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IJML 2012 Vol.2(2): 93-98
doi: 10.7763/IJMLC.2012.V2.95

Automatic Parking Management System and Parking Fee Collection Based on Number Plate Recognition

M. M. Rashid1 , A. Musa1 , M. Ataur Rahman1,2 , N. Farahana1 , A. Farhana1

  • 1Mechatronics Eng. Department International Islamic University Malaysia Kuala Lumpur, Malaysia.
  • 2Mechanical Eng. Department International Islamic University Malaysia Kuala Lumpur, Malaysia.

Abstract

This paper discussed on automatic parking system and electronic parking fee collection based on vehicle number plate recognition. The aim of this research is to develop and implement an automatic parking system that will increase convenience and security of the public parking lot as well as collecting parking fee without hassles of using magnetic card. The auto parking system will able to have less interaction of humans and use no magnetic card and its devices. In additions to that, it has parking guidance system that can show and guide user towards a parking space. The system used image processing of recognizing number plates for operation of parking and billing system. Overall, the systems run with pre-programmed controller to make minimum human involvement in parking system and ensure access control in restricted places. This paper presents algorithm technology based method for license plate extraction from car images followed by the segmentation of characters and reorganization and also develop electronics parking fee collection system based on number plate information.

Keywords

  • Automatic parking system
  • autocorrelation
  • image processing
  • mean square error
  • plate number recognition structural similarity index
95-A009

How to Cite

Copied

M. M. Rashid, A. Musa, M. Ataur Rahman, N. Farahana, and A. Farhana, "Automatic Parking Management System and Parking Fee Collection Based on Number Plate Recognition," International Journal of Machine Learning, vol. 2, no. 2, pp. 93-98, 2012. https://doi.org/10.7763/IJMLC.2012.V2.95

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD