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A Robust Real-Time License Plate Recognition System Using Anchor-Free Method and Convolutional Neural Network

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2022, 27(4), pp.19-26
  • DOI : 10.9708/jksci.2022.27.04.019
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 28, 2022
  • Accepted : March 23, 2022
  • Published : April 29, 2022

Dae-Hoon Kim 1 Do-Hyeon Kim 2 Dong-Hoon Lee 2 Yoon Kim 1

1강원대학교
2지오비전

Accredited

ABSTRACT

With the recent development of intelligent transportation systems, car license plate recognition systems are being used in various fields. Such systems need to guarantee real-time performance to recognize the license plate of a driving car. Also, they should keep a high recognition rate even in problematic situations such as small license plates in low-resolution and unclear image due to distortion. In this paper, we propose a real-time car license plate recognition system that improved processing speed using object detection algorithm based on anchor-free method and text recognition algorithm based on Convolutional Neural Network(CNN). In addition, we used Spatial Transformer Network to increase the recognition rate on the low resolution or distorted images. We confirm that the proposed system is faster than previously existing car license plate recognition systems and maintains a high recognition rate in a variety of environment and quality images because the proposed system’s recognition rate is 93.769% and the processing speed per image is about 0.006 seconds.

Citation status

* References for papers published after 2022 are currently being built.