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Novel License Plate Detection Method Based on Heuristic Energy

  • Sarker, Md.Mostafa Kamal (Division of Electronic and Information Eng., Chonbuk National University) ;
  • Yoon, Sook (Dept. of Multimedia Engineering, Mokpo National University) ;
  • Lee, Jaehwan (Division of Electronic and Information Eng., Chonbuk National University) ;
  • Park, Dong Sun (Division of Electronic and Information Eng., Chonbuk National University)
  • Received : 2013.06.26
  • Accepted : 2013.11.19
  • Published : 2013.12.31

Abstract

License Plate Detection (LPD) is a key component in automatic license plate recognition system. Despite the success of License Plate Recognition (LPR) methods in the past decades, the problem is quite a challenge due to the diversity of plate formats and multiform outdoor illumination conditions during image acquisition. This paper aims at automatical detection of car license plates via image processing techniques. In this paper, we proposed a real-time and robust method for license plate detection using Heuristic Energy Map(HEM). In the vehicle image, the region of license plate contains many components or edges. We obtain the edge energy values of an image by using the box filter and search for the license plate region with high energy values. Using this energy value information or Heuristic Energy Map(HEM), we can easily detect the license plate region from vehicle image with a very high possibilities. The proposed method consists two main steps: Region of Interest (ROI) Detection and License Plate Detection. This method has better performance in speed and accuracy than the most of existing methods used for license plate detection. The proposed method can detect a license plate within 130 milliseconds and its detection rate is 99.2% on a 3.10-GHz Intel Core i3-2100(with 4.00 GB of RAM) personal computer.

