Skip to main content
SpringerLink
Log in

Vehicle License Plate Detection Using Image Segmentation and Morphological Image Processing

  • Conference paper
  • First Online:
Advances in Signal Processing and Intelligent Recognition Systems (SIRS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 678))

Abstract

This paper presents an image segmentation technique to segment out the Region of Interest (ROI) from an image, in this study, the ROI is the vehicle license plate. In order to successfully detect the license plate an improvised Sliding Concentric Window (SCW) algorithm has been developed to perform the segmentation process. In this proposed model, vehicle images were obtained and the SCW algorithm has been performed to segment out the ROI and then Morphological Image Processing techniques named erosion and dilation have been used to locate the license plate. In order to validate our proposed model, we have used a dataset where the images of the vehicles have been taken from a different angle that contains natural background and different lighting conditions. It has been observed that the proposed model exhibits 86.5% accuracy rate for our tested dataset. In addition to that, a comparative study has been carried out between two different techniques (Improved SCW and Modified Bernsen Algorithm) of ROI detection to illustrate their accuracy rate. It has been found that the accuracy rate of the proposed model of VLP detection is higher than some other traditional algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tian, B., Yao, Q., Gu, Y., Wang, K., Li, Y.: Video processing techniques for traffic flow monitoring: a survey. In: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1103–1108 (2011)

    Google Scholar 

  2. Barcellos, P., Bouvie, C., Escouto, F.L., Scharcanski, J.: A novel video based system for detecting and counting vehicles at user-defined virtual loops. Expert Syst. Appl. 42, 1845–1856 (2015)

    Article  Google Scholar 

  3. Tan, X.-J., JunLiu, C.: A video-based real-time vehicle detection method by classified background learning. World Trans. Eng. Technol. Edu. 6, 189 (2007)

    Google Scholar 

  4. Anagnostopoulos, C., Anagnostopoulos, I., Tsekouras, G., Kouzas, G., Loumos, V., Kayafas, E.: Using sliding concentric windows for license plate segmentation and processing. In: IEEE Workshop on Signal Processing Systems Design and Implementation, pp. 337–342, November 2005

    Google Scholar 

  5. Anagnostopoulos, C., Anagnostopoulos, I., Loumos, V., Kayafas, E.: A license plate-recognition algorithm for intelligent transportation system applications. IEEE Trans. Intell. Transp. Syst. 7(3), 377–392 (2006)

    Article  Google Scholar 

  6. Sonka, M., Vaclav H., Boyle, R.D.: Mathematical morphology. Image processing, analysis, and machine vision. In: International Student edn. Thompson Learning, Toronto, pp. 657–664 (2008)

    Google Scholar 

  7. Kamat, V., Ganesan, S.: An efficient implementation of the hough transform for detecting vehicle license plates using DSP’s. In: Proceedings of Real Time Technology and Applications, Chicago, 15-17 May 1995, pp. 58–59 (1995)

    Google Scholar 

  8. Yanamura, Y., Goto, M., Nishiyama, D.: Extraction and tracking of the license plate using hough transform and voted block matching. IEEE proceedings of Intelligent Vehicles Symposium, Columbus, 9-11 June 2003, pp. 243–246 (2003)

    Google Scholar 

  9. Martín, F., García, M., Alba, L.: New methods for automatic reading of VLP’s (Vehicle License Plates). In: Proceeding of IASTED International Conference SPPRA, June 2002

    Google Scholar 

  10. Hongliangand, B., Changping, L.: A hybrid license plate extraction method based on edge statistics and morphology. In: Proceeding of ICPR, pp. 831–834 (2004)

    Google Scholar 

  11. Zheng, D., Zhao, Y., Wang, J.: An efficient method of license plate location. Pattern Recognit. Lett. 26(15), 2431–2438 (2005)

    Article  Google Scholar 

  12. Lee, H.-J., Chen, S.-Y., Wang, S.-Z.: Extraction and recognition of license plates of motorcycles and vehicles on highways. In: Proceeding of ICPR, pp. 356–359 (2004)

    Google Scholar 

  13. Shi, X., Zhao, W., Shen, Y.: Automatic license plate recognition system based on color image processing. In: Gervasi, O., et al. (eds.) Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3483, pp. 1159–1168. Springer, New York(2005)

    Google Scholar 

  14. Yan, D., Hongqing, M., Jilin, L., Langang, L.: A high performance license plate recognition system based on the web technique. In: Proceeding of Conference Intelligent Transportation Systems, pp. 325–329 (2001)

    Google Scholar 

  15. Zimic, N.,. Ficzko, J., Mraz, M., Virant, J.: The fuzzy logic approach to the car numberplate locating problem. In: Proceeding IIS, pp. 227–230 (1997)

    Google Scholar 

  16. Chang, S.-L., Chen, L.-S., Chung, Y.-C., Chen, S.-W.: Automatic license plate recognition. IEEE Trans. Intell. Transp. Syst. 5(1), 42–53 (2004)

    Article  Google Scholar 

  17. Latha, M.G., Chakravarthy, G.: An improved Bernsen algorithm approaches for license plate recognition. IOSR-JECE: IOSR J. Electron. Commun. Eng. 3(4), 01–05 (2012)

    Google Scholar 

  18. Wang, T.-H., Ni, F.-C., Li, K.-T., Chen, Y.-P.: Robust license plate recognition based on dynamic projection warping. In: Proceeding IEEE International Conference Networking, Sensing and Control, pp. 784–788 (2004)

    Google Scholar 

  19. Rong, Z., Yong, W.: Application of improved median filter on image processing. J. Comput. 7(4), 838–841 (2012)

    Google Scholar 

  20. Sauvola, J., Pietikäinen, M.: Adaptive document image binarization. Pattern Recogn. 33, 225–236 (2000)

    Article  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge BRAC University, Bangladesh to provide their facilities and Dr Md. Moinul Hossain for the useful discussions. A very special acknowledgement is also made to the referees who make important comments to improve this paper.

Author information

Authors and Affiliations

  1. BRAC University, 66 Bir Uttam AK Khandakar Road, Dhaka, 1212, Bangladesh

    Wasif Shafaet Chowdhury, Ashikur Rashid Khan & Jia Uddin

Authors
  1. Wasif Shafaet Chowdhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ashikur Rashid Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jia Uddin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wasif Shafaet Chowdhury .

Editor information

Editors and Affiliations

  1. School of CS/IT, Indian Institute of Information Technology and Management, Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada

    Sri Krishnan

  3. Department of Computer Science, University of Salamanca, Salamanca, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  5. Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland

    Michal Wozniak

  6. Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, United Kingdom

    Dhiya Al-Jumeily

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Chowdhury, W.S., Khan, A.R., Uddin, J. (2018). Vehicle License Plate Detection Using Image Segmentation and Morphological Image Processing. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67934-1_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67933-4

  • Online ISBN: 978-3-319-67934-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation