车牌识别matlab 源码+字符模板 -

function [d]=main(jpg)
close all
clc
I=imread('car1.jpg');
figure(1),imshow(I);title('原图')
I1=rgb2gray(I);
figure(2),subplot(1,2,1),imshow(I1);title('灰度图');
figure(2),subplot(1,2,2),imhist(I1);title('灰度图直方图');
I2=edge(I1,'roberts',0.15,'both');
figure(3),imshow(I2);title('robert算子边缘检测')
se=[1;1;1];
I3=imerode(I2,se);
figure(4),imshow(I3);title('腐蚀后图像');
se=strel('rectangle',[25,25]);
I4=imclose(I3,se);
figure(5),imshow(I4);title('平滑图像的轮廓');
I5=bwareaopen(I4,2000);
figure(6),imshow(I5);title('从对象中移除小对象');
[y,x,z]=size(I5);
myI=double(I5);
tic
Blue_y=zeros(y,1);
for i=1:y
for j=1:x
if(myI(i,j,1)==1)
Blue_y(i,1)= Blue_y(i,1)+1;%蓝色像素点统计
end
end
end
[temp MaxY]=max(Blue_y);%Y方向车牌区域确定
PY1=MaxY;
while ((Blue_y(PY1,1)>=5)&&(PY1>1))
PY1=PY1-1;
end
PY2=MaxY;
while ((Blue_y(PY2,1)>=5)&&(PY2<y))
PY2=PY2+1;
end
IY=I(PY1:PY2,:,:);
%%%%%% X方向 %%%%%%%%%
Blue_x=zeros(1,x);%进一步确定x方向的车牌区域
for j=1:x
for i=PY1:PY2
if(myI(i,j,1)==1)
Blue_x(1,j)= Blue_x(1,j)+1;
end
end
end
PX1=1;
while ((Blue_x(1,PX1)<3)&&(PX1<x))
PX1=PX1+1;
end
PX2=x;
while ((Blue_x(1,PX2)<3)&&(PX2>PX1))
PX2=PX2-1;
end
PX1=PX1-1;%对车牌区域的校正
PX2=PX2+1;
dw=I(PY1:PY2-8,PX1:PX2,:);
t=toc;
figure(7),subplot(1,2,1),imshow(IY),title('行方向合理区域');
figure(7),subplot(1,2,2),imshow(dw),title('定位剪切后的彩色车牌图像')
imwrite(dw,'dw.jpg');
[filename,filepath]=uigetfile('dw.jpg','输入一个定位裁剪后的车牌图像');
jpg=strcat(filepath,filename);
a=imread('dw.jpg');
b=rgb2gray(a);
imwrite(b,'1.车牌灰度图像.jpg');
figure(8);subplot(3,2,1),imshow(b),title('1.车牌灰度图像')
g_max=double(max(max(b)));
g_min=double(min(min(b)));
T=round(g_max-(g_max-g_min)/3); % T 为二值化的阈值
[m,n]=size(b);
d=(double(b)>=T); % d:二值图像
imwrite(d,'2.车牌二值图像.jpg');
figure(8);subplot(3,2,2),imshow(d),title('2.车牌二值图像')
figure(8),subplot(3,2,3),imshow(d),title('3.均值滤波前')
% 滤波
h=fspecial('average',3);
d=im2bw(round(filter2(h,d)));
imwrite(d,'4.均值滤波后.jpg');
figure(8),subplot(3,2,4),imshow(d),title('4.均值滤波后')
% 某些图像进行操作
% 膨胀或腐蚀
% se=strel('square',3); % 使用一个3X3的正方形结果元素对象对创建的图像进行膨胀
% 'line'/'diamond'/'ball'...
