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Reseach Article

An Automatic Number Plate Recognition System for Car Park Management

by Mutua Simon Mandi, Bernard Shibwabo, Kaibiru Mutua Raphael
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 7
Year of Publication: 2017
Authors: Mutua Simon Mandi, Bernard Shibwabo, Kaibiru Mutua Raphael
10.5120/ijca2017915608

Mutua Simon Mandi, Bernard Shibwabo, Kaibiru Mutua Raphael . An Automatic Number Plate Recognition System for Car Park Management. International Journal of Computer Applications. 175, 7 ( Oct 2017), 36-42. DOI=10.5120/ijca2017915608

@article{ 10.5120/ijca2017915608,
author = { Mutua Simon Mandi, Bernard Shibwabo, Kaibiru Mutua Raphael },
title = { An Automatic Number Plate Recognition System for Car Park Management },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2017 },
volume = { 175 },
number = { 7 },
month = { Oct },
year = { 2017 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number7/28503-2017915608/ },
doi = { 10.5120/ijca2017915608 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:24:28.332799+05:30
%A Mutua Simon Mandi
%A Bernard Shibwabo
%A Kaibiru Mutua Raphael
%T An Automatic Number Plate Recognition System for Car Park Management
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 7
%P 36-42
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

References
  1. Litman, T. 2013. Parking Management Strategies, Evaluation and Planning. Retrieved from http://www.vtpi.org/park_man.pdf
  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 http://www.ijmer.com/papers/vol2_issue3/AE23742748.pdf
  3. Cornwall. 2009. Drivers on police files for life. Retrieved from http://www.westbriton.co.uk/Drivers-police-files-life/story-11398048-detail/story.html
  4. Roberts & Casanova 2012. Automated License Plate Recognition Systems: Policy and Operational Guidance for Law Enforcement. Retrieved from https://www.aclu.org/files/FilesPDFs/ALPR/federal/NHTSA/15948-16075DOJ-IACP%20report.pdf
  5. ACPO (2013). The police use of Automatic Number Plate Recognition Retrieved from http://www.acpo.police.uk/documents/crime/2013/201303CBA-ANPR.pdf
  6. Friedrich, M., Jehlicka, P. & Schlaich, J. 2008. Automatic number plate recognition for the observance of travel behavior. Retrieved from http://www.isv.uni-stuttgart.de/vuv/publication/downloads/200805_Fr_PJ_JS-ANPR.pdf
  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 http://www.camera-sdk.com/p_89-how-to-implement-number-plate-recognition-in-c-onvif.html
  9. Reshma, P. 2012. Noise Removal and Blob Identification Approach for Number Plate Recognition. Retrieved from http://research.ijcaonline.org/volume47/number8/pxc3879992.pdf
  10. Dhiraj, Y., Pramod, G. & Borole, B. 2014. A Review Paper on Automatic Number Plate Recognition (ANPR) System. Retrieved from http://www.scribd.com/doc/229724157/A-Review-Paper-on-Automatic-Number-Plate-Recognition-ANPR-System
  11. Kumar, R. & Singh, A. 2011. Character Segmentation in Gurumukhi Handwritten Text using Hybrid Approach. Retrieved from http://www.ijcte.org/papers/357-G831.pdf
  12. Casey, G. & Lecolinet, E. A Survey of Methods and Strategies in Character Segmentation. Retrieved from http://perso.telecom-paristech.fr/~elc/papers/pami96.pdf.
  13. Saha, S., Basu, S., Nasipuri, M. & Dipak, B. 2010. A Hough Transform based Technique for Text Segmentation. Retrieved from http://arxiv.org/ftp/arxiv/papers/1002/1002.4048.pdf
  14. Shah, K. & Sharma, A. 1998. Design and Implementation of Optical Character Recognition System to Recognize Gujarati Script using Template Matching. Retrieved from https://books.google.co.ke/books?id=vdCeBQAAQBAJ&pg=PA1&lpg=PA297&dq#v=onepage&q&f=false
  15. Dedgaonkar, G., Chandavale, A. & Sapkal, M. 2012. Survey of Methods for Character Recognition. Retrieved from http://ijeit.com/vol%201/Issue%205/IJEIT1412201205_36.pdf
  16. Eikvil, L. (1993). Optical Character Recognition. Retrieved from http://www.nr.no/~eikvil/OCR.pdf
  17. Daily mobile 2008. Retrieved from http://www.dailymobile.net/2008/10/24/symbian-application-nokia-multiscanner/
  18. iMore 2012. CamCard vs. WorldCard vs. Business Card Reader: card scanner for iPhone app shootout. Retrieved from http://www.imore.com/camcard-worldcard-business-card-reader-card-scanner-iphone-app-shootout
  19. Competitive Survey and White Paper of Automated License Plate Recognition Vendors (n.d). Retrieved from https://www.aclu.org/files/FilesPDFs/ALPR/arizona/alprpra_PhoenixPD_PhoenixAZ_4.pdf
  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 https://airbrake.io/blog/category/insight
  23. Kristensen T. (2016) Computational Intelligence, Evolutionary Computing and Evolutionary Clustering Algorithms. Bentham Science Publishers.
  24. Burge, S. 2011. The Systems Engineering Tool Box http://www.burgehugheswalsh.co.uk/uploaded/documents/CD-Tool-Box-V1.0.pdf
Index Terms

Computer Science
Information Sciences

Keywords

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