Number Plate Detection Using YOLOV4 and Tesseract OCR

Authors

  • G. Poorani
  • B.R. Krithick Krishnna
  • T. Raahul
  • P. Praveen Kumar

DOI:

https://doi.org/10.47750/pnr.2022.13.S03.021

Keywords:

Recognition, Accuracy, Detection General Terms - Automatic License Plate Recognition (ALPR), Tesseract-OCR, Image Processing, Yolov4.

Abstract

The number of on-road vehicles is quickly expanding in present day times. The larger part of the time, it is vital to affirm the character of these cars in arrange to authorize the travel control and oversee stopping carports. Physically assessing a gigantic number of moving automobiles is troublesome. As a result, creating a precise programmed permit plate acknowledgment show that incorporates character acknowledgment is basic to reduce the previously mentioned concerns. We've made a demonstrate based on an assortment of permit plates from other nations. Yolov4, which utilizes CNN structures, was utilized to prepare the picture dataset. After various picture pre-processing procedures and morphological changes, character acknowledgment was performed utilizing the Tesseract OCR. In terms of permit plate discovery, the proposed framework includes a 92 % precision rate and 81% in character acknowledgment.

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Published

2022-09-22

Issue

Section

Articles

How to Cite

Number Plate Detection Using YOLOV4 and Tesseract OCR. (2022). Journal of Pharmaceutical Negative Results, 130-136. https://doi.org/10.47750/pnr.2022.13.S03.021