基于混合神经网络的车牌字符识别技术

License Plate Character Recognition Technology Based on Hybrid Neural Network

车牌识别是智能交通系统的重要组成部分,其关键是车牌字符识别技术。单一的神经网络难以识别模糊的车牌字符,文中提出了一种混合神经网络实现车牌字符识别技术。该混合神经网络结合联想记忆与BP神经网络,对输入的字符进行两次判别,经过训练、特征提取得到检测结果。通过在不同的噪声和不同的角度实验表明,采用混合神经网络具有更高的识别精度。

License plate recognition was an important part of the intelligent transportation system, and the key was the license plate character recognition technology. A single neural network was difficult to identify fuzzy license plate characters, and a hybrid neural network was proposed to realize license plate character recognition technology. The hybrid neural network combined associative memory with BP neural network to discriminate the input characters twice. After training and feature extraction, the detection results were obtained. Experiments with different noises and different angles showed that the hybrid neural network had higher recognition accuracy.