vehicle guidance. ECMR, online proc, 6 pages, (2007)

  9. Wendling, L., Loria, S.T.: Recognition of arrows in line drawings based on the aggregation of geometric criteria using the Choquet Integral. IEEE 7th International Conference on Document Analysis and Recognition, pp. 299–303 (2003)

  10. Gao, X.W., Podladchikova, L., Shaposhnikov, D., Hong, K., Shevtsova, N.: Recognition of traffic signs based on their colour and shape features extracted using human vision models. Elsevier. J. Vis. Commun. Image Represent. 17, 675–685 (2006)

    Article  Google Scholar 

  11. Baba, K., Hirai, Y.: Real-time recognition of traffic signs using opponent color. Proceedings of ITSWC2007, 12pages, (2007)

  12. Parker, J.R.: Algorithms for image processing and computer vision. Wiley, New York (1997)

    Google Scholar 

  13. Davies, E.R.: Machine vision: theory, algorithms, practicalities, 3rd edn. Morgan Kaufmann, San Francisco (2004)

    Google Scholar 

  14. Shneier, M.: Road sign detection and recognition. Submitted to the IEEE Computer Society International Conference on Computer Vision and Pattern Recognition, June (2005)

  15. de Berg, M., Cheong, O., van Kreveld, M., Overmars, M.: Computational geometry: algorithms and applications, 2nd edn. Springer, Berlin (2008)

    MATH  Google Scholar 

  16. Traffic Signs Handbook (in Japanese). Japan Contractors Association of Traffic Signs and Lane Makings (JCASM), (2004)

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Correspondence to Mohammed Hayyan Alsibai.

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Alsibai, M.H., Hirai, Y. Real-Time Recognition of Blue Traffic Signs Designating Directions. Int. J. ITS Res. 8, 96–105 (2010). https://doi.org/10.1007/s13177-010-0010-0

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  • DOI: https://doi.org/10.1007/s13177-010-0010-0

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