Keywords

References

  1. C. N. E. Anagnostopoulos, I. E. Anagnostopoulos, V. Loumos, and E. Kayafs, "A license plate-recognition algorithm for intelligent transportation system applications," IEEE Trans. Intell. Transp. Syst., vol. 7. no. 3, pp. 377-392, Sep. 2006.
  2. C. N. E. Anagnostopoulos, I. E. Anagnostopoulos, I. D. Psoroulas, V. Loumos, and E. Kayafas, "License plate recognition from still images and video sequences : a survey," IEEE Trans. Intell. Transp. Syst., vol. 9, no. 3, pp. 377-391, Sep. 2008. https://doi.org/10.1109/TITS.2008.922938
  3. B. Hongliang and L. Changping, "A hybrid license plate extraction method based on edge statistics and morphology," in Proc. 17th Int. Conf. Pattern Recognition (ICPR'04), vol. 2, pp. 831-834, Cambridge, U.K., Aug. 2004.
  4. D. Zheng, Y. Zhao, and J. Wang, "An efficient method of license plate location," Pattern Recogn. Lett., vol. 26, no. 15, pp. 2431-2438, Nov. 2005. https://doi.org/10.1016/j.patrec.2005.04.014
  5. P. V. Suryanarayana, S. K. Mitra, A. Banerjee, and A. K. Roy, "A morphology based approach for car license plate extraction," in Proc. Annu. IEEE INDICON 2005, pp. 24-27, Chennai, India, Dec. 2005.
  6. J. Cano and J.-C. Perez-Cortes, "Vehicle license plate segmentation in natural images," Lecture Notes Comput. Sci., vol. 2652. pp. 142-149, June 2003.
  7. L. Hsi-Jian, C. Si-Yuan, and W. Shen-Zheng, "Extraction and recognition of license plates of motorcycles and vehicles on highways," in Proc. 17th Int. Conf. Pattern Recognition (ICPR'04), vol. 4, pp. 356-359, Cambridge, U.K., Aug. 2004.
  8. K. Fatih, K. Binnur, and G. Muhittin, "License plate character segmentation based on the Gabor transform and vector quantization," Lecture Notes Comput. Sci., vol. 2869. pp. 381-388, Nov. 2003.
  9. L. Miao, F. Wang, and H. Wang, "Automatic license plate detection based on edge density and color model," in Proc. Annu. Conf. Chinese Control Decision Conf. (CCDC'09), pp. 3718-3721, Guilin, China, June 2009.
  10. K. Deb and K.-H. Jo, "HSI color based vehicle license plate detection," in Proc. Int. Conf. Control, Automation, Syst. (ICCAS 2008), pp. 687-691, Seoul, Korea, Oct. 2008.
  11. M. I. Chacon M and A. Zimmerman S, "License plate location based on a dynamic PCNN scheme," in Proc. Int. Joint Conf. Neural Networks, vol. 2, pp. 1195-1200, Portland, U.S.A., July 2003.
  12. K. K. Kim, K. I. Kim, J. B. Kim, and H. J. Kim, "Learning-based approach for license plate recognition," in Proc. 2000 IEEE Signal Process. Soc. Workshop Neural Networks Signal Process. X, vol. 2, pp. 614-623, Sydney, Australia, Dec. 2000.
  13. Y.-N. Chen, C.-C. Han, C.-T. Wang, B.-S. Jeng, and K.-C. Fan, "The application of a convolution neural network on face and license plate detection," in Proc. 18th Int. Conf. Pattern Recognition (ICPR 2006), pp. 552-555, Hong Kong, China, Aug. 2006.
  14. Y. Kang and C. Bae, "License plates detection using a Gaussian windows," J. Korea Inform. Commun. Soc. (KICS), vol. 37A, no. 9, pp. 780-785, Sep. 2012. https://doi.org/10.7840/kics.2012.37A.9.780
  15. M. Yu and Y. D. Kim, "An approach to Korean license plate recognition based on vertical edge matching," in Proc. 2000 IEEE Int. Conf. Syst., Man, Cybernetics, vol. 4, pp. 2975-2980, Nashville, U.S.A., Oct. 2000.
  16. M. J. McDonnell, "Box-filtering techniques," Computer Graphics Image Process., vol. 17, no. 1, pp. 65-70, Sep. 1981. https://doi.org/10.1016/S0146-664X(81)80009-3
  17. H. Samet and M. Tamminen, "Efficient component labeling of images of arbitrary dimension represented by linear bintrees," IEEE Trans. Pattern Anal. Mach. Intell., vol. 10, no. 4, pp. 579-586, July 1988. https://doi.org/10.1109/34.3918
  18. M. B. Dillencourt, H. Samet, and M. Tamminen, "A general approach to connected-component labeling for arbitrary image representations," J. ACM, vol. 39, no. 2, pp. 253-280, Apr. 1992. https://doi.org/10.1145/128749.128750
  19. W. Chen, M. L. Giger, and U. Bick, "A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR Images," Academic Radiology, vol. 13, no. 1, pp. 63-72, Jan. 2006. https://doi.org/10.1016/j.acra.2005.08.035
  20. K. Wu, W. Koegler, J. Chen, and A. Shoshani, "Using bitmap Index for interactive exploration of large datasets," in Proc. 15th Int. Conf. Sci. Stat. Database Manage., pp. 99-108, Cambridge, U.S.A., July 2003.
  21. K. Deb, H. Chae, and K. Jo, "Vehicle license plate detection method based on sliding concentric windows and histogram," J. Comput., vol. 4, no. 8, pp.771-777, Aug. 2009.
  22. M. Ashoori-Lalimi and S. Ghofrani, "An efficient method for vehicle license plate detection in complex scenes," Circuits Syst., vol. 2, no. 4, pp. 320-325, Oct. 2011. https://doi.org/10.4236/cs.2011.24044
  23. A. M. Al-Ghaili, S. Mashohor, A. R. Ramli, and A. Ismail, "Vertical edges-based car license plate detection method," IEEE Trans. Veh. Technol., vol. 62, no. 1, pp. 26-38, Oct. 2012.
  24. J.-M. Guo and Y.-F. Liu, "License plate localization and character segmentation with feedback self-learning and hybrid binarization techniques," IEEE Trans. Veh. Technol., vol. 57, no. 3, pp. 1417-1424, May 2008. https://doi.org/10.1109/TVT.2007.909284