Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Segmentation and Recognition of Korean Vehicle License Plate Characters Based on the Global Threshold Method and the Cross-Correlation Matching Algorithm

  • Sarker, Md. Mostafa Kamal (Dept. of Electronic Convergence Engineering, Wonkwang University) ;
  • Song, Moon Kyou (Dept. of Electronic Convergence Engineering, Wonkwang University)
  • Received : 2015.05.19
  • Accepted : 2015.09.30
  • Published : 2016.12.31
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Abstract

The vehicle license plate recognition (VLPR) system analyzes and monitors the speed of vehicles, theft of vehicles, the violation of traffic rules, illegal parking, etc., on the motorway. The VLPR consists of three major parts: license plate detection (LPD), license plate character segmentation (LPCS), and license plate character recognition (LPCR). This paper presents an efficient method for the LPCS and LPCR of Korean vehicle license plates (LPs). LP tilt adjustment is a very important process in LPCS. Radon transformation is used to correct the tilt adjustment of LP. The global threshold segmentation method is used for segmented LP characters from two different types of Korean LPs, which are a single row LP (SRLP) and double row LP (DRLP). The cross-correlation matching method is used for LPCR. Our experimental results show that the proposed methods for LPCS and LPCR can be easily implemented, and they achieved 99.35% and 99.85% segmentation and recognition accuracy rates, respectively for Korean LPs.

