Paper Title :Simulation Learning Algorithm Applied to Yolov4 License Plate Image Recognition in Rainfall Scenes
Author :Jia-Chyi Wu, Jinhong Lee
Article Citation :Jia-Chyi Wu ,Jinhong Lee ,
(2023 ) " Simulation Learning Algorithm Applied to Yolov4 License Plate Image Recognition in Rainfall Scenes " ,
International Journal of Advances in Science, Engineering and Technology(IJASEAT) ,
pp. 64-70,
Volume-11,Issue-3
Abstract : Incorporating add-on algorithm to enhance license plate recognition over rainfall scenes and to discuss the system
effectiveness analysis, this proposed approach has been applied the convolutional neural network YOLOv4 object detection
system to train license plate data sets in different situations. The training processes are conducted in different states and
evaluated on different combined datasets: the Application Oriented License Plate(AOLP) dataset whose real images are used
for benchmark tasks, and a generated dataset with synthetic images recreating a variety of lighting and rainfall conditions.
For license plate and character training and recognition, we have prepared four kinds of data sets, which are the original
license plate image from AOLP, and the simulated rainfall factor interference to the original license plate image for training.
The experimental recognition results show that the license plate detection and recognition rate is better in the rainy scene
where the overall character recognition reached 84.5%, effectively improving the recognition ability in the rainfall
conditions.
Keywords - Deep Learning, Convolutional Neural Network, Yolov4, License Plate Recognition
Type : Research paper
Published : Volume-11,Issue-3
DOIONLINE NO - IJASEAT-IRAJ-DOIONLINE-20269
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Copyright: © Institute of Research and Journals
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Published on 2023-12-18 |
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