CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A Review of Recognition Technique Used Automatic License Plate Recognition System

by Sheetal Rani, Pawan Kumar Dahiya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 17
Year of Publication: 2015
Authors: Sheetal Rani, Pawan Kumar Dahiya
10.5120/21630-4938

Sheetal Rani, Pawan Kumar Dahiya . A Review of Recognition Technique Used Automatic License Plate Recognition System. International Journal of Computer Applications. 121, 17 ( July 2015), 6-9. DOI=10.5120/21630-4938

@article{ 10.5120/21630-4938,
author = { Sheetal Rani, Pawan Kumar Dahiya },
title = { A Review of Recognition Technique Used Automatic License Plate Recognition System },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 17 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number17/21630-4938/ },
doi = { 10.5120/21630-4938 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:08:39.561417+05:30
%A Sheetal Rani
%A Pawan Kumar Dahiya
%T A Review of Recognition Technique Used Automatic License Plate Recognition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 17
%P 6-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic License Plate Recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images or video as input. A learning based approach plays a very important role in recognition process. ALPR system consists of four modules named as Acquisition of an image, localization of license plate, segmentation of an image and character recognition of license plate. Recognition module helps in recognition of character that is present on license plate. Template Matching, Neural network (NN), Support Vector Machine (SVM) etc. can be used as recognition process. This paper presents different methods of character recognition in an Automatic License Plate Recognition system (ALPR). Recognition techniques are presented along with their advantages and disadvantages. The methods are categorized according to their response, accuracy and faster response. The future foresees for researchers are also given at the end of the paper.

