function [PY2,PY1,PX2,PX1]=chepai_fenge(I5)
[y,x,z]=size(I5);
myI=double(I5);
tic
Y_threshlow=5; %这个数值很重要。决定了提取的彩图的质量
X_firrectify=5;
%====================== Y 方向============================
Blue_y=zeros(y,1);
for i=1:yfor j=1:xif(myI(i,j,1)==1)Blue_y(i,1)= Blue_y(i,1)+1;     % 蓝色象素点统计                    end  end
end[temp MaxY]=max(Blue_y);% Y方向车牌区域确定 temp(最多点数):所有行中，最多的累积像素点 MaxY（最多点所在行）:该行中蓝点最多PY1=MaxY;%有最多蓝点的行付给PY1while ((Blue_y(PY1,1)>=Y_threshlow)&&(PY1>1))%找到图片上边界PY1=PY1-1;endPY2=MaxY; %PY1：存储车牌上边界值while ((Blue_y(PY2,1)>=Y_threshlow)&&(PY2<y))%阈值为5PY2=PY2+1;endPY1, PY2 figure(1),imshow(Blue_y),title('y方向确定');pause(2);%==============X 方向===============================X_threshhigh=(PY2-PY1)/11;%这个数值很重要。决定了提取的彩图的质量,适当提高可抗干扰，但是小图会照成剪裁太多Blue_x=zeros(1,x);             % 进一步确定X方向的车牌区域for j=1:xfor i=PY1:PY2if(myI(i,j,1)==1)Blue_x(1,j)= Blue_x(1,j)+1;               end  end       end[temp MaxX]=max(Blue_x);PX1=MaxX-6*(PY2-PY1);if  PX1<=1PX1=1;endwhile ((Blue_x(1,PX1)<=X_threshhigh)&&(PX1<x))%阈值PX1=PX1+1;end               %确定出X方向车牌起点   PX2=MaxX+6*(PY2-PY1);if  PX2>=xPX2=x;endwhile ((Blue_x(1,PX2)<=X_threshhigh)&&(PX2>PX1))%阈值PX2=PX2-1;end            %确定出X方向车牌终点PX1 ,PX2figure(2),imshow(Blue_x),title('X方向确定');

S=(PY2-PY1)*(PX2-PX1)
if       S<=25000threshold=50;Y_secrectify=3;X_secrectify=3;
elseif S>25000&&S<=45000  threshold=100;Y_secrectify=-3;X_secrectify=3;
elseif S>45000&&S<=80000threshold=200;Y_secrectify=-3;X_secrectify=3;
elseif S>80000&&S<=150000threshold=300;Y_secrectify=-10;X_secrectify=-10;
elseif S>150000&&S<=400000threshold=600;Y_secrectify=-10;X_secrectify=-10;
elsethreshold=1800;Y_secrectify=-10;X_secrectify=-10;
end
PY1=PY1-Y_secrectify;
PY2=PY2+Y_secrectify;
PX1=PX1;
PX2=PX2;%对车牌区域的进一步修正
3、字符分割程序：
function e=zifufenge(d)
[m,n]=size(d);
top=1;bottom=m;left=1;right=n;
while sum(d(top,:))==0 && top<=mtop=top+1;
end
while sum(d(bottom,:))==0 && bottom>=1bottom=bottom-1;
end
while sum(d(:,left))==0 && left<=nleft=left+1;
end
while sum(d(:,right))==0 && right>=1right=right-1;
end
dd=right-left;
hh=bottom-top;
e=imcrop(d,[left top dd hh]);

function [word,result]=getword(d)%获取字符
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-2wide=wide+1;endtemp=zifufenge(imcrop(d,[1 1 wide m]));[m1,n1]=size(temp);if wide<y1 && n1/m1>y2d(:,[1:wide])=0;if sum(sum(d))~=0d=zifufenge(d);  % 切割出最小范围else word=[];flag=1;endelseword=zifufenge(imcrop(d,[1 1 wide m]));d(:,[1:wide])=0;if sum(sum(d))~=0;d=zifufenge(d);flag=1;else d=[];endendendresult=d;

function varargout = main(varargin)
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...'gui_Singleton',  gui_Singleton, ...'gui_OpeningFcn', @main_OpeningFcn, ...'gui_OutputFcn',  @main_OutputFcn, ...'gui_LayoutFcn',  [] , ...'gui_Callback',   []);
if nargin && ischar(varargin{1})gui_State.gui_Callback = str2func(varargin{1});
end
