车牌识别.rar

%1.读取图片 [fn,pn,fi]=uigetfile('*.jpg','选择图片'); I=imread([pn fn]); figure(1), imshow(I); title('原始图像'); %2.灰度处理 Im1=rgb2gray(I); figure(2), subplot(1,2,1), imshow(Im1); subplot(1,2,2), imhist(Im1); title('灰度图'); %3.增强处理 tiao=imadjust(Im1,[0.2,0.8],[0,1]); figure(3), subplot(1,2,1), imshow(tiao); subplot(1,2,2), imhist(tiao); title('增强效果图'); %4.边缘检测-sobel算子 Im2=edge(tiao,'sobel',0.15); figure(4), imshow(Im2); title('sobel算子边缘检测'); %5.灰度图腐蚀 se=[1;1]; %刷子矩阵 Im3=imerode(Im2,se); figure(5), imshow(Im3); title('腐蚀效果图'); %6.图像平滑处理 se=strel('rectangle',[25,25]); %创建结构元素 Im4=imclose(Im3,se) %平滑轮廓 figure(6), imshow(Im4); title('平滑图像轮廓'); %7.移除小对象 Im5=bwareaopen(Im4,10000); figure(7), imshow(Im5); title('移除小对象'); %gtmd水印 %8.牌照区域分割（看不懂） [y,x]=size(Im5); Im6=double(Im5); Blue_y=zeros(y,1); %创建元素为零的矩阵y*1 for i=1:y for j=1:x if(Im6(i,j,1)==1) Blue_y(i,1)=Blue_y(i,1)+1;%根据Im5的y值确定 end end end [temp MaxY]=max(Blue_y); 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,:,:); Blue_x=zeros(1,x); for j=1:x for i=PY1:PY2 if(Im6(i,j,1)==1) Blue_x(1,j)=Blue_x(1,j)+1; %根据Im5的x值确定 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)&&(PX1<PX2)) PX2=PX2-1; end PX1=PX1-1; %车牌方向校正 PX2=PX2+1; dw=I(PY1:PY2-6,PX1:PX2,:); figure(8), subplot(1,2,1), imshow(IY), title('垂直方向的合理区域'); figure(8), subplot(1,2,2), imshow(dw), title('定位剪切后的彩色车牌图像') %9.滤波，二值化，膨胀与腐蚀处理 imwrite(dw,'dw.jpg'); a=imread('dw.jpg'); b=rgb2gray(a); figure(9), subplot(2,2,1), imshow(b), title('1.车牌灰度图像'); g_max=max(max(b)); g_min=min(min(b)); T=round((2/3)*g_max+(1/3)*g_min); %设定阈值 [m,n]=size(b); d=(double(b)>=T); figure(9), subplot(2,2,2), imshow(d), title('2.车牌二值图像'); figure(9), subplot(2,2,3), imshow(d), title('3.均值滤波前'); h=fspecial('average',3); d=im2bw(round(filter2(h,d))); figure(9), subplot(2,2,4), imshow(d), title('4.均值滤波后'); %有问题 % [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,'膨胀或腐蚀处理后.jpg'); % figure(9), % subplot(3,2,5), % imshow(d), % title('5.膨胀或腐蚀处理后') %10.字符分割与归一化 d=qiege(d); [m,n]=size(d); % subplot(3,2,5),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; 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); figure(10); subplot(2,7,1),imshow(word1),title('1'); subplot(2,7,2),imshow(word2),title('2'); subplot(2,7,3),imshow(word3),title('3'); subplot(2,7,4),imshow(word4),title('4'); subplot(2,7,5),imshow(word5),title('5'); subplot(2,7,6),imshow(word6),title('6'); subplot(2,7,7),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(2,7,8),imshow(word1),title('1'); subplot(2,7,9),imshow(word2),title('2'); subplot(2,7,10),imshow(word3),title('3'); subplot(2,7,11),imshow(word4),title('4'); subplot(2,7,12),imshow(word5),title('5'); subplot(2,7,13),imshow(word6),title('6'); subplot(2,7,14),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' '京辽鲁陕苏豫浙']); %建立自动识别字符代码表 SubBw2=zeros(40,20); %产生40*20的全0矩阵 l=1; for I=1:7 ii=int2str(I); %转为串 t=imread([ii,'.jpg']); %读取图片文件中的数据 SegBw2=imresize(t,[40 20],'nearest'); %对图像做缩放处理 SegBw2=double(SegBw2)>20; 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('D:\MATLAB\字符模板\',liccode(k2),'.jpg'); %把行向量转化成字符串 SamBw2 = imread(fname); SamBw2=double(SamBw2)>1; 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)=' '; %输出最大相关图像 l=l+1; end figure(11),imshow(dw),title (['车牌号码:', Code],'Color','r');