Devising a method for processing the image of a vehicle's license plate when shooting with a smartphone camera
DOI:
https://doi.org/10.15587/1729-4061.2022.252310Keywords:
image processing, license plate, vehicle, character recognition, smartphone cameraAbstract
This paper reports an improved method for processing the image of a vehicle's license plate when shooting with a smartphone camera. The method for processing the image of a vehicle's license plate includes the following stages:
– enter the source data;
– split the video streaming into frames;
– preliminary process the image of a vehicle's license plate;
– find the area of a vehicle's license plate;
– refine character recognition using the signature of a vehicle's license plate;
– refine character recognition using the combined results from frames in the streaming video;
– obtain the result of processing.
Experimental studies were conducted on the processing of images of a vehicle's license plate. During the experimental studies, the license plate of a military vehicle (Ukraine) was considered. The original image was the color image of a vehicle. The results of experimental studies are given. A comparison of the quality of character recognition in a license plate has been carried out. It was established that the improved method that uses the combined results from streaming video frames works out efficiently at the end of the sequence. The improved method that employs the combined results from streaming video frames operates with numerical probability vectors.
The assessment of errors of the first and second kind in processing the image of a license plate was carried out. The total accuracy of finding the area of a license plate by known method is 61 % while the improved method's result is 76 %. It has been established that the minimization of errors of the first kind is more important than reducing errors of the second kind. If a license plate is incorrectly identified, these results would certainly be discarded at the character recognition stage.
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Copyright (c) 2022 Hennadii Khudov, Oleksandr Makoveichuk, Dmytro Misiuk, Hennadii Pievtsov, Irina Khizhnyak, Yuriy Solomonenko, Iryna Yuzova, Volodymyr Cherneha, Valerii Vlasiuk, Vladyslav Khudov
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