MATLAB车牌识别程序与实现仿真

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MATLAB车牌识别程序的实现可以包括以下步骤：1. 车牌区域检测：通过图像处理技术，将图像中的车牌区域提取出来。可以使用图像分割、颜色检测等方法。2. 车牌字符分割：将车牌图像中的字符进行分割，得到单个字符图像。可以使用字符间距、字符形状等特征进行分割。3. 字符识别：对每个字符图像进行识别，得到字符的类别。可以使用机器学习算法，如支持向量机、卷积神经网络等进行训练和预测。4. 字符串拼接与识别结果输出：将识别出的字符进行字符串拼接，得到完整的车牌号码，并输出识别结果。需要注意的是，车牌识别是一个复杂的问题，需要综合运用图像处理、特征提取与选择、机器学习等多种技术。在MATLAB中，可以使用图像处理工具箱、机器学习工具箱等进行实现。关于仿真，可以使用MATLAB提供的仿真工具进行车牌识别算法的评估与调试。可以通过输入不同的车牌图像，观察算法在不同情况下的性能表现，评估识别的准确率、召回率等指标。同时，也可以进行算法的优化与调参，以提高算法的准确性和鲁棒性。总结起来，MATLAB车牌识别程序可以通过以下步骤实现：车牌区域检测、字符分割、字符识别和结果输出。仿

%%%打开图像clc[filename, pathname]=uigetfile('*.jpg', 'File Selector');I=imread([pathname '\' filename]);%括号括起来就是把这个看成一个路径handles.I=I;figure(1)imshow(I);title('原图');%%灰度，腐蚀YuanShi=handles.I;YuanShiHuiDu=rgb2gray(YuanShi);%转化为灰度图像figure(2)imshow(YuanShiHuiDu);title('灰度图')BianYuan=edge(YuanShiHuiDu,'canny',0.2);%Canny算子边缘检测%BianYuan=edge(YuanShiHuiDu,'roberts',0.2,'both');figure(3)imshow(BianYuan);title('边缘')handles.BianYuan=BianYuan;%%%%腐蚀BianYuan=handles.BianYuanse1=[1;1;1]; %线型结构元素FuShi=imerode(BianYuan,se1); %腐蚀图像figure(4)imshow(FuShi);title('腐蚀')handles.FuShi=FuShi;mainfc;se2=strel('rectangle',[25,25]); %矩形结构元素TianChong=imclose(FuShi,se2);%图像聚类、填充图像YuanShiLvBo=bwareaopen(TianChong,2000);%从对象中移除面积小于2000的小对象figure(5)imshow(YuanShiLvBo);title('去除干扰')handles.YuanShiLvBo=YuanShiLvBo%%%%%%定位YuanShiLvBo=handles.YuanShiLvBo[y,x]=size(YuanShiLvBo);%size函数将数组的行数返回到第一个输出变量，将数组的列数返回到第二个输出变量YuCuDingWei=double(YuanShiLvBo);%%%%%%%%%2.确定行的起始位置和终止位置%%%%%%%%%%%Y1=zeros(y,1);%产生y行全零数组for i=1:y for j=1:x if(YuCuDingWei(i,j)==1) Y1(i,1)= Y1(i,1)+1;%白色像素点统计 end endend[temp,MaxY]=max(Y1);%Y方向车牌区域确定。返回行向量temp和MaxY，temp向量记录Y1的每列的最大值，MaxY向量记录Y1每列最大值的行号PY1=MaxY;while ((Y1(PY1,1)>=50)&&(PY1>1))%从最高点开始向两侧找边界 PY1=PY1-1;endPY2=MaxY;while ((Y1(PY2,1)>=50)&&(PY2<y)) PY2=PY2+1;endYuanShi=handles.IIY=YuanShi(PY1:PY2,:,:);%%%%%%%%%%车牌粗定位之二确定列的起始位置和终止位置%%%%%%%%%%%%%%%%%%%%%和列分割不同这个是从两边向中间找%%%%%%%%%%%%%%X1=zeros(1,x);%产生1行x列全零数组for j=1:x for i=PY1:PY2 if(YuCuDingWei(i,j,1)==1) X1(1,j)= X1(1,j)+1; end endendPX1=1;while ((X1(1,PX1)<3)&&(PX1<x)) PX1=PX1+1;endPX3=x;while ((X1(1,PX3)<3)&&(PX3>PX1)) PX3=PX3-1;endCuDingWei=YuanShi(PY1:PY2,PX1+10:PX3-10,:);%待定figure(6)imshow(CuDingWei);title('定位图')%%%%%%%%%%2.3、车牌精定位之一预处理%%%%%%%%%%%CuDingWeiHuiDu=rgb2gray(CuDingWei); %将RGB图像转化为灰度图像figure(7)imshow(CuDingWeiHuiDu);title('车牌灰度图')c_max=double(max(max(CuDingWeiHuiDu)));c_min=double(min(min(CuDingWeiHuiDu)));T=round(c_max-(c_max-c_min)/3); %T为二值化的阈值CuDingWeiErZhi=im2bw(CuDingWeiHuiDu,T/256);figure(8)imshow(CuDingWeiErZhi);title('车牌二值图')CuDingWeiErZhi=bwareaopen(CuDingWeiErZhi,20);CuDingWeiErZhi(: ,PX3)=0;CuDingWeiErZhi=bwareaopen(CuDingWeiErZhi,100);CuDingWeiErZhi=lvbo(CuDingWeiErZhi);handles.CuDingWeiErZhi=CuDingWeiErZhi%%%定位CuDingWeiErZhi=handles.CuDingWeiErZhiChePaiLvBo=CuDingWeiErZhi;%logical()BianYuan=handles.BianYuanChePaiYuFenGe=double(ChePaiLvBo);[p,q]=size(ChePaiYuFenGe);X3=zeros(1,q);%产生1行q列全零数组for j=1:q for i=1:p if(ChePaiYuFenGe(i,j)==1) X3(1,j)=X3(1,j)+1; end endend%%%%%%%%%%3.2、字符分割%%%%%%%%%%%p高q宽，倒序分割Px0=q;%字符右侧限Px1=q;%字符左侧限for i=1:6 while((X3(1,Px0)<3)&&(Px0>0)) Px0=Px0-1; end Px1=Px0; while( ( (X3(1,Px1) >=3) ) && (Px1>0) || ((Px0-Px1)<25) )%要求一个字符大于15个像素 Px1=Px1-1; end ChePaiFenGe=ChePaiLvBo(:,Px1:Px0,:);%得到一个第一个字符（右侧） ii=int2str(8-i);%命名 imwrite(ChePaiFenGe,strcat(ii,'.jpg'));%strcat连接字符串。保存字符图像。 Px0=Px1;endPX3=Px1;%字符1右侧限while((X3(1,PX3)<3)&&(PX3>0)) PX3=PX3-1;endZiFu1DingWei=ChePaiYuFenGe(:,1:PX3,:);%subplot(1,7,1);imshow(ZiFu1DingWei);imwrite(ZiFu1DingWei,'1.jpg');%%%%%%%%%%%%%%读取分割完成的字符%%%%%%%%%%%%%%%%%%%%%%%%ZiFu1=imresize(im2bw(imread('1.jpg'),graythresh(imread('1.jpg'))), [40 20],'bilinear');ZiFu2=imresize(im2bw(imread('2.jpg'),graythresh(imread('2.jpg'))), [40 20],'bilinear');ZiFu3=imresize(im2bw(imread('3.jpg'),graythresh(imread('3.jpg'))), [40 20],'bilinear');ZiFu4=imresize(im2bw(imread('4.jpg'),graythresh(imread('4.jpg'))), [40 20],'bilinear');ZiFu5=imresize(im2bw(imread('5.jpg'),graythresh(imread('5.jpg'))), [40 20],'bilinear');ZiFu6=imresize(im2bw(imread('6.jpg'),graythresh(imread('6.jpg'))), [40 20],'bilinear');ZiFu7=imresize(im2bw(imread('7.jpg'),graythresh(imread('7.jpg'))), [40 20],'bilinear');figure(9)subplot(171)imshow(ZiFu1);subplot(172)imshow(ZiFu2);subplot(173)imshow(ZiFu3);subplot(174)imshow(ZiFu4);subplot(175)imshow(ZiFu5);subplot(176);imshow(ZiFu6);subplot(177);imshow(ZiFu7);handles.ZiFu1=ZiFu1handles.ZiFu2=ZiFu2handles.ZiFu3=ZiFu3handles.ZiFu4=ZiFu4handles.ZiFu5=ZiFu5handles.ZiFu6=ZiFu6handles.ZiFu7=ZiFu7%%%%%%%识别ZiFu1=handles.ZiFu1ZiFu2=handles.ZiFu2ZiFu3=handles.ZiFu3ZiFu4=handles.ZiFu4ZiFu5=handles.ZiFu5ZiFu6=handles.ZiFu6ZiFu7=handles.ZiFu7%%%%%%%%%%%把0-9,A-Z以及省份简称的数据存储方便访问%%%%%%%%%%%HanZi=ReadCharacter(imread('Chinesecharacter\藏.jpg'),imread('Chinesecharacter\川.jpg'),imread('Chinesecharacter\鄂.jpg'),... imread('Chinesecharacter\贵.jpg'),imread('Chinesecharacter\黑.jpg'), imread('Chinesecharacter\吉.jpg'),... imread('Chinesecharacter\冀.jpg'),imread('Chinesecharacter\津.jpg'),imread('Chinesecharacter\晋.jpg'),... imread('Chinesecharacter\京.jpg'),imread('Chinesecharacter\辽.jpg'),imread('Chinesecharacter\鲁.jpg'),... imread('Chinesecharacter\闽.jpg'),imread('Chinesecharacter\琼.jpg'),imread('Chinesecharacter\陕.jpg'),... imread('Chinesecharacter\苏.jpg'),imread('Chinesecharacter\皖.jpg'),imread('Chinesecharacter\湘.jpg'),... imread('Chinesecharacter\豫.jpg'),imread('Chinesecharacter\粤.jpg'),imread('Chinesecharacter\云.jpg'),... imread('Chinesecharacter\浙.jpg'));ShuZiZiMu=ReadStringNumber(imread('E and N character\0.jpg'),imread('E and N character\1.jpg'),imread('E and N character\2.jpg'),... imread('E and N character\3.jpg'),imread('E and N character\4.jpg'),imread('E and N character\5.jpg'),... imread('E and N character\6.jpg'),imread('E and N character\7.jpg'),imread('E and N character\8.jpg'),... imread('E and N character\9.jpg'),imread('E and N character\A.jpg'),imread('E and N character\B.jpg'),... imread('E and N character\C.jpg'),imread('E and N character\D.jpg'),imread('E and N character\E.jpg'),... imread('E and N character\F.jpg'),imread('E and N character\G.jpg'),imread('E and N character\H.jpg'),... imread('E and N character\J.jpg'),imread('E and N character\K.jpg'),imread('E and N character\L.jpg'),... imread('E and N character\M.jpg'),imread('E and N character\N.jpg'),imread('E and N character\P.jpg'),... imread('E and N character\Q.jpg'),imread('E and N character\R.jpg'),imread('E and N character\S.jpg'),... imread('E and N character\T.jpg'),imread('E and N character\U.jpg'),imread('E and N character\V.jpg'),... imread('E and N character\W.jpg'),imread('E and N character\X.jpg'),imread('E and N character\Y.jpg'),... imread('E and N character\Z.jpg'));%%%%%%%%%%%4.3、车牌字符识别%%%%%%%%%%%%%%%%%%%%%%第一位一定为汉字，两个矩阵相减%%%%%%%%%%%store1=strcat('藏','川','鄂','贵','黑','吉','冀','津','京','晋','辽','鲁','闽','琼','陕','苏','皖','湘','豫','粤','云','浙'); %创建汉字识别模板库ShiBieJieGuo=[];for j=1:22 Im=ZiFu1; Template= HanZi(:,:,j); Differ=Im-Template; Compare(j)=sum(sum(abs(Differ)));endindex=find(Compare==(min(Compare)));index;ShiBieJieGuo=[ShiBieJieGuo store1(index)];store2=strcat('0','1','2','3','4','5','6','7','8','9','A','B','C','D','E','F','G','H','J','K','L','M','N','P','Q','R','S','T','U','V','W','X','Y','Z'); %创建字母与数字识别模板库for j=1:34 Im=ZiFu2; Template=ShuZiZiMu(:,:,j); Differ=Im-Template; Compare(j)=sum(sum(abs(Differ)));endindex=find(C