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References

  1. M. M. K. Sarker and M. K. Song, "Real-time vehicle license plate detection based on background subtraction and cascade of boosted classifiers," Journal of Korea Information and Communications Society, vol. 39C, no. 10, pp. 909-919, 2014. https://doi.org/10.7840/kics.2014.39C.10.909
  2. A. M. Al-Ghaili, S. Mashohor, A. R. Ramli, and A. Ismail, "Vertical edge based car license plate detection method," IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 26-38, 2013. https://doi.org/10.1109/TVT.2012.2222454
  3. S. Dey, A. Choudhury, and J. Mukherjee, "An efficient technique to locate number plate using morphological edge detection and character matching algorithm," International Journal of Computer Applications, vol. 101, no. 15, pp. 36-41, 2014. https://doi.org/10.5120/17766-8883
  4. J. Pang, "Variance window based car license plate localization," Journal of Computer and Communications, vol. 2, no. 9, pp. 61-69, 2014.
  5. D. Kim and L. Zheng, "Car license plate detection based on line segments," in Proceedings of Advanced Science and Technology Letters, Jeju, Korea, 2014, pp. 99-103.
  6. A. H. Ashtari, M. J. Nordin, and M. Fathy, "An Iranian license plate recognition system based on color features," IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 4, pp. 1690-1705, 2014. https://doi.org/10.1109/TITS.2014.2304515
  7. J. Olivares, J. M. Palomares, J. M. Soto, and J. C. Gamez, "License plate detection based on genetic neural networks, morphology, and active contours," in Proceedings of the 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, Cordoba, Spain, 2010, pp. 301-310.
  8. J. M. Guo, Y. F. Liu, and C. H. Hsia, "Multiple license plates recognition system," in Proceedings of the International Conference on System Science and Engineering (ICSSE), Dalian, China, 2012, pp. 120-125.
  9. P. S. Rani and V. Prasad, "License plate character segmentation based on pixel distribution density," International Journal of Engineering Science & Advanced Technology, vol. 2, no. 5, pp. 1539-1542, 2012.
  10. K. Romic, I. Galic, and A. Baumgartner, "Character recognition based on region pixel concentration for license plate identification," Technical Gazette, vol. 19, no. 2, pp. 321-325, 2012.
  11. Y. Yoon, K. Ban, H. Yoon, J. Lee, and J. Kim, "Best combination of binarization methods for license plate character segmentation," ETRI Journal, vol. 35, no. 3, pp. 491-500, 2013. https://doi.org/10.4218/etrij.13.0112.0545
  12. P. Gupta, G. N. Purohit, and M. Rathore, "Number plate extraction using template matching technique," International Journal of Computer Application, vol. 88, no. 3, pp. 40-44, 2014. https://doi.org/10.5120/15336-3670
  13. V. H. Mai, D. Q. Miao, R. Wang, and H. Zhang, "An improved method for Vietnam license plate location, segmentation and recognition," in Proceedings of the 2011 International Conference on Computational and Information Sciences (ICCIS), Chengdu, China, 2011, pp. 212-215.
  14. Z. H. Dong and X. Feng, "Research on license plate recognition algorithm based on support vector machine," Journal of Multimedia, vol. 9, no. 2, pp. 253-260, 2014.
  15. G. Yang, "License plate character recognition based on wavelet kernel LS-SVM," in Proceedings of the 2011 3rd International Conference on Computer Research and Development (ICCRD), Shanghai, China, 2011, pp. 222-226.
  16. M. S. Pan, Q. Xiong, and J. B. Yan, "A new method for correcting vehicle license plate tilt," International Journal of Automation and Computing, vol. 6, no. 2, pp. 210-216, 2009. https://doi.org/10.1007/s11633-009-0210-8
  17. V. H. Mai, D. Q. Miao, and R. Z. Wang, "Research on characters segmentation in one-row and two-row of Vietnam license plates," Advanced Materials Research, vol. 479-481, pp. 2293-2296, 2012. https://doi.org/10.4028/www.scientific.net/AMR.479-481.2293
  18. E. J. Kirkland, "Bilinear interpolation," in Advanced Computing in Electron Microscopy. New York: Springer, 2010, pp. 261-263.
  19. R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision. New York: McGraw-Hill, 1995, pp. 120-121.
  20. J. P. Tarel and N. Hautiere, "Fast visibility restoration from a single color or gray level image," in Proceedings of the IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, 2009, pp. 2201-2208.
  21. N. Hautiere, J. P. Tarel, J. Lavenant, and D. Aubert, "Automatic fog detection and estimation of visibility distance through use of an onboard camera," Machine Vision and Applications, vol. 17, no. 1, pp. 8-20, 2006. https://doi.org/10.1007/s00138-005-0011-1
  22. T. K. H. Nguyen, B. Cecile, and V. P. Tuan, "Performance and evaluation Sobel edge detection on various methodologies," International Journal of Electronics and Electrical Engineering, vol. 2, no. 1, pp. 15-20, 2014.
  23. N. Patel, A. Shah, M. Mistry, and K. Dangarwala, "A study of digital image filtering techniques in spatial image processing," in Proceedings of the 2014 International Conference on Convergence of Technology (I2CT), Pune, India, 2014, pp. 1-6.
  24. N. Otsu, "A threshold selection method from gray-level histogram," IEEE Transactions on Systems, Man and Cybernetics. vol. 9, no. 1, pp. 62-66, 1979. https://doi.org/10.1109/TSMC.1979.4310076
  25. C. H. Bindu and K. S. Prasad, "An efficient medical image segmentation using conventional Otsu method," International Journal of Advanced Science and Technology, vol. 38, pp. 67-73, 2012.
  26. M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine Vision, 3rd ed. Toronto: Thomson Learning, 2008, pp. 658-666.
  27. L. G. Shapiro and G. C. Stockman, Computer Vision. Upper Saddle River, NJ: Prentice-Hall, 2001, pp. 63-64.
  28. S. H. M. Kasaei and S. M. M. Kasaei, "Extraction and recognition of the vehicle license plate for passing under outside environment," in Proceedings of the 2011 European Intelligence and Security Informatics Conference (EISIC), Athens, Greece, 2011, pp. 234-237.
  29. S. Qiao, Y. Zhu, X. Li, T. Liu, and B. Zhang, "Research of improving the accuracy of license plate character segmentation," in Proceedings of the 5th International Conference on Frontier of Computer Science and Technology (FCST), Changchun, China, 2010, pp. 489-493.
  30. M. M. K. Sarker and M. K. Song, "A novel license plate character segmentation method for different types of vehicle license plates," in Proceedings of the 2014 International Conference on Information and Communication Technology Convergence (ICTC), Busan, Korea, 2014, pp. 84-88.
  31. M. M. K. Sarker and M. K. Song, "Korean car license plate character recognition using local line binary pattern," in Proceedings of the Winter 2015 General Conference on Korea Information and Communications Society, Gangwon, Korea, 2015, pp. 112-114.

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