• DocumentCode
    145375
  • Title

    License Plate Detection Method for Real-Time Video of Low-Cost Webcam Based on Hybrid SVM-Heuristic Approach

  • Author

    Khalil, Mohammed S. ; Kurniawan, Fajri

  • Author_Institution
    Center of Excellence in Inf. Assurance, King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2014
  • fDate
    7-9 April 2014
  • Firstpage
    321
  • Lastpage
    326
  • Abstract
    License plate recognition (LPR) systems have attracted the community to expand its benefit and usefulness. It gives easiness to keep tracks of the vehicles that enter and exit the same place. This success is influencing the people to develop mobile LPR systems. In the mobile LPR system, the camera is installed on a vehicle such as the police officer´s car. In such systems, the problem is more challenging compared to fixed LPR systems. The detection process becomes crucial in the mobile LPR systems, because the license plate can be captured in various angles. The environment also cannot be controlled, and it affects the performance of LPR systems significantly. Thus, this paper proposed license plate localization based on statistical features. The proposed method achieved promising accuracy 88.46% tested on collected database.
  • Keywords
    feature extraction; image sensors; mobile computing; object detection; object recognition; statistical analysis; support vector machines; traffic engineering computing; video signal processing; feature extraction; hybrid SVM-heuristic approach; licence plate detection method; license plate recognition systems; low-cost webcam; mobile LPR system; real-time video; statistical features; support vector machine; Cameras; Feature extraction; Image edge detection; Licenses; Real-time systems; Streaming media; Vehicles; feature extraction; intersection strategy; license plate detection; svm-based;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2014 11th International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4799-3187-3
  • Type

    conf

  • DOI
    10.1109/ITNG.2014.21
  • Filename
    6822217