2 BP神经网络车牌识别.zip

使用BP神经网络算法来进行文字识别，可以抛出周边环境进行识别车牌信息，利用MATLAB来进行实现

function bp（）
%use for bp training
I0=pretreatment（imread（‘A.jpg‘））;
I1=pretreatment（imread（‘B.jpg‘））;
I2=pretreatment（imread（‘C.jpg‘））;
I3=pretreatment（imread（‘D.jpg‘））;
I4=pretreatment（imread（‘E.jpg‘））;
I5=pretreatment（imread（‘F.jpg‘））;
I6=pretreatment（imread（‘G.jpg‘））;
I7=pretreatment（imread（‘H.jpg‘））;
I8=pretreatment（imread（‘I.jpg‘））;
I9=pretreatment（imread（‘J.jpg‘））;
I10=pretreatment（imread（‘K.jpg‘））;
I11=pretreatment（imread（‘L.jpg‘））;
I12=pretreatment（imread（‘M.jpg‘））;
I13=pretreatment（imread（‘N.jpg‘））;
I14=pretreatment（imread（‘O.jpg‘））;
I15=pretreatment（imread（‘P.jpg‘））;
I16=pretreatment（imread（‘Q.jpg‘））;
I17=pretreatment（imread（‘R.jpg‘））;
I18=pretreatment（imread（‘S.jpg‘））;
I19=pretreatment（imread（‘T.jpg‘））;
I20=pretreatment（imread（‘U.jpg‘））;
I21=pretreatment（imread（‘V.jpg‘））;
I22=pretreatment（imread（‘W.jpg‘））;
I23=pretreatment（imread（‘X.jpg‘））;
I24=pretreatment（imread（‘Y.jpg‘））;
I25=pretreatment（imread（‘Z.jpg‘））;
P=[I0‘I1‘I2‘I3‘I4‘I5‘I6‘I7‘I8‘I9‘I10‘I11‘I12‘I13‘I14‘I15‘I16‘I17‘I18‘I19‘I20‘I21‘I22‘I23‘I24‘I25‘];
%输出样本%
T=eye（2626）;
%%bp神经网络参数设置
net=newff（minmax（P）[8002326]{‘logsig‘‘logsig‘‘logsig‘}‘trainrp‘）;
net.inputWeights{11}.initFcn =‘randnr‘;
net.layerWeights{21}.initFcn =‘randnr‘;
net.trainparam.epochs=5000;
net.trainparam.show=50;
net.trainparam.goal=0.0000000001;
net=init（net）;
%%%训练样本%%%%
[nettr]=train（netPT）;
save（‘ym‘‘net‘）;

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     文件      221760  2012-11-29 16:35  2  BP神经网络车牌识别\1.png
     文件         967  2018-05-02 22:17  2  BP神经网络车牌识别\A.jpg
     文件        1461  2012-12-07 22:06  2  BP神经网络车牌识别\bp.m
     文件        7493  2018-05-02 21:57  2  BP神经网络车牌识别\chepai.m
     文件        4674  2018-05-02 22:10  2  BP神经网络车牌识别\dw.jpg
     文件         493  2018-05-02 21:39  2  BP神经网络车牌识别\pretreatment.m
     文件    13733302  2012-12-07 21:50  2  BP神经网络车牌识别\ym.mat
     目录           0  2018-05-08 22:16  2  BP神经网络车牌识别\