Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
권호 표지
DOI QR코드

DOI QR Code

An image enhancement-based License plate detection method for Naturally Degraded Images

  • Khan, Khurram (Dept. of Electronics and Communication Engineering, Hanyang University) ;
  • Choi, Myung Ryul (Dept. of Electronics and Communication Engineering, Hanyang University)
  • Received : 2018.12.17
  • Accepted : 2018.12.25
  • Published : 2018.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes an image enhancement-based license plate detection algorithm to improve the overall performance of system. Non-uniform illumination conditions have huge impact on overall plate detection system accuracy. In this paper, we propose an algorithm for color image enhancement-based license plate detection for improving accuracy of images degraded by excessively strong and low sunlight. Firstly, the image is enhanced by Multi-Scale Retinex algorithm. Secondly, a plate detection method is employed to take advantage of geometric properties of connected components, which can significantly reduce the undesired plate regions. Finally, intersection over union method is applied for detecting the accurate location of number plate. Experimental results show that the proposed method significantly improves the accuracy of plate detection system.

Keywords

JGGJB@_2018_v22n4_1188_f0001.png 이미지

Fig. 1 overall system architecture.

JGGJB@_2018_v22n4_1188_f0002.png 이미지

Fig. 2. Flowchart of enhancement algorithm.

JGGJB@_2018_v22n4_1188_f0003.png 이미지

Fig. 3. Flowchart of plate detection method.

JGGJB@_2018_v22n4_1188_f0004.png 이미지

Fig. 4. Outputs of Plate detection system (a) Original Images (b) Enhanced images (c) Detected plate.

Table 2. Comparison with conventional Methods.

JGGJB@_2018_v22n4_1188_t0001.png 이미지

Table. 3 Detection Accuracy

JGGJB@_2018_v22n4_1188_t0002.png 이미지

Table 1. Enhancement algorithm.

JGGJB@_2018_v22n4_1188_t0003.png 이미지

References

  1. Z. Mahmood, M. Khan, M. Jawad, S. Khan, and L. Yang, "A parallel framework for object detection and recognition for secure vehicle parking," 17th Int. Conf. on High Performance Computing and Communications, New York,. 2015. DOI:10.1109/HPCC-CSS-ICESS.2015.18
  2. B. Han, J. Lee, K. Lim, Y. Chung, "Real Time License Plate Detection in High Resolution Videos Using Fastest Available Cascade Classifier and Core Patterns," ETRI Journal, Vol.37, No.2, pp.251-261, 2015. DOI:https://doi.org/10.4218/etrij.15.2314.0077
  3. C. Anagnostopoulos, I. Anagnostopolous, I. Psoroulas, V. Loumos, and E. Kayafas, "License plate recognition from still images and video sequences: A survey," IEEE Trans. Intell. Trans. Syst., Vol.9, No.3, pp.377-391, 2008. DOI:10.1109/TITS.2008.922938
  4. Y. Wu, S. Liu and X. Wang., "License Plate Location Method Based on Texture and Color," in Proc. of IEEE Int. Conf. on Software Engineering and Service Science, pp.361-364, 2013. DOI:10.1109/ICSESS.2013.6615324
  5. H-H. Kim, J-K. park, J-H. Oh, and D-J. Kang, "Multi-task convolutional neural network system for license plate recognition," Int. Journal of Control, Automation and Systems, Vol.15, No.6, pp.2942-2949, 2017. DOI:10.1007/s12555-016-0332-z
  6. K. Robert, "Video-based traffic monitoring at day and night vehicle features detection tracking," Proc. of 12th Int. IEEE Conf. on Intelligent Transportation Systems, pp.1-6, 2009. DOI:10.1109/ITSC.2009.5309837
  7. J. Nijhuis, M. Brugge, K. Helmholt, J. Pluim, L. Spaanenburg, R. Venema, and M. Wassenberg, "Car license plate recognition with neural networks and fuzzy logic," Proc. of IEEE Int. Conf Neural Networks, Vol.5, pp.2232-2236, 1995. DOI:10.1109/ICNN.1995.487708
  8. S. Chen, and A. Ramli, "Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation," IEEE Trans. on Consumer Electronics, Vol.49, No.4, pp.1301-1309, 2003. DOI:10.1109/TCE.2003.1261233
  9. X. Dong, Y. Pang, and J. Wen, "Fast efficient algorithm for enhancement of low lighting video," ACM SIGGRAPH 2010 Posters, p.69. ACM, 2010. DOI:ieeecomputersociety.org/
  10. C. Wang and Y. Zhongfu, "Brightness preserving histogram equalization with maximum entropy: a variational perspective," IEEE Trans. on Consumer Electronics, Vol.51, No.4, pp.1326-1334, 2005. DOI:10.1109/TCE.2005.1561863
  11. H. Land, J. Edwin, J. McCann, "Lightness and Retinex Theory," Journal of the Optical Society of America, Vol.61, pp.1-11, 1971. https://doi.org/10.1364/JOSA.61.000001
  12. D. Jobson, Z. Rahman, and G. Woodell, "Properties and performance of a Center/Surround Retinex," IEEE Trans. Image Processing, Vol.6, No.3, 1997.
  13. D. Jobson, Z. Rahman, and G. Woodell, "A Multi-Scale Retinex for Bridging the Gap Between Color Images and the Human Observation of Scenes," IEEE Trans. on Image Proc., Vol.6, No.7, 1997. DOI:10.1109/83.597272
  14. H. Abdi and L. Williams, "Principal component analysis," Computational statistics, Vol.2, No.4, pp.433-459, 2010. https://doi.org/10.1002/wics.101
  15. Y. Yuan, W. Zou, Y. Zhao, X. Wang, X. Hu, and N. Komodakis, "A robust and efficient approach to license plate detection," IEEE Trans. on Image Process., Vol.26, No.3, pp.1102-1114, 2017. DOI:10.1109/TIP.2016.2631901
  16. Z. Mahmood, T. Ali, S. Khattak, M. Aslam, H. Mehmood, "A color image enhancement technique using multiscale retinex," Proc. of 11th Int. Conf. on Frontiers of Information Tech., pp.119-124, 2013. DOI:10.1109/FIT.2013.29
  17. D. Ghimire and J. Lee, "Nonlinear transfer function-based local approach for color image enhancement," IEEE Trans. on Consumer Electronics, Vol.57, No.2, pp.858-865, 2011. DOI:10.1109/TCE.2011.5955233
  18. Z. Rahman, D. J. Jobson, and G. A. Woodell, "A Multiscale Retinex for Color Rendition and Dynamic Range Compression," SPIE International Symposium on Optical Science, Engineering and Instrumentation, Applications of Digital Image Processing XIX, Proceedings SPIE 2825, Andrew G. Tescher, ed., 1996. DOI:10.1117/12.258224