if nargout[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
elsegui_mainfcn(gui_State, varargin{:});
end
pause(1);
function main_OpeningFcn(hObject, eventdata, handles, varargin)
set(handles.process,'enable','on')
handles.output = hObject;
guidata(hObject, handles);
function varargout = main_OutputFcn(hObject, eventdata, handles)
tic
varargout{1} = handles.output;
function pushbutton1_Callback(hObject, eventdata, handles)
[filename pathname]=uigetfile({'*.jpg';'*.bmp'}, 'File Selector');
I = imread([pathname '\' filename]);
handles.I = I;
guidata(hObject, handles);
axes(handles.axes1);
imshow(I);title('原始图片')
set(handles.process,'enable','on')
function process_Callback(hObject, eventdata, handles)
I = handles.I;
I1=rgb2gray(I);
guidata(hObject, handles);
axes(handles.axes2);
imshow(I1);title('灰度图');
axes(handles.axes3);
imhist(I1);title('灰度图直方图');
pause(2);
imshow(I2);title('robert算子边缘检测');
pause(2);
se=[1;1;1];
I3=imerode(I2,se);
guidata(hObject, handles);
axes(handles.axes3);
imshow(I3);title('腐蚀后图像');
pause(2);
se=strel('rectangle',[10,25]);
I4=imclose(I3,se);
guidata(hObject, handles);
axes(handles.axes2);
imshow(I4);title('平滑图像的轮廓');
pause(2);
I5=bwareaopen(I4,2000);
guidata(hObject, handles);
axes(handles.axes2);
imshow(I5);title('从对象中移除小对象');
pause(2);
[PY2,PY1,PX2,PX1]=chepai_fenge(I5);%调用分割车牌
global threshold;
[PY2,PY1,PX2,PX1,threshold]=chepai_xiuzheng(PY2,PY1,PX2,PX1);%调用车牌校正
IY=I(PY1:PY2,:,:);
Plate=I5(PY1:PY2,PX1:PX2);global dw;dw=Plate;
PX1=PX1-1;%对车牌区域的校正PX2=PX2+1;dw=I(PY1:PY2-8,PX1:PX2,:);axes(handles.axes2);imshow(dw),title('车牌区域的校正');pause(2);t=tic;
guidata(hObject, handles);
axes(handles.axes2);
imshow(IY),title('水平方向合理区域');
axes(handles.axes3);
imshow(dw),title('定位剪切后的彩色车牌图像');
pause(2);
imwrite(dw,'New number plate.jpg');
[filename,filepath]=uigetfile('New number plate.jpg','输入一个定位裁剪后的车牌图像');
jpg=strcat(filepath,filename);
a=imread('New number plate.jpg');
b=rgb2gray(a);
figure(3),subplot(3,2,1),imshow(b),title('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)/2); %T 为二值化的阈值
[m,n]=size(b);
d=(double(b)>=T);  % d:二值图像
figure(3),subplot(3,2,2),imshow(d),title('车牌二值图像');
figure(3),subplot(3,2,3),imshow(d),title('均值滤波前');
pause(1);
h=fspecial('average',3);% 滤波
d=im2bw(round(filter2(h,d)));
figure(3),subplot(3,2,4),imshow(d),title('均值滤波后');
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>=0.365d=imerode(d,se);
elseif bwarea(d)/m/n<=0.235d=imdilate(d,se);
end
figure(3),subplot(3,2,5),imshow(d),title('膨胀或腐蚀处理后');
pause(2);
%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=zifufenge(d);
[m,n]=size(d);
guidata(hObject, handles);
axes(handles.axes3);imshow(d);
k1=1;k2=1;s=sum(d);j=1;
while j~=nwhile s(j)==0j=j+1;endk1=j;while s(j)~=0 && j<=n-1j=j+1;endk2=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
d=zifufenge(d); % 再分割
