• DocumentCode
    3405289
  • Title

    Precise 2-step segmentation of corrupted characters in License Plate Recognition applications

  • Author

    Sedaghat A, Nima ; Amindavar, Hamidreza

  • Author_Institution
    Electr. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    1086
  • Lastpage
    1089
  • Abstract
    Image-based License Plate Recognition (LPR) algorithms are the core modules of many Intelligent Transportation Systems (ITS). Different algorithms and approaches have been proposed so far. All of these methods have the following three steps in common: License Plate Localization, Character Segmentation & Character Recognition. There are many real-world issues encountered during the design of each step, including different plate formats, time-variant illumination conditions and etc. To have a reliable operator-free system, all of these need to be overcome. One of such issues which is the main focus of this article and so far has not been addressed in any previous work is the presence of characters corrupted by misplaced rivets/screws. In this paper we present a simple, yet effective technique based on traditional pattern matching methods which when combined with modern character recognition techniques, can bring up the success rates of current systems closer to 100%.
  • Keywords
    image matching; image segmentation; traffic information systems; corrupted characters segmentation; image recognition; intelligent transportation systems; license plate recognition; pattern matching; Artificial neural networks; Character recognition; Fasteners; Image recognition; Image segmentation; Licenses; Shape; Computer Vision; Image Processing; LPR; License Plate Recognition; Rivet; Segmentation; Skrew;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5655885
  • Filename
    5655885