Design and Implementation of Automatic License Plate Recognition System for Security Gates

Document Type : Original Article

Authors

1 Assistant professor, Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran.

2 MSc, Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran.

3 Associated professor, Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran.

4 Assistant professor, Department of Mechanical Engineering, Technical and Vocational University (TVU), Tehran, Iran.

Abstract

In recent years, intelligent control of entry/exit points particularly based on image processing extracted from surveillance cameras, has been developed. The information obtained from such systems is important for monitoring the traffic and passage of vehicles. It can play an effective role in maintaining public safety and obtaining traffic statistics such as counting traffic at the gates of cities, statistical estimation of clients to organizations, and detecting and tracking suspicious traffic. Vehicles that enter a busy organization are identified at the time of entry and exit and a traffic log including the vehicle image with the license plate number and the date and time of entry and exit are recorded. In this research, a new method for extracting the license plate area is presented. The proposed method uses a combination of Canny vertical edge detection method and examination of connected components to identify candidate areas for the license plate. Experiment results in real conditions (images were taken from surveillance cameras in the organization supporting this research) showed that the proposed method can identify the license plate area of different vehicles in different lighting conditions with accuracy and readability of more than 98% and presents better performance than other state of the art methods.

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References

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Karafan Quarterly Scientific Journal
Volume 18, Issue 3 - Serial Number 55
Engineering
October 2021
Pages 237-252

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History

  • Receive Date: 04 January 2021
  • Revise Date: 12 April 2021
  • Accept Date: 09 May 2021

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