基于MATLAB的车牌识别系统,基于matlab的车牌识别系统设计,matlab

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,'sobel',0.15,'both'); figure(3),imshow(I2);title('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,:); G=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'); a=imread('dw.jpg'); b=rgb2gray(a);%功能是将真彩色图像转换为灰度图像，即灰度化处理 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 向最近的方向取整 [~,~]=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') % 均值滤波处理 h=fspecial('average',3); d=im2bw(round(filter2(h,d)));%filter2(B,X),B为滤波器.X为要滤波的数据,这里将B放在X上,一个一个移动进行模板滤波. imwrite(d,'4.均值滤波后.jpg'); figure(8),subplot(3,2,4),imshow(d),title('4.均值滤波后') se=eye(2);%产生m×n的单位矩阵 [m,n]=size(d); if bwarea(d)/m/n>=0.365 %bwarea是计算二值图像中对象的总面积的函数 d=imerode(d,se);%腐蚀 elseif bwarea(d)/m/n<=0.235 d=imdilate(d,se);%膨胀 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') H=toc; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 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); [~,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; % 判定有两个字符,需要分割 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,~]=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,~]=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; % 此处为切割出来的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); % 归一化大小为 40*20 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' '京津沪晋辽吉鲁苏浙皖鲁豫粤川陕新黑宁']); JG=zeros(40,20);%产生一个40*20大小的零矩阵 l=1; L=toc; for I=1:7 %I为待识别的字符位 ii=int2str(I);%整形数据转化为字符串类型 t=imread([ii,'.jpg']); MB=imresize(t,[40 20],'nearest');%缩放处理 if l==1 %车牌号第一位为汉字识别，使用37-53号样本库 kmin=37; kmax=53; elseif l==2 %车票号第二位为 A~Z 大写字母识别，使用11-36号样本库 kmin=11; kmax=36; else l>=3; %第三位以后是字母或数字识别，使用1-36号样本库 kmin=1; kmax=36; end for k2=kmin:kmax fname=strcat('样本库\',liccode(k2),'.bmp'); YB = imread(fname); %调用样本库图像文件 for i=1:40 for j=1:20 JG(i,j)=MB(i,j)-YB(i,j); % 这里是将待识别图像与模板图像两幅图相减得到第三幅图 end end Dmax=0; for k1=1:40 for l1=1:20 if ( JG(k1,l1) > 0 || JG(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 t=toc; figure(10),imshow(dw),title (['车牌号:', Code],'Color','k' ,'font','20');