Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Automatic Car License Plate Detection System for Odd and Even Series

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Sapna Gaur, Sweta Singh
10.5120/ijca2016911557

Sapna Gaur and Sweta Singh. Automatic Car License Plate Detection System for Odd and Even Series. International Journal of Computer Applications 150(7):12-16, September 2016. BibTeX

@article{10.5120/ijca2016911557,
	author = {Sapna Gaur and Sweta Singh},
	title = {Automatic Car License Plate Detection System for Odd and Even Series},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2016},
	volume = {150},
	number = {7},
	month = {Sep},
	year = {2016},
	issn = {0975-8887},
	pages = {12-16},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume150/number7/26104-2016911557},
	doi = {10.5120/ijca2016911557},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

An automatic car license plate detection system is essential for today’s busy traffic as it allows for quick traffic monitoring, toll processing and law enforcements related to traffic. Over the years many researchers have successfully developed much automatic car license plate detection system. Each system has its own set of advantages and limitations. In India, the need for automatic car license plate detection system is highly essential. Currently States like Delhi have adopted an Odd-even based traffic policy to bring down the levels of traffic pollution. In such scenarios it becomes highly difficult for the traffic inspectors to manually monitor odd-even series car plates. Thus, this work is a preliminary effort in developing an automatic car license plate detection system for odd-even based systems and it also supports the classification of car license based on the color of the license plate like private vehicle, commercial vehicle, government vehicle and so on. This work makes use of integration of SURF, Multiclass SVM and OCR for car license plate detection system.The proposed system is very fast and accurate results are obtained in less time. The system on execution successfully classifies the odd and even vehicles with an accuracy of 94%.

References

  1. Christos Nikolaos E. Anagnostopoulos, Ioannis E. Anagnostopoulos, VassiliLoumos, and EleftheriosKayafas, "A License Plate-Recognition Algorithm for Intelligent Transportation System Applications," pp. 377-392, 2006.
  2. Kaushik Deb, Ibrahim Kahn, AnikSaha, and Kang-Hyun Jo, "An Efficeint Method of Vehicle License Plate Recognition Based on Sliding Concentric Windows and Artificial Neural Network," Procedia Technology, vol. 4, pp. 812-819, 2012.
  3. Shen-Zheng Wang and Hsi-Jian Lee, "A cascade framework for real-time statistical plate recognition system," IEEE Trans. Inf. Forensics security, vol. 2, no. 2, pp. 267-282, 2007.
  4. PrathameshKulkarni, AshishKhatri, PrateekBanga, and Kushal Shah, "Automatic Number Plate Recognition (ANPR)," in RADIOELEKTRONIKA. 19th International Conference, 2009.
  5. Zhen-Xue Chen, Cheng-Yun Liu, Fa-Liang Chang, and Guo-You Wang, "Automatic License-Plate Location and Recognition Based on Feature Saliance," IEEE Transactions on Vehicular Technology, vol. 58, no. 7, pp. 3781-3785, 2009.
  6. Ch.Jaya Lakshmi, Dr.A.Jhansi Rani, Dr.K.Sri Ramakrishna, and M. KantiKiran, "A Novel Approach for Indian License Recognition System," International Journal of Advanced Engineering Sciences and Technologies, vol. 6, no. 1, pp. 10-14, 2011.
  7. AbdulkarSengur and YanhuiGuo, "Color texture image segmentation based on neutrosophic set and wavelet transformation ," Computer Vision and Image Understanding, vol. 115, no. 8, pp. 1134-1144, August 2011.
  8. Jiann-Jone Chen, Chun-Rong Su, W.E.L Grimson, Jun-Lin Liu, and De-HuiShiue, "Object Segmentation of Database Images by Dual Multiscale Morphological Reconstructions and Retrieval Applications," IEEE Transactions on Image Processing, vol. 21, no. 2, pp. 828-843, 2012.
  9. MahmoodAshooriLalimi, SedighehGhofrani, and Des McLernon, "A vehicle license plate detection method using region and edge based methods," Computers & Electrical Engineering, November 2012.
  10. M. S. Sarfraz et al., "Real-Time automatic license plate recognition for CCTV forensicc applications," Journal of Real-Time Image Processing- Springer Berlin/Heidelberg, 2011.
  11. H. ErdincKocer and K. KursatCevik, "Artificial neural netwokrs based vehicle license plate recognition," Procedia Computer Science, vol. 3, pp. 1033-1037, 2011.
  12. A Roy and D.P Ghoshal, "Number Plate Recognition for use in different countries using an improved segmenation," in 2nd National Conference on Emerging Trends and Applications in Computer Science(NCETACS), 2011, pp. 1-5.
  13. HuShuo, Wu Na, SongaHuajun, “Object Tracking Method Based on SURF”, Elsevier, Conference on Modelling, Identification and Control. AASRI Procedia,Volume 3, 2012, pp. 351–356.
  14. PhalgunPandya, Mandeep Singh “Morphology based approach to recognize Number plate in India” International Journal of Soft Computing and Engineering (IJSCE)ISSN: 2231-2307, Volume-1, Issue-3, July 2011.

Keywords

Car License plate detection, Odd even system, SVM, SURF, OCR