Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지
DOI QR코드

DOI QR Code

An Automatic Road Sign Recognizer for an Intelligent Transport System

  • Miah, Md. Sipon (Department of Electrical Engineering, University of Ulsan) ;
  • Koo, Insoo (Department of Electrical Engineering, University of Ulsan)
  • Received : 2012.09.09
  • Accepted : 2012.10.20
  • Published : 2012.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

Keywords

References

  1. R. Vicen-Bueno, R. Gil-Pita, M. P. Jarabo-Amores, and F. Lopez- Ferreras, "Complexity reduction in neural networks applied to traffic sign recognition tasks," in Proceedings of the 13th European Signal Processing Conference, Antalya, Turkey, 2005.
  2. H. X. Liu and B. Ran, "Vision-based stop sign detection and recognition system for intelligent vehicles," Transportation Research Record, vol. 1748, pp. 161-166, 2001. https://doi.org/10.3141/1748-20
  3. D. M. Gavrila, "Traffic sign recognition revisited," in Proceedings of the 21st DAGM Symposium for Mustererkennung, Bonn, Germany, pp. 86-93, 1999.
  4. H. Fleyeh and M. Dougherty, "Road and traffic sign detection and recognition," in Proceedings of the 10th Meeting and 16th Mini EURO Conference of the Euro Working Group on Transportation, Poznan, Poland, 2005.
  5. A. L. Yuille, D. Snow, and M. Nitzberg, "Signfinder: using color to detect, localize and identify informational signs," in Proceedings of the 6th International Conference on Computer Vision, Bombay, India, pp. 628-633, 1998.
  6. C. L. Huang and S. H. Hsu, "Road sign interpretation using matching pursuit method," in Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, pp. 329-333, 2000.
  7. L. Pacheco, J. Batlle, X. Cufi, "A new approach to real time traffic sign recognition based on colour information," in Proceedings of the Intelligent Vehicles Symposium, Paris, pp. 339-344, 1994.
  8. H. Ishida, T. Takahashi, I. Ide, Y. Mekada, and H. Murase, "Identification of degraded traffic sign symbols by a generative learning method," in Proceedings of the 18th International Conference on Pattern Recognition, Hong Kong, China, pp. 531- 534, 2006.
  9. C. Nunn, A. Kummert, and S. Muller-Schneiders, "A novel region of interest selection approach for traffic sign recognition based on 3D modeling," in Proceedings of the IEEE Intelligent Vehicles Symposium, Eindhoven, Netherlands, pp. 654-659, 2008.
  10. A. de la Escalera, J. M. Armingol, J. M. Pastor, and F. J. Rodriguez, "Visual sign information extraction and identification by deformable models for intelligent vehicles," IEEE Transactions on Intelligent Transportation Systems, vol. 5, no. 2, pp. 57-68, 2004. https://doi.org/10.1109/TITS.2004.828173
  11. H. Fleyeh, "Traffic sign recognition by fuzzy sets," in Proceedings of the IEEE Intelligent Vehicles Symposium, Eindhoven, Netherlands, pp. 422-427, 2008.
  12. A. de la Escalera, J. M. Armingol, and M. Mata, "Traffic sign recognition and analysis for intelligent vehicles," Image and Vision Computing, vol. 21, no. 3, pp. 247-258, 2003. https://doi.org/10.1016/S0262-8856(02)00156-7
  13. A. de la Escalera, L. E. Moreno, M. A. Salichs, and J. M. Armingol, "Road traffic sign detection and classification," IEEE Transactions on Industrial Electronics, vol. 44, no. 6, pp. 848-859, 1997. https://doi.org/10.1109/41.649946
  14. P. Paclik, J. Novovicova, P. Pudil, and P. Somol, "Road sign classification using Laplace kernel classifier," Pattern Recognition Letters, vol. 21, no. 13-14, pp. 1165-1173, 2000. https://doi.org/10.1016/S0167-8655(00)00078-7
  15. J. Torresen, J. W. Bakke, and L. Sekanina, "Efficient recognition of speed limit signs," in Proceedings of the 7th International IEEE Conference on Intelligent Transportation Systems, Washington: DC, pp. 652-656, 2004.
  16. M. M. Zadeh, T. Kasvand, and C. Y. Suen, "Localization and recognition of traffic signs for automated vehicle control systems," Intelligent Transportation Systems, Proceedings of the SPIE vol. 3207, Pittsburgh: PA, pp. 272-282, 1997.
  17. M. Be'nallal, and J. Meunier, "Real-time color segmentation of road signs," in Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering, Montreal, Canada, pp. 1823-1826, 2003.