License plate detection using YOLO v4

https://doi.org/10.53730/ijhs.v6nS2.7475

Authors

  • Rishabh Rathi Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
  • Aditya Sharma Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
  • Nikesh Baghel Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
  • Prathamesh Channe Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
  • Shreyas Barve Student, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
  • Sweta Jain Assistant Professor, Shri Ramdeobaba College of Engineering and Management, Nagpur

Keywords:

convolutional neural network, object detection and recognition, YOLO, deep learning

Abstract

Automatic License Plate Recognition (ALPR) is a sizzling topic in the disciplines of intelligent transportation systems and image recognition. The real-time object detector YOLO (You Only Look Once) - darknet deep learning framework is used in this article to detect car number plates in parking lots in real time. The YOLOv4 deep learning technique was utilized in this proposed strategy to automatically recognize a car's number plate from a video stream. An OCR technique is applied to extract the number from the image of the number plate. The system detects license plates with an accuracy of around 89%.

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References

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Published

18-05-2022

How to Cite

Rathi, R., Sharma, A., Baghel, N., Channe, P., Barve, S., & Jain, S. (2022). License plate detection using YOLO v4. International Journal of Health Sciences, 6(S2), 9456–9462. https://doi.org/10.53730/ijhs.v6nS2.7475

Issue

Section

Peer Review Articles