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An Overview of Image Analysis Algorithms for License Plate Recognition

Author

Listed:
  • Aboura Khalid

    (University of Dammam, College of Business Administration, Dammam, Saudi Arabia)

  • Al-Hmouz Rami

    (King Abdulaziz University, Department of Electrical and Computer Engineering, Jeddah, Saudi Arabia)

Abstract

Background and purpose: We explore the problem of License Plate Recognition (LPR) to highlight a number of algorithms that can be used in image analysis problems. In management support systems using image object recognition, the intelligence resides in the statistical algorithms that can be used in various LPR steps. We describe a number of solutions, from the initial thresholding step to localization and recognition of image elements. The objective of this paper is to present a number of probabilistic approaches in LPR steps, then combine these approaches together in one system. Most LPR approaches used deterministic models that are sensitive to many uncontrolled issues like illumination, distance of vehicles from camera, processing noise etc. The essence of our approaches resides in the statistical algorithms that can accurately localize and recognize license plate.

Suggested Citation

  • Aboura Khalid & Al-Hmouz Rami, 2017. "An Overview of Image Analysis Algorithms for License Plate Recognition," Organizacija, Sciendo, vol. 50(3), pages 285-295, August.
    • Handle: RePEc:vrs:organi:v:50:y:2017:i:3:p:285-295:n:2
    DOI: 10.1515/orga-2017-0014
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