References
  1. Sheetal Rani, Pawan Kumar Dahiya, "A comprehensive study of different techniques of automatic license plate recognition system," TEQIP sponsored national conference on Advances in Electronics & Communication Technologies, Jan. , 2015, pp. 159-163.
  2. Jitender Kumar, Pawan Kumar Dahiya, "Automatic number plate recognition: a state-of-the-art", the World congress on Engineering 2014 (WCE 2014) London, U. K. , july, 2014.
  3. Priya Sharma, Randhir Singh, "Survey and classification of character recognition system," International Journal of Engineering Trends and Technology, Volume-4, Issue3, pp. 315-318, 2013.
  4. Shan Du, Mahmoud Ibrahim, Mohamed Shehata, "Automatic license plate recognition (ALPR): a state-of-the art review," IEEE Transactions on circuits and systems for video technology, Vol. 23, No. 2, pp. 311-325, February 2013.
  5. Suruchi G. Dedgaonkar, Anjali A. Chandavale, Ashok M. Sapkal, "Survey of methods for character recognition," International Journal of Engineering and Innovative Technology (IJEIT), Volume 1, Issue 5, pp. 180-189, May 2012.
  6. Vivek Shrivastava1 and Navdeep Sharma, "Artificial neural network based optical character recognition," International Journal (SIPIJ) , Vol. 3, No. 5, pp. 73-80, October 2012.
  7. P. K. Dahiya, "Recent Trends in Evolutionary Computation," Ph. D. thesis, M. D. University, Rohtak, India, April, 2011.
  8. H. E. Kocer and K. K. Cevik, "Artificial neural networks based vehicle license plate recognition," in proc. Comput. Sci. , vol. 3. 2011, pp. 12–137.
  9. J. Jiao, Q. Ye, and Q. Huang, "A configurable method for multistyle license plate recognition," Pattern Recognit. , vol. 42, no. 3, pp. 358–369, 2009.
  10. S. N. H. S. Abdullah, M. Khalid, R. Yusof, and K. Omar, "License plate recognition using multicluster and multilayer neural networks," Inform. and Comm. Tech. , vol. 1, Apr. 2006. pp. 1818–1823.
  11. S. Tang and W. Li, "Number and letter character recognition of vehicle license plate based on edge Hausdorff distance," in Proc. Int. Conf. Parallel Distributed Comput. Applicat. Tech. , 2005, pp. 850–852.
  12. Y. Amit, D. Geman, and X. Fan, "A coarse-to-fine strategy for multiclass shape detection," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 26, no. 12, pp. 1606–1621, Dec. 2004.
  13. X. Lu, X. Ling, and W. Huang, "Vehicle license plate character recognition," in proc. Int. Conf. Neur. Netw. Signal Process. , vol. 2. 2003, pp. 166–169.
  14. M. Sarfraz, M. J. Ahmed, and S. A. Ghazi, "Saudi Arabian license plate recognition system," in proc. Int. Conf. Geom. Model. Graph. , 2003, pp. 36–41.
  15. P. Zhang and L. H. Chen, "A novel feature extraction method and hybrid tree classification for handwritten numeral recognition," in proc. Pattern Recognit. Lett. , vol. 23, no. 1, 2002, pp. 45–56.
  16. M. -K. Kim and Y. -B. Kwon, "Recognition of gray character using Gabor filters," in Proc. Int. Conf. Inform. Fusion, vol. 1. 2002, pp. 43–426.
  17. K. K. Kim, K. I. Kim, J. B. Kim, and H. J. Kim, "Learning-based approach for license plate recognition," in Proc. IEEE Signal Process. Soc. Workshop Neur. Netw. Signal Process. , vol. 2. Dec. 2000, pp. 614–623.
  18. T. Naito, T. Tsukada, K. Yamada, K. Kozuka, and S. Yamamoto, "Robust license-plate recognition method for passing vehicles under outside environment," IEEE Trans. Veh. Tech. , vol. 49, no. 6, pp. 2309–233, Nov. 2000.
  19. S. H. Park, K. I. Kim, K. Jung, H. J. Kim, "Locating vehicle license plates using neural networks", IEEE Electronics Letters, Vol. 35, No. 17, pp 1475- 1477, 1999.
  20. H. A. Hegt, R. J. Haye, and N. A. Khan, "A high performance license plate recognition system," in Proc. IEEE Int. Conf. Syst. Man Cybern. , vol. 5. Oct. 1998, pp. 4357–4362.
  21. S. Draghici, "A neural network based artificial vision system for license plate recognition," International Journal of Neural Systems, Vol. 8, No. 1, 1997.
  22. H. J. Kim, D. W. Kim, S . K. Kim, J. K. Lee, "Automatic recognition of a vehicle license plate using color image processing," Engineering Design and Automation Journal, Vol. 3, No. 1, 1997.
  23. H. J. Kang and J. Kim, "Probabilistic framework for combining multiple classifier at abstract level," in proc. Int. Conf. Document Anal. Recognition, vol. 1. 1997, pp. 870–874.
  24. P. Comelli, P. Ferragina, M. N. Granieri, and F. Stabile, "Optical recognition of motor vehicle license plates," IEEE Trans. Veh. Tech. , vol. 44, no. 4, pp. 790–799, Nov. 1995.
  25. C. J. Ahmad and M. Shridhar, "Recognition of handwritten numerals with multiple feature and multistage classifier," Pattern Recognit. , vol. 2, no. 28, pp. 153–160, 1995.
  26. Y. S. Huang and C. Y. Suen, "A method of combining multiple experts for the recognition of unconstrained handwritten numerals," IEEE Trans. Pattern Anal. Mach. Intel. , vol. 17, no. 1, pp. 90–93, Jan. 1995.
  27. E. R. Lee, P. K. Kim, H. J. Kim, "Automatic recognition of a vehicle license plate using color image processing," in proc. International Conference on Image Processing (ICIP'94), Vol. 2, 1994, pp. 301-305.
  28. K. Miyamoto, K. Nagano, M. Tamagawa, I. Fujita, and M. Yamamoto, "Vehicle license-plate recognition by image analysis," in proc. Int. Conf. Ind. Electron. Control Instrum. , vol. 3, pp. 1734–1738, 1991.
  29. K. Kanayama, Y. Fujikawa, K. Fujimoto, and M. Horino, "Development of vehicle-license number recognition system using real-time image processing and its application to travel-time measurement," in proc. IEEE Veh. Tech. Conf. , May 1991, pp. 798–804.
  30. Y. Dia, N. Zheng, X. Zhang, and G. Xuan, "Automatic recognition of province name on the license plate of moving vehicle," in proc. Int. Conf. Pattern Recognit. , vol. 2. , pp. 927–929, 1988.
Index Terms

Computer Science
Information Sciences

Keywords

Automatic License Plate Recognition (ALPR) Artificial Neural network (ANN) Neural Network (NN) Support Vector Machine (SVM) Optical Character Recognition (OCR).

Powered by PhDFocusTM