Call for Paper - May 2019 Edition
IJCA solicits original research papers for the May 2019 Edition. Last date of manuscript submission is April 20, 2019. Read More

A Vertical Edge Detection Algorithm for Car License Plate Detection

IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies
© 2015 by IJCA Journal
NCESC 2015 - Number 1
Year of Publication: 2015
Vijaya B. Ghule
Amol B. Jagadale

Vijaya B Ghule and Amol B Jagadale. Article: A Vertical Edge Detection Algorithm for Car License Plate Detection. IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies NCESC 2015(1):26-29, September 2015. Full text available. BibTeX

	author = {Vijaya B. Ghule and and Amol B. Jagadale},
	title = {Article: A Vertical Edge Detection Algorithm for Car License Plate Detection},
	journal = {IJCA Proceedings on Emerging Applications of Electronics System, Signal Processing and Computing Technologies},
	year = {2015},
	volume = {NCESC 2015},
	number = {1},
	pages = {26-29},
	month = {September},
	note = {Full text available}


Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Edge detection is one of the most critical tasks in automatic image analysis. There exists no universal edge detection method which works well under all conditions. This paper shows the new approach based on the one of the most efficient techniques for edge detection, which has advantages of its robustness and its flexibility. Edge detection is a very important process for many image processing applications, especially in Car License Plate Detection and Recognition Systems (CLPDRS). The need to distinguish the desired details is a very important pre-process in order to give good results in short time processing. We proposed a new and fast Vertical Edge Detection Algorithm (VEDA) which is based on the contrast between the gray scale values. After binarizing the input image using adaptive thresholding (AT), an unwanted-line elimination algorithm (ULEA) is proposed to enhance the image, and then, the VEDA is applied. The results revealed accurate edge detection performance and demonstrated the great efficiency of using VEDA in order to highlight license plate details.


  • R. C. Hardie and C. G. Boncelet, "Gradient-Based Edge Detection Using Nonlinear Edge Enhancing Prefilters," IEEE Trans. Image Process. , vol. 4, pp. 1572-1577, 1995.
  • L. S. Davis, "A Survey of Edge Detection Techniques," J. Computer Graphics Image Processing, vol. 4, pp. 248-270, 1975.
  • J. K. Aggarwal, R. O. Duda, and Rosenfeld, Computer Methods in Image Analysis. New York: (IEEE Press), 1977.
  • H. Bai, J. Zhu, and C. Liu, "A Fast License Plate Extraction Method on Complex Background," in Proc. IEEE Int. Conf. Intelligent Transportation Systems, China, October 2003, pp. 985-987.
  • H. Bai and C. Liu, "A Hybrid License Plate Extraction Method based on Edge Statistics and Morphology," in Proc. 17th Int. Conf. Pattern Recognition, IEEE Computer Society, CA, August 2004, pp. 831-834.
  • M. Yu and Y. D. Kim, "An Approach to Korean License Plate Recognition based on Vertical Edge Matching," in Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, USA, October 2000, pp. 2975- 2980.
  • W. Jia, H. Zhang, and Xiangjian, "Region-based License Plate Detection," J. Network and Computer Applications, vol. 30, pp. 1324- 1333, 2007.
  • S. Thanongsak and C. Kosin, "The Recognition of Car License Plate for Automatic Parking System," in Proc. 5th Int. Symp. Signal Processing and Its Applications, Australia, August 1999, pp. 455-457.
  • D. Zheng, Y. Zhao, and J. Wang, "An Efficient Method of License Plate Location," Pattern Recognition Lett. , vol. 26, pp. 2431-2438, 2005.
  • S. Thanongsak and C. Kosin, "Extracting of Car License Plate Using Motor Vehicle Regulation and Character Pattern Recognition," in Proc. IEEE Asia-Pacific Conf. Circuit and Systems, November 1998, pp. 559- 562.
  • K. Jung, K. I. Kim, and A. K. Jain, "Text information extraction in images and video: a survey," J. Pattern Recognition, vol. 37, pp. 977 – 997, 2004.
  • D. Chen, J. -M. Odobez, and H. Bourlard, "Text detection and recognition in images and video frames," J. Pattern Recognition, vol. 37, pp. 595-608, 2004.
  • D. Bradley and G. Roth, "Adaptive thresholding using the integral image," J. Graphics Tools, vol. 12, pp. 13–21, 2007.
  • F. Shafait, D. Keysers, and T. M. Breuel. (2008, February 8th). "Efficient Implementation of Local Adaptive Thresholding Techniques using Integral Images,"
  • H. -H. P. Wu, H. -H. Chen, R. -J. Wu, and D. -F. Shen, "License plate extraction in low resolution video," in Proc. IEEE 18th Int. Conf. Pattern Recognit. , Hong Kong, 2006, pp. 824–827.
  • N. A. Jusoh, J. M. Zain, and T. A. A. Kadir, "Enhancing Thinning Method for Malaysian Car Plates Recognition," in Proc. 2nd IEEE Int. Conf. Innovative Computing, Information, and Control, Japan,September 2007, pp. 378-378.
  • H. Zhang, W. Jia, X. He, and Q. Wu, "A fast algorithm for license plate detection in various conditions," in Proc. IEEE Int. Conf. Syst. , Man, Cybern. , Taipei, Taiwan, 2006, pp. 2420–2425.
  • J. Matas and K. Zimmermann, "Unconstrained license plate and text localization and recognition," in Proc. IEEE Int. Conf. Intell. Transp. Syst. , Vienna,Austria, 2005, pp. 572–577.
  • S. -L. Chang, L. -S. Chen, Y. -C. Chung, and S. -W. Chen, "Automatic license plate recognition," IEEE Trans. Intell. Transp. Syst. , vol. 5, no. 1, pp. 42–53, Mar. 2004.