% 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))~=0wide=wide+1;endif wide<y1   %  认为是左侧干扰d(:,[1:wide])=0;d=zifufenge(d);elsetemp=zifufenge(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>y2flag=1;word1=temp;  endd(:,[1:wide])=0;d=zifufenge(d);end
end[word2,d]=getword(d); % 分割出第二个字符
pause(1);[word3,d]=getword(d);
pause(1);[word4,d]=getword(d);
pause(1);[word5,d]=getword(d);
pause(1);[word6,d]=getword(d);
pause(1);[word7,d]=getword(d); % 分割出第七个字符
pause(1);
guidata(hObject, handles);
axes(handles.axes4);imshow(word1),title('1');
guidata(hObject, handles);
axes(handles.axes4);imshow(word2),title('2');
guidata(hObject, handles);
axes(handles.axes4);imshow(word3),title('3');
guidata(hObject, handles);
axes(handles.axes4);imshow(word4),title('4');
guidata(hObject, handles);
axes(handles.axes4);imshow(word5),title('5');
guidata(hObject, handles);
axes(handles.axes4);imshow(word6),title('6');
guidata(hObject, handles);
axes(handles.axes4);imshow(word7),title('7');
[m,n]=size(word1);
word1=imresize(word1,[40 20]); % 商用系统程序中归一化大小为 40*20,此处演示
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]);
guidata(hObject, handles);
axes(handles.axes4);imshow(word1),title('1');
guidata(hObject, handles);
axes(handles.axes5);imshow(word2),title('2');
guidata(hObject, handles);
axes(handles.axes6);imshow(word3),title('3');
guidata(hObject, handles);
axes(handles.axes7);imshow(word4),title('4');
guidata(hObject, handles);
axes(handles.axes8);imshow(word5),title('5');
guidata(hObject, handles);
axes(handles.axes9);imshow(word6),title('6');
guidata(hObject, handles);
axes(handles.axes10);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' '桂鲁苏豫京']);  %建立自动识别字符代码表
SubBw2=zeros(40,20);
l=1;
for I=1:7ii=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=41;   pause(1);elseif l==2              %第二位 A~Z 字母识别kmin=11;kmax=36;   pause(1);else l>=3              %第三位以后是字母或数字识别kmin=1;kmax=36;       end     for k2=kmin:kmaxfname=strcat('模板库\',liccode(k2),'.jpg');SamBw2 = imread(fname);for  i=1:40for j=1:20SubBw2(i,j)=SegBw2(i,j)-SamBw2(i,j);endend    % 以上相当于两幅图相减得到第三幅图Dmax=0;for k1=1:40for l1=1:20if  ( SubBw2(k1,l1) > 0 || SubBw2(k1,l1) <0 )Dmax=Dmax+1;endendendError(k2)=Dmax;endError1=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
guidata(hObject, handles);
axes(handles.axes3);imshow(dw),title(['车牌识别号码:', Code],'fontsize',25,'fontname','隶书');
pause(2);
fid = fopen('Data.xls', 'a+');fprintf(fid,'%s\r\n',Code,datestr(now));winopen('Data.xls');fclose(fid);
function pushbutton6_Callback(hObject, eventdata, handles)
close(gcf);% --- 实现清屏功能.
function pushbutton7_Callback(hObject, eventdata, handles)
clc;cla(handles.axes1);cla(handles.axes2);cla(handles.axes3);cla(handles.axes4);cla(handles.axes5);cla(handles.axes6);cla(handles.axes7);cla(handles.axes8);cla(handles.axes9);cla(handles.axes10);