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Real Scene Sign Recognition

  • Linlin Li
  • Chew Lim Tan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6020)

Abstract

A common problem encountered in recognizing signs in real-scene images is the perspective deformation. In this paper, we employ a descriptor named Cross Ratio Spectrum for recognizing real scene signs. Particularly, this method will be applied in two different ways: recognizing a multi-component sign as an whole entity or recognizing individual components separately. For the second strategy, a graph matching is used to finally decide the identify of the query sign.

Keywords

Graphics Recognition Real Scene Recognition Perspective Deformation 

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References

  1. 1.
    Barber, C.B., Dobkin, D.P., Huhdanpaa, H.T.: The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software 22(4), 469–483 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 509–522 (2002)CrossRefGoogle Scholar
  3. 3.
    de la Escalera, A., Moreno, L., Salichs, M., Armingol, J.: Road traffic sign detection and classification. IEEE Transactions on Industrial Electronics 44(6) (1997)Google Scholar
  4. 4.
    Lalondeand, M., Li, Y.: Road signs recognition - survey of the state of the art. Technique Report, CRIM-IIT (1995)Google Scholar
  5. 5.
    Lee, S.W., Kim, J.S.: Multi-lingual, multi-font, multi-size large-set character recognition using self-organizing neural network. In: Proceedings of the 3rd International Conference on Document Analysis and Recognition, vol. 1, pp. 23–33 (1995)Google Scholar
  6. 6.
    Li, L., Tan, C.L.: Character recognition under severe perspective distortion. In: Proceedings of the 19th International Conference on Pattern Recognition (2008)Google Scholar
  7. 7.
    Mundy, J.L., Zisserman, A.P.: Geometric invariance in computer vision. MIT Press, Cambridge (1992)Google Scholar
  8. 8.
    Rehrmann, V., Priese, L.: Fast and robust segmentation of natural color scenes. In: Chin, R., Pong, T.-C. (eds.) ACCV 1998. LNCS, vol. 1351. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  9. 9.
    Yamaguchi, T., Maruyama, M., Miyao, H., Nakano, Y.: Digit recognition in a natural scene with skew and slant normalization. International Journal of Document Analysis and Recognition 7(2-3), 168–177 (2005)CrossRefGoogle Scholar
  10. 10.
    Zhou, P., Li, L., Tan, C.L.: Character recognition under severe perspective distortion. In: Proceedings of the 10th International Conference on Document Analysis and Recognitionn (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Linlin Li
    • 1
  • Chew Lim Tan
    • 1
  1. 1.Computer ScienceNational University of SingaporeSingapore

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