摘要
车牌识别系统是智能交通中的一个重要分支,本文针对传统的模板匹配算法存在识别准确率低的问题,提出了一种基于神经网络的车牌字符识别算法。该方法对分割、归一化后的字符进行特征提取获取其特征向量,把这个特征向量送到BP网络中进行训练,可以得到训练好的权值,以此权值对车牌字符进行识别。实验表明,本算法对车牌图像的识别率达90%以上。
License plate recognition system is an important branch in the intelligent transportation.This paper presents a license plate character recognition algorithm based on neural network, the traditional template matching method has low recognition accuracy problem.First extracted the character image features to obtain its feature vector,then put the feature vector to BP network train and get trained weights,which weights the license plate character recognition.The experiments results showed that the recognition accuracy of number and alphabet is above 90%.
出处
《软件工程师》
2015年第1期19-20,共2页
Software Engineer
基金
咸阳师范学院国家级大学生创新创业训练项目
项目编号:201310722002
咸阳师范学院省级大学生创新创业训练项目
项目编号:1801
咸阳师范学院校级大学生创新创业训练项目
项目编号:XSYCX2013005
关键词
字符识别
BP神经网络
车牌识别
character recognition
BP neural network
license plate recognition
