基于神经网络的车牌识别系统 matlab

适合零基础学习的代码。本设计完全基于matlab开发车牌识别系统，修复原代码中的BUG，适用于matlab2014a。图示车牌识别的各个过程，最后基于神经网络算法完成分类识别。

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        967  2015-05-13 10:27  A.jpg

     文件     221760  2012-11-29 16:35  1.png

     文件       1461  2012-12-07 22:06  bp.m

     文件       7220  2015-05-13 10:27  chepai.m

     文件        538  2015-05-12 16:34  pretreatment.m

     文件   13733302  2012-12-07 21:50  ym.mat

     文件       4674  2015-05-13 10:27  dw.jpg

----------- ---------  ---------- -----  ----

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