se=eye(2); % eye(n) returns the n-by-n identity matrix 单位矩阵
[m,n]=size(d);
if bwarea(d)/m/n>=0.365
d=imerode(d,se);
elseif bwarea(d)/m/n<=0.235
d=imdilate(d,se);
end
imwrite(d,'5.膨胀或腐蚀处理后.jpg');
figure(8),subplot(3,2,5),imshow(d),title('5.膨胀或腐蚀处理后')
% 寻找连续有文字的块，若长度大于某阈值，则认为该块有两个字符组成，需要分割
d=qiege(d);
[m,n]=size(d);
figure,subplot(2,1,1),imshow(d),title(n)
k1=1;k2=1;s=sum(d);j=1;
while j~=n
while s(j)==0
j=j+1;
end
k1=j;
while s(j)~=0 && j<=n-1
j=j+1;
end
k2=j-1;
if k2-k1>=round(n/6.5)
[val,num]=min(sum(d(:,[k1+5:k2-5])));
d(:,k1+num+5)=0; % 分割
end
end
% 再切割
d=qiege(d);
% 切割出 7 个字符
y1=10;y2=0.25;flag=0;word1=[];
while flag==0
[m,n]=size(d);
left=1;wide=0;
while sum(d(:,wide+1))~=0
wide=wide+1;
end
if wide<y1 % 认为是左侧干扰
d(:,[1:wide])=0;
d=qiege(d);
else
temp=qiege(imcrop(d,[1 1 wide m]));
[m,n]=size(temp);
all=sum(sum(temp));
two_thirds=sum(sum(temp([round(m/3):2*round(m/3)],:)));
if two_thirds/all>y2
flag=1;word1=temp; % WORD 1
end
d(:,[1:wide])=0;d=qiege(d);
end
end
% 分割出第二个字符
[word2,d]=getword(d);
% 分割出第三个字符
[word3,d]=getword(d);
% 分割出第四个字符
[word4,d]=getword(d);
% 分割出第五个字符
[word5,d]=getword(d);
% 分割出第六个字符
[word6,d]=getword(d);
% 分割出第七个字符
[word7,d]=getword(d);
subplot(5,7,1),imshow(word1),title('1');
subplot(5,7,2),imshow(word2),title('2');
subplot(5,7,3),imshow(word3),title('3');
subplot(5,7,4),imshow(word4),title('4');
subplot(5,7,5),imshow(word5),title('5');
subplot(5,7,6),imshow(word6),title('6');
subplot(5,7,7),imshow(word7),title('7');
[m,n]=size(word1);
% 商用系统程序中归一化大小为 40*20,此处演示
word1=imresize(word1,[40 20]);
word2=imresize(word2,[40 20]);
word3=imresize(word3,[40 20]);
word4=imresize(word4,[40 20]);
word5=imresize(word5,[40 20]);
word6=imresize(word6,[40 20]);
word7=imresize(word7,[40 20]);
subplot(5,7,15),imshow(word1),title('1');
subplot(5,7,16),imshow(word2),title('2');
subplot(5,7,17),imshow(word3),title('3');
subplot(5,7,18),imshow(word4),title('4');
subplot(5,7,19),imshow(word5),title('5');
subplot(5,7,20),imshow(word6),title('6');
subplot(5,7,21),imshow(word7),title('7');
imwrite(word1,'1.jpg');
imwrite(word2,'2.jpg');
imwrite(word3,'3.jpg');
imwrite(word4,'4.jpg');
imwrite(word5,'5.jpg');
imwrite(word6,'6.jpg');
imwrite(word7,'7.jpg');
liccode=char(['0':'9' 'A':'Z' '苏豫陕鲁京辽浙']); %建立自动识别字符代码表
SubBw2=zeros(40,20);
l=1;
for I=1:7
ii=int2str(I);
t=imread([ii,'.jpg']);
SegBw2=imresize(t,[40 20],'nearest');
if l==1 %第一位汉字识别
kmin=37;
kmax=43;
elseif l==2 %第二位 A~Z 字母识别
kmin=11;
kmax=36;
else l>=3 %第三位以后是字母或数字识别
kmin=1;
kmax=36;
end
for k2=kmin:kmax
fname=strcat('F:\edge 下载\车牌识别3 第二版\车牌识别\程序与图像\字符模板\',liccode(k2),'.jpg');
SamBw2 = imread(fname);
for i=1:40
for j=1:20
SubBw2(i,j)=SegBw2(i,j)-SamBw2(i,j);
end
end
% 以上相当于两幅图相减得到第三幅图
Dmax=0;
for k1=1:40
for l1=1:20
if ( SubBw2(k1,l1) > 0 | SubBw2(k1,l1) <0 )
Dmax=Dmax+1;
end
end
end
Error(k2)=Dmax;
end
Error1=Error(kmin:kmax);
MinError=min(Error1);
findc=find(Error1==MinError);
Code(l*2-1)=liccode(findc(1)+kmin-1);
Code(l*2)=' ';
l=l+1;
end
figure(10),imshow(dw),title (['车牌号码:', Code],'Color','b');
function [word,result]=getword(d)
word=[];flag=0;y1=8;y2=0.5;
while flag==0
[m,n]=size(d);
wide=0;
while sum(d(:,wide+1))~=0 && wide<=n-2
wide=wide+1;
end
temp=qiege(imcrop(d,[1 1 wide m]));
[m1,n1]=size(temp);
if wide<y1 && n1/m1>y2
d(:,[1:wide])=0;
if sum(sum(d))~=0
d=qiege(d); % 切割出最小范围
else word=[];flag=1;
end
else
word=qiege(imcrop(d,[1 1 wide m]));
d(:,[1:wide])=0;
if sum(sum(d))~=0;
d=qiege(d);flag=1;
else d=[];
end
end
end
%end
result=d;
function e=qiege(d)
[m,n]=size(d);
top=1;bottom=m;left=1;right=n; % init
while sum(d(top,:))==0 && top<=m
top=top+1;
end
while sum(d(bottom,:))==0 && bottom>=1
bottom=bottom-1;
end
while sum(d(:,left))==0 && left<=n
left=left+1;
end
while sum(d(:,right))==0 && right>=1
right=right-1;
end
dd=right-left;
hh=bottom-top;
e=imcrop(d,[left top dd hh]);

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