• DocumentCode
    3427403
  • Title

    Extraction and recognition of license plates of motorcycles and vehicles on highways

  • Author

    Lee, Hsi-Jian ; Chen, Si-Yuan ; Wang, Shen-Zheng

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., National Chiao-Tung Univ., Hsinchu, Taiwan
  • Volume
    4
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    356
  • Abstract
    A recognition system is proposed to extract and recognize license plates of motorcycles and vehicles on highways. In the first stage, a block-difference method is used to detect moving objects. According to the variance and the similarity of the M×N blocks defined on two diagonal lines, the blocks are categorized as three kinds: low-contrast, stationary and moving blocks. In the second stage, a screening method based on the projection of edge magnitudes is used to find two peaks in the projection histograms to bound license plates. The scanning lines with low counts can be removed. In the third stage, character images are segmented and recognized. In our experiments, we tested 180 pairs of images. The block-difference method has a 98% success rate and can remove 88% of pixels from an image on average. The screening method has a 94.4% success rate and the character recognition method has a 95.7% precision rate.
  • Keywords
    automobiles; character recognition; feature extraction; image motion analysis; image recognition; image segmentation; motorcycles; object detection; block-difference method; character image segmentation; character recognition method; highway vehicle; license plate extraction; license plate recognition; motorcycles; moving object detection; projection histograms; screening method; Character recognition; Histograms; Image edge detection; Image recognition; Image segmentation; Licenses; Motorcycles; Object detection; Road transportation; Road vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1333776
  • Filename
    1333776