基于MATLAB的车牌识别系统.zip

close all clc [fn,pn,fi]=uigetfile('ChePaiKu\*.jpg','选择图片'); YuanShi=imread([pn fn]);%输入原始图像 figure(1);subplot(3,2,1),imshow(YuanShi),title('原始图像'); %%%%%%%%%%1、图像预处理%%%%%%%%%%% YuanShiHuiDu=rgb2gray(YuanShi);%转化为灰度图像 subplot(3,2,2),imshow(YuanShiHuiDu),title('灰度图像'); BianYuan=edge(YuanShiHuiDu,'canny',0.5);%Canny算子边缘检测 subplot(3,2,3),imshow(BianYuan),title('Canny算子边缘检测后图像'); se1=[1;1;1]; %线型结构元素 FuShi=imerode(BianYuan,se1); %腐蚀图像 subplot(3,2,4),imshow(FuShi),title('腐蚀后边缘图像'); se2=strel('rectangle',[25,25]); %矩形结构元素 TianChong=imclose(FuShi,se2);%图像聚类、填充图像 subplot(3,2,5),imshow(TianChong),title('填充后图像'); YuanShiLvBo=bwareaopen(TianChong,2000);%从对象中移除面积小于2000的小对象 figure(2); subplot(2,2,1),imshow(YuanShiLvBo),title('形态滤波后图像'); %%%%%%%%%%2、车牌定位%%%%%%%%%%% [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); %%%%%%%%%%2.1、车牌粗定位之一确定行的起始位置和终止位置%%%%%%%%%%% Y1=zeros(y,1);%产生y行1列全零数组 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 end end [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 subplot(2,2,2),plot(0:y-1,Y1),title('原图行方向像素点值累计和'),xlabel('行值'),ylabel('像素'); PY1=MaxY; while ((Y1(PY1,1)>=50)&&(PY1>1)) PY1=PY1-1; end PY2=MaxY; while ((Y1(PY2,1)>=50)&&(PY2<y)) PY2=PY2+1; end IY=YuanShi(PY1:PY2,:,:); %%%%%%%%%%2.2、车牌粗定位之二确定列的起始位置和终止位置%%%%%%%%%%% 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 end end subplot(2,2,4),plot(0:x-1,X1),title('原图列方向像素点值累计和'),xlabel('列值'),ylabel('像数'); PX1=1; while ((X1(1,PX1)<3)&&(PX1<x)) PX1=PX1+1; end PX3=x; while ((X1(1,PX3)<3)&&(PX3>PX1)) PX3=PX3-1; end CuDingWei=YuanShi(PY1:PY2,PX1:PX3,:); subplot(2,2,3),imshow(CuDingWei),title('粗定位后的彩色车牌图像') %%%%%%%%%%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 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(3); subplot(2,2,1),imshow(CuDingWeiErZhi),title('粗定位的二值车牌图像')%DingWei %%%%%%%%%%2.4、车牌精定位之二去除边框干扰%%%%%%%%%%% [r,s]=size(CuDingWeiErZhi);%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 YuJingDingWei=double(CuDingWeiErZhi);%;CuDingWeiErZhi X2=zeros(1,s);%产生1行s列全零数组 for i=1:r for j=1:s if(YuJingDingWei(i,j)==1) X2(1,j)= X2(1,j)+1;%白色像素点统计 end end end [temp,MaxX]=max(X2); subplot(2,2,2),plot(0:s-1,X2),title('粗定位车牌图像列方向像素点值累计和'),xlabel('列值'),ylabel('像素'); %%%%%%%%%%2.4.1、去除左侧边框干扰%%%%%%%%%%% [g,h]=size(YuJingDingWei); ZuoKuanDu=0;YouKuanDu=0;KuanDuYuZhi=5; while sum(YuJingDingWei(:,ZuoKuanDu+1))~=0 ZuoKuanDu=ZuoKuanDu+1; end if ZuoKuanDu<KuanDuYuZhi % 认为是左侧干扰 YuJingDingWei(:,[1:ZuoKuanDu])=0;%给图像d中1到KuanDu宽度间的点赋值为零 YuJingDingWei=QieGe(YuJingDingWei); %值为零的点会被切割 end subplot(2,2,3),imshow(YuJingDingWei),title('去除左侧边框的二值车牌图像') %%%%%%%%%2.4.1、去除右侧边框干扰%%%%%%%%%%% [e,f]=size(YuJingDingWei);%上一步裁剪了一次，所以需要再次获取图像大小 d=f; while sum(YuJingDingWei(:,d-1))~=0 YouKuanDu=YouKuanDu+1; d=d-1; end if YouKuanDu<KuanDuYuZhi % 认为是右侧干扰 YuJingDingWei(:,[(f-YouKuanDu):f])=0;% YuJingDingWei=QieGe(YuJingDingWei); %值为零的点会被切割 end subplot(2,2,4),imshow(YuJingDingWei),title('精确定位的车牌二值图像') % % % %%%%%%%%%%2.5、保存车牌图像%%%%%%%%%%% % % % % imwrite(DingWei,'DingWei.jpg'); % % % % [filename,filepath]=uigetfile('DingWei.jpg','输入一个定位裁剪后的车牌图像'); % % % % jpg=strcat(filepath,filename); % % % % DingWei=imread('DingWei.jpg'); % % % %%%%%%%%%%3、车牌字符分割%%%%%%%%%%% % % % %%%%%%%%%%3.1、预处理%%%%%%%%%%% % % % figure(4); % % % % subplot(2,2,1),imshow(DingWei),title('车牌图像') % % % % ChePaiHuiDu=rgb2gray(DingWei); %将RGB图像转化为灰度图像 % % % % subplot(2,2,2),imshow(ChePaiHuiDu),title('车牌灰度图像') % % % % g_max=double(max(max(ChePaiHuiDu))); % % % % g_min=double(min(min(ChePaiHuiDu))); % % % % T=round(g_max-(g_max-g_min)/3); %T为二值化的阈值 % % % % [m,n]=size(ChePaiHuiDu); % % % % % ChePaiErZhi=(double(ChePaiHuiDu)>=T); %车牌二值图像 % % % % ChePaiErZhi=im2bw(ChePaiHuiDu,T/256); % % % % % im2bw:通过设定亮度将真彩等图像转换为二值图像，T/256为阈值，范围[0,1] % % % % subplot(2,2,3),imshow(ChePaiErZhi),title('车牌二值图像') ChePaiErZhi=YuJingDingWei;%logical() ChePaiLvBo=bwareaopen(ChePaiErZhi,20); subplot(1,2,1),imshow(ChePaiLvBo),title('形态学滤波后的车牌二值图像') ChePaiYuFenGe=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 end end subplot(1,2,2),plot(0:q-1,X3),title('列方向像素点灰度值累计和'),xlabel('列值'),ylabel('累计像素量'); %%%%%%%%%%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)<15)) Px1=Px1-1; end ChePaiFenGe=ChePaiLvBo(:,Px1:Px0,:); figure(6);subplot(1,7,8-i);imshow(ChePaiFenGe); ii=int2str(8-i); imwrite(ChePaiFenGe,strcat(ii,'.jpg'));%strcat连接字符串。保存字符图像。 Px0=Px1; end %%%%%%%%%%对第一个字符进行特别处理%%%%%%%%%%% PX3=Px1;%字符1右侧限 while((X3(1,PX3)<3)&&(PX3>0)) PX3=PX3-1; end ZiFu1DingWei=ChePaiYuFenGe(:,1:PX3,:); subplot(1,7,1);imshow(ZiFu1DingWei); imwrite(ZiFu1DingWei,'1.jpg'); %%%%%%%%%%%4、车牌字符识别%%%%%%%%%%% %%%%%%%%%%%4.1、车牌字符预处理%%%%%%%%%%% ZiFu1=imresize(~imread('1.jpg'), [110 55],'bilinear');%用反色识别 ZiFu2=imresize(~imread('2.jpg'), [110 55],'bilinear'); ZiFu3=imresize(~imread('3.jpg'), [110 55],'bilinear'); ZiFu4=imresize(~imread('4.jpg'), [110 55],'bilinear'); ZiFu5=imresize(~imread('5.jpg'), [110 55],'bilinear'); ZiFu6=imresize(~imread('6.jpg'), [110 55],'bilinear'); ZiFu7=imresize(~imread('7.jpg'), [110 55],'bilinear'); %%%%%%%%%%%4.2、把0-9,A-Z以及省份简称的数据存储方便访问%%%%%%%%%%% HanZi=DuQuHanZi(imread('MuBanKu\sichuan.bmp'),imread('MuBanKu\guizhou.bmp'),imread('MuBanKu\beijing.bmp'),imread('MuBanKu\chongqing.bmp'),... imread('MuBanKu\guangdong.bmp'),imread('MuBanKu\shandong.bmp'),imread('MuBanKu\zhejiang.bmp')); ShuZiZiMu=DuQuSZZM(imread('MuBanKu\0.bmp'),imread('MuBanKu\1.bmp'),imread('MuBanKu\2.bmp'),imread('MuBanKu\3.bmp'),imread('MuBanKu\4.bmp'),... imread('MuBanKu\5.bmp'),imread('MuBanKu\6.bmp'),imread('MuBanKu\7.bmp'),imread('MuBanKu\8.bmp'),imread('MuBanKu\9.bmp'),... imread('MuBanKu\10.bmp'),imread('MuBanKu\11.bmp'),imread('MuBanKu\12.bmp'),imread('MuBanKu\13.bmp'),imread('MuBanKu\14.bmp'),... imread('MuBanKu\15.bmp'),imread('MuBanKu\16.bmp'),imread('MuBanKu\17.bmp'),imread('MuBanKu\18.bmp'),imread('MuBanKu\19.bmp'),... imread('MuBanKu\20.bmp'),imread('MuBanKu\21.bmp'),imread('MuBanKu\22.bmp'),imread('MuBanKu\23.bmp'),imread('MuBanKu\24.bmp'),... imread('MuBanKu\25.bmp'),imread('MuBanKu\26.bmp'),imread('MuBanKu\27.bmp'),imread('MuBanKu\28.bmp'),imread('MuBanKu\29.bmp'),... imread('MuBanKu\30.bmp'),imread('MuBanKu\31.bmp'),imread('MuBanKu\32.bmp'),imread('MuBanKu\33.bmp')); 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