The week's pick
Random Articles
Reseach Article
Automated Parking Management System using Image Processing Techniques
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 11 - Number 3 |
| Year of Publication: 2016 |
| Authors: Vaidehi P. De, D. Ragavesh |
10.5120/ijais2016451584
|
Vaidehi P. De, D. Ragavesh . Automated Parking Management System using Image Processing Techniques. International Journal of Applied Information Systems. 11, 3 ( Aug 2016), 6-10. DOI=10.5120/ijais2016451584
Abstract
Computerized systems being an integral part of the current era, an automated parking system is one of its most commonly used applications. This automated parking management system is designed to give access, exclusively to vehicles registered in the database. It takes the image of the vehicle and locates the license plate and identifies its license number. It then checks with the database to determine its access. This report is a detailed description of the image processing techniques used for Automatic Number Plate Recognition. It deals with computer vision and the various techniques used in image processing. The entire setup is compact enough to improve its portability and efficiency, whilst providing better security. The algorithms, train the machine for better pattern recognition to locate number plates. This system requires the vehicle to be physically present, so that security is not hampered with and access is denied to any vehicle that is not registered. The results were recorded to observe the quality of recognition.
References
- W. Al Faqheri and S. Mashohor, "A Real-Time Malaysian Automatic License Plate Recognition (M-ALPR) using Hybrid Fuzzy", International Journal of Computer Science and Network Security, vol. 9, no. 2, pp. 333-340, 2009.
- S. G. Patel, "Vehicle License Plate Recognition Using Morphology and Neural Network", IJCI, vol. 2, no. 1, pp. 1-7, 2013.
- B. Al Taan, "Vehicle Registration Checking System",unpublished.
- Zhai, X. and Bensaali, F., 2013, November. Standard Definition ANPR System on FPGA and an Approach to Extend it to HD. In GCC Conference and Exhibition (GCC), 2013 7th IEEE (pp. 214-219). IEEE.
- Kalaiselvi, K., Selvakani, S., Iyan, P.S. and Ananth, C., 2016. ANPR for Developing Countries
- D. Baggio, Mastering Open CV with practical computer vision projects. Biringham: Packt Publishing, 2012.R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press.
- I. Supriana and A. Nasution, "Arabic Character Recognition System Development", Procedia Technology, vol. 11, pp. 334-341, 2013.
- S. Saha, S. Basu, M. Nasipuri and D. Basu, "Localization of License Plates from Surveillance Camera Images: A Color Feature Based ANN Approach", International Journal of Computer Applications, vol. 1, no. 23, pp. 27-31, 2010.
- D. Molloy, "Capturing Images and Video on the Beaglebone | derekmolloy.ie", derekmolloy.ie, 2015. [Online]. Available:
- http://derekmolloy.ie/beaglebone-images-video-and-opencv/. [Accessed: 14- Nov- 2015].
- Coley, G., 2013. Beaglebone black system reference manual. Texas Instruments, Dallas.
- Bradski, G. and Kaehler, A., 2008. Learning OpenCV: Computer vision with the OpenCV library. " O'Reilly Media, Inc.".
- Bezdek, J.C., Keller, J., Krisnapuram, R. and Pal, N., 2006. Fuzzy models and algorithms for pattern recognition and image processing (Vol. 4). Springer Science & Business Media.
Index Terms
Keywords