The License Plate Recognition System Based on Fuzzy Theory and BP Neural Network

L. Li, Feng Guangli
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引用次数: 9

Abstract

In different conditions such as light and complex backgrounds, we get some car images, the traditional methods are slow convergence speed and low accuracy. This paper presents a method which applies fuzzy theory to enhance several features of for target. To obtain the license information, we use an improved BP neural network algorithm, by through setting proper numbers of hidden layer of BP network, we can solve the recognition problems of China's automobile license such as characters kinds, the numbers, and confusing. This method can improve the accuracy and efficiency of car license recognition, and enhance the system robustness.
基于模糊理论和BP神经网络的车牌识别系统
在光照和复杂背景等不同条件下,我们得到了一些汽车图像,传统的方法收敛速度慢,精度低。本文提出了一种应用模糊理论增强目标若干特征的方法。为了获取驾照信息,我们采用改进的BP神经网络算法,通过设置BP网络隐藏层的适当数量,可以解决中国驾照字符种类、数字、混淆等识别问题。该方法提高了车牌识别的准确性和效率,增强了系统的鲁棒性。
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