基本信息
源码名称：车牌识别.m
源码大小：6.98KB
文件格式：.m
开发语言：MATLAB
更新时间：2022-01-19
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源码介绍
车牌识别.m
clc;
close all;
I=imread('img.png');
imshow(I);
title("原图");
I1=rgb2gray(I);
figure(2);
imshow(I1);
title('灰度图');
I2=edge(I1, 'Roberts',0.11,'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(PY1-1:PY2 1,PX1-1:PX2 1,:) ;
t=toc;
figure(7) ,
subplot(1,2,1) ,
imshow(IY),
title('行方向区域');
figure(7) ,
subplot(1,2,2),
imshow(dw),
title('定位后的彩色车牌图像');
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) ;
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为二值化的阀值
[m,n]=size(b);
d=(double(b)>=T); % d:二值图像
imwrite(d,'2.车牌二值图像.jpg') ;
figure(9) ,
imshow(d) ,
title('2.车牌二值图像');
figure(10),
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(11),
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(12),
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),imwrite(word1,'1.png');
% 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
wordl=p_resize(word1);
word2=p_resize(word2) ;
word3=p_resize(word3);
word4=p_resize(word4);
word5=p_resize(word5);
word6=p_resize(word6);
word7=p_resize(word7) ;
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),imwrite(word1,'1.png');
title('7') ;
wordl=imresize(word1,[28 28]);
word2=imresize(word2,[28 28]) ;
word3=imresize(word3,[28 28]);
word4=imresize(word4,[28 28]);
word5=imresize(word5,[28 28]);
word6=imresize(word6,[28 28]);
word7=imresize(word7,[28 28]) ;
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.png');
imwrite(word2,'2.png');
imwrite(word3,'3.png');
imwrite(word4,'4.png');
imwrite(word5,'5.png');
imwrite(word6,'6.png');
imwrite(word7,'7.png');
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]) ;
end
function [word,d]=getword(d)%, result
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
function [photo] = p_resize(word)
[m,n] = size(word);
k = max(m,n) 8
photo = zeros(k,k);
a = uint8((k-m)/2)
b = uint8((k-n)/2)
for i = a:m a-1
for j = b:b n-1
i,j
photo(i,j) = photo(i,j) word(i-a 1,j-b 1);
end
end
end
车牌识别.m
clear;
clc;
close all;
I=imread('img.png');
imshow(I);
title("原图");
I1=rgb2gray(I);
figure(2);
imshow(I1);
title('灰度图');
I2=edge(I1, 'Roberts',0.11,'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(PY1-1:PY2 1,PX1-1:PX2 1,:) ;
t=toc;
figure(7) ,
subplot(1,2,1) ,
imshow(IY),
title('行方向区域');
figure(7) ,
subplot(1,2,2),
imshow(dw),
title('定位后的彩色车牌图像');
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) ;
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为二值化的阀值
[m,n]=size(b);
d=(double(b)>=T); % d:二值图像
imwrite(d,'2.车牌二值图像.jpg') ;
figure(9) ,
imshow(d) ,
title('2.车牌二值图像');
figure(10),
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(11),
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(12),
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),imwrite(word1,'1.png');
% 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
wordl=p_resize(word1);
word2=p_resize(word2) ;
word3=p_resize(word3);
word4=p_resize(word4);
word5=p_resize(word5);
word6=p_resize(word6);
word7=p_resize(word7) ;
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),imwrite(word1,'1.png');
title('7') ;
wordl=imresize(word1,[28 28]);
word2=imresize(word2,[28 28]) ;
word3=imresize(word3,[28 28]);
word4=imresize(word4,[28 28]);
word5=imresize(word5,[28 28]);
word6=imresize(word6,[28 28]);
word7=imresize(word7,[28 28]) ;
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.png');
imwrite(word2,'2.png');
imwrite(word3,'3.png');
imwrite(word4,'4.png');
imwrite(word5,'5.png');
imwrite(word6,'6.png');
imwrite(word7,'7.png');
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]) ;
end
function [word,d]=getword(d)%, result
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
function [photo] = p_resize(word)
[m,n] = size(word);
k = max(m,n) 8
photo = zeros(k,k);
a = uint8((k-m)/2)
b = uint8((k-n)/2)
for i = a:m a-1
for j = b:b n-1
i,j
photo(i,j) = photo(i,j) word(i-a 1,j-b 1);
end
end
end