Research on License Plate Recognition Algorithm Based on ABCNet

Yanyang Liu, Jun Yan, Yanping Xiang
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引用次数: 2

Abstract

In order to improve the accuracy of license plate recognition algorithm, we propose a license plate recognition algorithm based on ABCNet. Firstly, the original images with ABCNet is to locate license plate detection network, secondly, use CRNN - CTC algorithm for license plate character recognition, character recognition algorithm is the main process of the convolution neural network is used to extract image convolution, the cycle of neural network is used to extract image convolution features of sequence, the CTC algorithm is used to solve the problem that training characters cannot be aligned, the license plate recognition's accuracy is 96.4%. With a speed of 9ms, it has a well effect and can play an important role in actual traffic management.
基于ABCNet的车牌识别算法研究
为了提高车牌识别算法的准确率,提出了一种基于ABCNet的车牌识别算法。首先,利用ABCNet对原始图像进行车牌定位检测网络,其次,利用CRNN - CTC算法进行车牌字符识别,字符识别算法的主要过程是卷积神经网络用于提取图像的卷积,循环神经网络用于提取图像的卷积特征序列,CTC算法用于解决训练字符不能对齐的问题;车牌识别准确率为96.4%。速度为9ms,效果良好,可以在实际交通管理中发挥重要作用。
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