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Research of Vehicle License Plate Location Algorithm Based on Color Features and Plate Processions

  • Yao-Quan Yang
  • Jie Bai
  • Rui-Li Tian
  • Na Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)

Abstract

Locating the region of a license plate is the key component of the vehicle plate recognition system. A novel method is adopted in this paper to replace the traditional method which is based on gray image. The method that sufficiently utilizes the color characteristics of the colored image is based on the color collocation of the plate’s background and characters combined with the plate’s structure and texture to locate the vehicle license plate. The plate’s region would then be emended and binarized. The location rate reaches 98% in experiments.

Keywords

Edge Point Color Model Gray Image Line Detection Plate Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Wei, W., Huang, X., Wang, M.: An Automatic System of Vehicle Number-plate Recognition Based on Neural Networks. Journal of Systems Engineering and Electronics 12, 63–72 (2001)Google Scholar
  2. 2.
    Hegt, H.A., De la Haye, R.J., Khan, N.A.: A High Performance License Plate Recognition System. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, San Diego, vol. 5, pp. 4357–4362 (1998)Google Scholar
  3. 3.
    Li, W.-J., Liang, D.-Q., Zhang, Q.: A Novel Approach for Vehicle License Plate Location Based on Edge-Color Pair. China Journal of Computers 27, 204–208 (2004)Google Scholar
  4. 4.
    Lee, E.R., Kim, P.K., Kim, H.J.: Automatic Recognition of a Car License Plate Using Color Image Processing. In: Proceedings of IEEE International Conference on Image Processing, Austin, Texas, pp. 301–305 (1994)Google Scholar
  5. 5.
    Xu, L., Oja, E., Kultanan, P.: Randomized Hough transform (RHT). Pattern Recognition Letters, 331–338 (1990)Google Scholar
  6. 6.
    Xu, G.-F., Li, B., Shen, Z.-K.: An Efficient Random Algorithm for Lines Detection. Journal of Image and Graphics 8, 1418–1421 (2003)Google Scholar
  7. 7.
    Li, W.-J., Liang, D.-Q., Cui, L.-Y.: Novel License Plate Image Preprocessing Approach for Character Segmentation. Application Research of Computers 21, 258–260 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yao-Quan Yang
    • 1
  • Jie Bai
    • 1
  • Rui-Li Tian
    • 1
  • Na Liu
    • 1
  1. 1.Faculty of Control Science and EngineeringNorth China Electric Power UniversityBaodingChina

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