Localization of car license plate using adaptive Euler-template matching method

Authors

  • Nay Zar Aung School of Industrial Training and Education, Department of Technical and Vocational Education and Training, Ministry of Science and Technology, Myanmar
  • Jinghui Peng Department of Fluid Control and Automation, Harbin Institute of Technology, China
  • Khin Cho Tun Department of Electronic Engineering, Yangon Technological University, Myanmar
  • Songjing Li Department of Fluid Control and Automation, Harbin Institute of Technology, China

DOI:

https://doi.org/10.58712/ie.v2i1.30

Keywords:

euler-template, adaptive template matching, license plate localizing, smart traffic control, automatic recognition system

Abstract

License plate (LP) detection plays an important role in intelligent transportation systems smart traffic control systems of today. Although it is simple and easy to implement for LP detection, traditional template matching method is less favorable compared to state-of-the-art methods due to its processing cost. Thus, this study proposes an innovative template matching method called “adaptive Euler-template matching method” for detection of LP. Two different models of Euler-template and a new matching concept are proposed. The proposed method is evaluated by detecting LP in a total of 150 test images. Then, the performance of proposed method is compared with the performances of some exiting methods. The proposed method gives accuracies of 96% using Euler-template(model-A) and 96.7% using Euler-template(model-B). The average processing time of proposed method is 0.303 s. The results show that Euler-template(model-B) is more effective for LP detection. More distinct observations are presented and finally recommendations for further works are given in this study.

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Published

2025-05-22

How to Cite

Aung, N. Z., Peng, J., Tun, K. C., & Li, S. (2025). Localization of car license plate using adaptive Euler-template matching method. Innovation in Engineering, 2(2), 91–105. https://doi.org/10.58712/ie.v2i1.30

Issue

Vol. 2 No. 2 (2025): Regular Issue

Section

Articles

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Copyright (c) 2025 Nay Zar Aung, Jinghui Peng, Khin Cho Tun, Songjing Li

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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