Fusion Model for Traffic Sign Detection, Tracking and Recognition

  • Authors

    • Shubham Dhingra
    • G Saranya
    • Shalini Diwakar
    • Manish Kumar
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.15889
  • traffic sign, detection, tracking, recognition.
  • A video-input traffic sign recognition is an advanced application which is a part of Intelligent Transport System(ITS) that provides information to the vehicles in order to make them safe and coordinated on road. The approach is to take a video as an input, divide it into series of frames and implement detection and recognition under mobile conditions. There are three major components: 1) detection; 2) recognition; 3) classification. We implement our technology on real data sets to obtain results in real-time manner.

     

     

  • References

    1. [1] M. Da Lio et al., “Artificial co-drivers as a universal enabling technology for future intelligent vehicles and transportation systems,†IEEE Trans. Intell. Transp. Syst., vol. 16, no. 1, pp. 244–263, Feb. 2015.

      [2] J. Zhang, F.-Y. Wang, K. Wang, W.-H. Lin, X. Xu, and C. Chen, “Data-driven intelligent transportation systems: A survey,†IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1624–1639, Dec. 2011.

      [3] U. Handmann, T. Kalinke, C. Tzomakas, M. Werner, and W. V. Seelen, “An image processing system for driver assistance,†Image Vis. Comput., vol. 18, no. 5, pp. 367–376, 2000.

      [4] R. Timofte, V. A. Prisacariu, L. J. V. Gool, and I. Reid, “Combining traffic sign detection with 3D tracking towards better driver assistance,†in Emerging Topics in Computer Vision and its Applications, E. C. H. Chen, Ed. Singapore: World Scientific, 2011.

      [5] Z. Zhu, D. Liang, S. Zhang, X. Huang, B. Li, and S. Hu, “Traffic-sign detection and classification in the wild,†in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2016, pp. 2110–2118.

      [6] F. Zaklouta and B. Stanciulescu, “Real-time traffic sign recognition in three stages,†Robot. Auto. Syst., vol. 62, no. 1, pp. 16–24, 2014.

      [7] S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Gil- Jimenez, H. Gomez-Moreno, and F. Lopez-Ferreras, “Road-sign detection and recognition based on support vector machines,†IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, pp. 264–278, Jun. 2007.

      [8] R. Timofte, K. Zimmermann, and L. J. V. Gool, “Multi- view traffic sign detection, recognition, and 3D localisation,†in Proc. IEEE Workshop Appl. Comput. Vis., Dec. 2009, pp. 1–8.

      [9] X. W. Gao, K. Hong, P. Passmore, L. Podladchikova, and D. Shaposhnikov, “Colour vision model-based approach for segmentation of traffic signs,†J. Image Video Process. (EURASIP), vol. 2008, no. 1, pp. 1–7, 2008.

      [10] X. W. Gao, L. Podladchikova, D. Shaposhnikov, K. Hong, and N. Shevtsova, “Recognition of traffic signs based on their colour and shape features extracted using human vision models,†J. Vis. Commun. Image Represent., vol. 17, no. 4, pp. 675–685, 2006.

      [11] S. Lafuente-Arroyo, S. Salcedo-Sanz, S. Maldonado- Bascón, J. A. Portilla-Figueras, and R. J. López-Sastre, “A decision support system for the automatic management of keep-clear signs based on support vector machines and geographic information systems,†Expert Syst. Appl., vol. 37, no. 1, pp. 767–773, 2010.

      [12] P. Gil-Jiménez, S. Maldonado-Bascón, H. Gómez- Moreno, S. Lafuente-Arroyo, and F. López-Ferreras, “Traffic sign shape classification and localization based on the normalized FFT of the signature of blobs and 2D homographies,†Signal Process., vol. 88, no. 12, pp.2943–2955, 2008.

      [13] V. A. Prisacariu, R. Timofte, K. Zimmermann, I. Reid, and L. V. Gool, “Integrating object detection with 3D tracking towards a better driver assistance system,†in Proc. Int. Conf. Pattern Recognit., 2010, pp. 3344–3347.

      [14] F. S. Khan, R. M. Anwer, J. van de Weijer, A. D. Bagdanov, M. Vanrell, and A. M. Lopez, “Color attributes for object detection,†in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2012, pp. 3306–3313.

      [15] P. Dollár, R. Appel, S. Belongie, and P. Perona, “Fast feature pyramids for object detection,†IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 8, pp. 1532–1545, Aug. 2014.

      [16] S. Houben, J. Stallkamp, J. Salmen, M. Schlipsing, and C. Igel, “Detection of traffic signs in real-world images: The german traffic sign detection benchmark,†in Proc. Int. Joint Conf. Neural Netw., Aug. 2013, pp. 1–8.

      [17] S. Segvi´c, K. Brki´c, Z. Kalafati´c, and A. Pinz, “Exploiting temporal and spatial constraints in traffic sign detection from a moving vehicle,†Mach. Vis. Appl., vol. 25, no. 3, pp. 649–665, 2014.

  • Downloads

  • How to Cite

    Dhingra, S., Saranya, G., Diwakar, S., & Kumar, M. (2018). Fusion Model for Traffic Sign Detection, Tracking and Recognition. International Journal of Engineering & Technology, 7(3.12), 112-115. https://doi.org/10.14419/ijet.v7i3.12.15889