一种改进的神经网络车牌识别算法研究  

Research on an improved neural network license plate recognition algorithm

作　　者：司朋举 胡伟[1] Si Pengju Hu Wei(School of Electric and Engineering, Henan Polytechnic University JiaoZuo,454003,Chin)

机构地区：[1]河南理工大学电气工程与自动化学院,焦作454003

出　　处：《电子测量技术》2016年第10期100-103,共4页Electronic Measurement Technology

基　　金：河南省重点科技攻关项目(102102210197);河南省高等学校矿山信息化重点学科开放实验室开放基金;河南理工大学博士基金(B2010-23)项目资助

摘　　要：根据实际应用要求,要求使车牌实时识别系统识别准确率高,提出了一种改进的神经网络车牌识别算法,基于标准的神经网络的识别算法上进行了改进,在标准神经网络算法中增加惯性冲量分批处理的方法进行改进,并通过训练大量样本进行了实验。实验结果表明,改进的神经网络识别算法与未改进的标准神经网络字符识别算法相比其识别率和处理速度有了很大的提高,已在小区停车场应用,达到了应用的要求,证明了改进后的神经网络车牌识别算法与标准神经网络算法相比在实时识别正确率上有了很大提高。According to the actual application requirements,the requirements of recognition of license plate recognition system with high accuracy,proposes an improved neural network license plate recognition algorithm based on neural network recognition algorithm on the standard was improved in the standard neural network algorithm in the method of increasing the inertia impulse batch processing is improved and tested by training a large number of samples,the experimental results show that the neural network recognition algorithm improved the recognition rate and processing speed is greatly improved compared with the standard neural network character recognition has not improved algorithm has been applied in residential parking lot,achieves the application requirements,and proves that compared the improved neural network license plate recognition algorithm and standard the neural network algorithm in the real-time recognition accuracy has been greatly improved.

关 键 词：车牌识别 神经网络 惯性冲量 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]