License plate detection and recognition,as an important component of intelligent transportation management,are widely used in scenarios such as road supervision and parking lot management.To improve the accuracy of license plate recognition,this article constructs an efficient and fast license plate detection and recognition system.Combining YOLOv8 object detection model with LPRNet license plate recognition network to improve the accuracy and robustness of the model.The test results show that the system achieves an accuracy of 85%for license plate detection and character recognition,with an average inference speed of 40.30ms,demonstrating good effectiveness and efficiency.
关键词
深度学习/卷积神经网络/车牌识别/车牌检测
Key words
Deep Learning/Convolutional Neural Networks/License Plate Detection/License Plate Recognition
维普
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