车牌识别的matlab程序(程序,讲解,模板)

clc

clear

close all

I=imread('chepai.jpg');

subplot(3,2,1);imshow(I), title('原始图像');

I_gray=rgb2gray(I);

subplot(3,2,2),imshow(I_gray),title('灰度图像');

%====================== 形态学预处理======================

I_edge=edge(I_gray,'sobel');

subplot(3,2,3),imshow(I_edge),title('边缘检测后图像');

se=[1;1;1];

I_erode=imerode(I_edge,se);

subplot(3,2,4),imshow(I_erode),title('腐蚀后边缘图像');

se=strel('rectangle',[25,25]);

I_close=imclose(I_erode,se); %图像闭合、填充图像

subplot(3,2,5),imshow(I_close),title('填充后图像');

I_final=bwareaopen(I_close,2000); %去除聚团灰度值小于2000的部分

subplot(3,2,6),imshow(I_final),title('形态滤波后图像');

%========================== 车牌分割============================= I_new=zeros(size(I_final,1),size(I_final,2));

location_of_1=[];

for i=1:size(I_final,1) %寻找二值图像中白的点的位置

for j=1:size(I_final,2)

if I_final(i,j)==1;

newlocation=[i,j];

location_of_1=[location_of_1;newlocation];

end

end

end

mini=inf;maxi=0;

for i=1:size(location_of_1,1)

%寻找所有白点中，x坐标与y坐标的和最大，最小的两个点的位置

temp=location_of_1(i,1)+location_of_1(i,2);

if temp

mini=temp;

a=i;

end

if temp>maxi

maxi=temp;

b=i;

end

end

first_point=location_of_1(a,:); %和最小的点为车牌的左上角

last_point=location_of_1(b,:); %和最大的点为车牌的右下角

x1=first_point(1)+4; %坐标值修正

x2=last_point(1)-4;

y1=first_point(2)+4;

y2=last_point(2)-4;

I_plate=I(x1:x2,y1:y2);

I_plate=OTSU(I_plate); %以OTSU算法对分割出的车牌进行自适应二值化处理

I_plate=bwareaopen(I_plate,50);

figure,imshow(I_plate),title('车牌提取') %画出最终车牌

%========================= 字符分割============================

X=[]; %用来存放水平分割线的横坐标

flag=0;

for j=1:size(I_plate,2)

sum_y=sum(I_plate(:,j));

if logical(sum_y)~=flag %列和有变化时，记录下此列

X=[X j];

flag=logical(sum_y);

end

end

figure

for n=1:7

char=I_plate(:,X(2*n-1):X(2*n)-1); %进行粗分割

for i=1:size(char,1) %这两个for循环对分割字符的上下进行裁剪if sum(char(i,:))~=0

top=i;

break

end

end

for i=1:size(char,1)

if sum(char(size(char,1)-i,:))~=0

bottom=size(char,1)-i;

break

end

end

char=char(top:bottom,:);

subplot(2,4,n);imshow(char);

char=imresize(char,[32,16],'nearest'); %归一化为32*16的大小，以便模板匹配

eval(strcat('Char_',num2str(n),'=char;')); %将分割的字符放入Char_i中

end

%========================== 字符识别============================= char=[];

store1=strcat('京','津','沪','渝','冀','晋','辽','吉','黑','苏','浙'... %汉字识别

,'皖','闽','赣','鲁','豫','鄂','湘','粤','琼','川','贵','云','陕'...

,'甘','青','藏','桂','皖','新','宁','港','鲁','蒙');

for j=1:34

Im=Char_1;

Template=imread(strcat('chinese\',num2str(j),'.bmp')); %chinese文件附在最后

Template=im2bw(Template);

Differ=Im-Template;

Compare(j)=sum(sum(abs(Differ)));

end

index=find(Compare==(min(Compare)));

char=[char store1(index)];

store2=strcat('A','B','C','D','E','F','G','H','J','K','L','M','M','N','P','Q','R'...

,'S','T','U','V','W','X','Y','Z','0','1','2','3','4','5','6','7','8','9');

for i=2:7 %字母数字识别for j=1:35

Im=eval(strcat('Char_',num2str(i)));

Template=imread(strcat('cha&num\',num2str(j),'.bmp')); %cha&num文件附在最后

Template=im2bw(Template);

Differ=Im-Template;

Compare(j)=sum(sum(abs(Differ)));

end

index=find(Compare==(min(Compare)));

char=[char store2(index)];

end

figure,imshow(I),title(strcat('车牌为:',char))