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An Automatic Number Plate Recognition System for Car Park Management

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Mutua Simon Mandi, Bernard Shibwabo, Kaibiru Mutua Raphael

Mutua Simon Mandi, Bernard Shibwabo and Kaibiru Mutua Raphael. An Automatic Number Plate Recognition System for Car Park Management. International Journal of Computer Applications 175(7):36-42, October 2017. BibTeX

	author = {Mutua Simon Mandi and Bernard Shibwabo and Kaibiru Mutua Raphael},
	title = {An Automatic Number Plate Recognition System for Car Park Management},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2017},
	volume = {175},
	number = {7},
	month = {Oct},
	year = {2017},
	issn = {0975-8887},
	pages = {36-42},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017915608},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Automatic Number Plate Recognition (ANPR) is an internationally recognized methodology that is used in vehicle identification. ANPR systems allow for real time recognition of a vehicle’s number plate. Vehicle parking is an important component within any transportation system, whereby vehicles are often parked at destinations. With an increased number of motor vehicles on roads especially in developing countries, there is need for a vehicle identification mechanism that is effective, affordable and efficient. There are also increased insecurity challenges including terrorism which call for increased surveillance. In most academic institutions and car parks, the ongoing car park entry registration process for visitors, staff or students entering the institution involves a security guard having to confirm membership details by checking for membership sticker on the windscreen of the vehicle or by checking the driver’s identification card. This process of writing is tedious and time consuming and is prone to inaccurate recordings, furthermore the backup and sharing of this vehicle information is difficult because the data is hard copy. We propose the adoption of a mobile based software solution that has ANPR capabilities to aid in vehicle identification and vehicle registration. The software application that was developed adopted an object oriented analysis and design methodology, the software developed implements Optical Character Recognition (OCR) using the mobile device camera to detect and capture the vehicle number plate. The proposed solution reduced registration time from 30 seconds to 6 seconds in addition to other benefits. It was recommended that the system be adopted and implemented to address the current challenges in vehicle registration and surveillance.


  1. Litman, T. 2013. Parking Management Strategies, Evaluation and Planning. Retrieved from
  2. Subraman T. 2012. Parking Study on Main Corridors in Major Urban Centre. International Journal of Modern Engineering Research (IJMER) ISSN: 2249-6645. Retrieved from
  3. Cornwall. 2009. Drivers on police files for life. Retrieved from
  4. Roberts & Casanova 2012. Automated License Plate Recognition Systems: Policy and Operational Guidance for Law Enforcement. Retrieved from
  5. ACPO (2013). The police use of Automatic Number Plate Recognition Retrieved from
  6. Friedrich, M., Jehlicka, P. & Schlaich, J. 2008. Automatic number plate recognition for the observance of travel behavior. Retrieved from
  7. Lotufo, R., Morgan, D. & Johnson, S. 2013. Automatic license plate recognition (ALPR) a state-of-the-art review. Journal of IEEE transaction on circuits and system for video technology, vol. 23, no, 2013, pp. 311-325 DOI:10.1109/TCSVT.2012.2203741
  8. Camera-sdk Retrieved from
  9. Reshma, P. 2012. Noise Removal and Blob Identification Approach for Number Plate Recognition. Retrieved from
  10. Dhiraj, Y., Pramod, G. & Borole, B. 2014. A Review Paper on Automatic Number Plate Recognition (ANPR) System. Retrieved from
  11. Kumar, R. & Singh, A. 2011. Character Segmentation in Gurumukhi Handwritten Text using Hybrid Approach. Retrieved from
  12. Casey, G. & Lecolinet, E. A Survey of Methods and Strategies in Character Segmentation. Retrieved from
  13. Saha, S., Basu, S., Nasipuri, M. & Dipak, B. 2010. A Hough Transform based Technique for Text Segmentation. Retrieved from
  14. Shah, K. & Sharma, A. 1998. Design and Implementation of Optical Character Recognition System to Recognize Gujarati Script using Template Matching. Retrieved from
  15. Dedgaonkar, G., Chandavale, A. & Sapkal, M. 2012. Survey of Methods for Character Recognition. Retrieved from
  16. Eikvil, L. (1993). Optical Character Recognition. Retrieved from
  17. Daily mobile 2008. Retrieved from
  18. iMore 2012. CamCard vs. WorldCard vs. Business Card Reader: card scanner for iPhone app shootout. Retrieved from
  19. Competitive Survey and White Paper of Automated License Plate Recognition Vendors (n.d). Retrieved from
  20. Leszek A. M. 2007. Requirements Analysis and Systems Design. Pearson Education Canada.
  21. Murch R. (2012). The Software Development Lifecycle - A Complete Guide. Amazon Digital Services LLC
  22. Alwan M. 2016. Getting even more context for errors & exceptions. Retrieved from
  23. Kristensen T. (2016) Computational Intelligence, Evolutionary Computing and Evolutionary Clustering Algorithms. Bentham Science Publishers.
  24. Burge, S. 2011. The Systems Engineering Tool Box


ANPR (Automatic Number Plate Recognition), Vehicle surveillance, Vehicle Parking, Optical Character Recognition