A Novel Approach for Automatic Car Plate Detection and Recognition

Authors

  • Fattah Alizadeh Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewlêr, Erbil, Kurdistan Region, Iraq http://orcid.org/0000-0002-0690-1147
  • Sazan Luqman Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewlêr, Erbil, Kurdistan Region, Iraq

DOI:

https://doi.org/10.25079/ukhjse.v5n2y2021.pp1-9

Keywords:

Automatic Car Plate Recognition, SURF Descriptor, Segmentation, Character Recognition, Digit Recognition, Horizontal Projection, Vertical Projection

Abstract

The increasing number of cars inside cities creates problems in traffic control. This issue can be solved by implementing a computer-based automatic system known as the Automatic Car Plate Recognition System (ACPRS). The main purpose of the current paper is to propose an automatic system to detect, extract, segment, and recognize the car plate numbers in the Kurdistan Region of Iraq (KRI). To do so, a frontal image of cars is captured and used as an input of the system. After applying the required pre-processing steps, the SURF descriptor is utilized to detect and extract the car plate from the whole input image. After segmentation of the extracted plate, an efficient projection-based technique is being exploited to describe the available digits and the city name of the registered car plate. The system is evaluated over 200 sample images, which are taken under various testing conditions. The best accuracy of the proposed system, under the controlled condition, shows the high performance and accuracy of the system which is 94%.

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Author Biographies

  • Fattah Alizadeh, Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewlêr, Erbil, Kurdistan Region, Iraq

    Fattah Alizadeh is Assistant Professor in Computer Science at the School of Science and Engineering, University Kurdistan Hawler (Kurdistan region, Iraq). He holds PhD degree in Computer Image Processing from the university of Dublin City University (Ireland), a Master-Degree in Computer Software Engineering from Iran University of Science and Technology, Tehran (Iran) and a Bachelor of Science from Shiraz University, Shiraz (Iran) in Computer System Engineering. Before joining UKH, Fattah has worked as a lecturer at the School of Computing, Mahabad Azad University, Iran, for 7 years from 2004 to 2010. Then he joined Dublin City University as a PhD research student from 2010 to 2014. He also worked for one year as a Teaching Assistance in Dublin City University, Ireland. His research area is mainly related to Image Processing, Machine Vision, Bioinformatics and Biomedical Image Analysis.

  • Sazan Luqman, Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewlêr, Erbil, Kurdistan Region, Iraq

    Sazan Luqman: Obtained both BSc and MSc at the Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewlêr, Erbil, Kurdistan Region, Iraq.

References

Abbas, E. I., & Hashim, T. A. (2016). Iraqi Cars License Plate Detection and Recognition System using Edge Detection and Template Matching Correlation. Engineering and Technology Journal, 34(2 Part (A) Engineering), 257-271.
Albiol, A., Sanchis, L., Albiol, A., & Mossi, J. M. (2011). Detection of parked vehicles using spatiotemporal maps. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1277-1291.
Alginahi, Y. M. (2011). Automatic arabic license plate recognition. International Journal of Computer and Electrical Engineering, 3(3), 454-460.
Ali, A. M., Shareef, S. M., & Rashid, T. A. (2015). Automatic License Plate Recognition in Kurdistan Region of Iraq (KRI). Journal of Zankoi Sulaimani, Part-A-(Pure and Applied Sciences), 17, 235-244.
Amatya, M. L., & Sarvanan, K. N. (2017). The state of the art–Vehicle Number Plate Identification–a complete Survey. International Research Journal of Engineering and Technology (IRJET), 4(2), 785-792. Retrieved from https://www.irjet.net/archives/V4/i2/IRJET-V4I2153.pdf
Awaidah, S. M., & Mahmoud, S. A. (2009). A multiple feature/resolution scheme to Arabic (Indian) numerals recognition using hidden Markov models. Signal Processing, 89(6), 1176-1184.
Bay, H., Tuytelaars, T., & Van Gool, L. (2006, May). Surf: Speeded up robust features. In European conference on computer vision (pp. 404-417), Berlin, Heidelberg.
Davies, P., Emmott, N., & Ayland, N. (1990, February). License plate recognition technology for toll violation enforcement. In IEE Colloquium on Image Analysis for Transport Applications (pp. 7-1). IET. London, UK. Retrieved from https://ieeexplore.ieee.org/document/191012
Draghici, S. (1997). A neural network based artificial vision system for licence plate recognition. International Journal of Neural Systems, 8(01), 113-126.
Ebrahimi, A., Amirkhani, A., A Raie, A., & Mosavi, M. R. (2015). Car license plate recognition using color features of Persian license plates. Journal of Advances in Computer Research, 6(4), 27-38.
He, L., Ren, X., Gao, Q., Zhao, X., Yao, B., & Chao, Y. (2017). The connected-component labeling problem: A review of state-of-the-art algorithms. Pattern Recognition, 70, 25-43.
Lotufo, R. A., Morgan, A. D., & Johnson, A. S. (1990, February). Automatic number-plate recognition. In IEE Colloquium on Image Analysis for Transport Applications (pp. 6-1). IET. London, UK. Retrieved from https://ieeexplore.ieee.org/document/191011
Massoud, M. A., Sabee, M., Gergais, M., & Bakhit, R. (2013). Automated new license plate recognition in Egypt. Alexandria Engineering Journal, 52(3), 319-326.
Patel, C., Shah, D., & Patel, A. (2013). Automatic number plate recognition system (anpr): A survey. International Journal of Computer Applications, 69(9), 21-33.
Wady, S. H., Ahmad, F. H., & Ahmed, H. O. (2017), Iraqi Kurdistan Vehicle License Plate Recognition System based on Client-server Network. Journal of Zankoi Sulaimani, 19 – 1 (Part-A), 251-262. doi: https://doi.org/10.17656/jzs.10603

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Published

2021-12-28

Issue

Vol. 5 No. 2 (2021): ISSUE 9

Section

Research Articles

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How to Cite

A Novel Approach for Automatic Car Plate Detection and Recognition. (2021). UKH Journal of Science and Engineering, 5(2), 1-9. https://doi.org/10.25079/ukhjse.v5n2y2021.pp1-9

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