matlab车牌识别字符切割,车牌识别字符分割问题

matlab车牌识别字符切割,车牌识别字符分割问题function[d]=main(jpg)closeall;clear;[filename,filepath]=uigetfile('.jpg','输⼊⼀个需要识别的车牌图像');%直接⾃动读⼊%file=strcat(filepath,filename);I=imread(file);%figure(1),imshow(I);title('原图');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,'roberts',0.18,'both');%边缘检测%figure(3),imshow(I2);title('robert算⼦边缘检测')se=[1;1;1];I3=imerode(I2,se);%腐蚀%figure(4),imshow(I3);title('腐蚀后图像');se=strel('rectangle',[20,20]);%⽣成⼀个矩阵I4=imclose(I3,se);%闭运算%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');%车牌定位[y,x,~]=size(I5);myI=double(I5);%转换为doublele类型%begin横向扫描Blue_y=zeros(y,1);fori=1:yforj=x:-1:1if(myI(i,j,1)==1)%如果myI(i,j,1)即myI图像中坐标为(i,j)的点为⽩⾊%则Blue_y的相应⾏的元素white_y(i,1)值加1Blue_y(i,1)=Blue_y(i,1)+1;%蓝⾊像素点统计endend

end[temp,MaxY]=max(Blue_y);%temp为向量white_y的元素中的最⼤值，MaxY为该值的索引(在向量中的位置)PY1=MaxY;while((Blue_y(PY1,1)>=5)&&(PY1>1))PY1=PY1-1;endPY2=MaxY;while((Blue_y(PY2,1)>=5)&&(PY2PY2=PY2+1;endIY=I(PY1:PY2,:,:);%IY为原始图像I中截取的纵坐标在PY1：PY2之间的部分%end横向扫描%begin纵向扫描Blue_x=zeros(1,x);%进⼀步确定x⽅向的车牌区域forj=1:xfori=PY1:PY2if(myI(i,j,1)==1)Blue_x(1,j)=Blue_x(1,j)+1;endendendPX1=1;while((Blue_x(1,PX1)<5)&&(PX1PX1=PX1+1;endPX2=x;while((Blue_x(1,PX2)<5)&&(PX2>PX1))PX2=PX2-1;end%end纵向扫描PX1=PX1-2;%对车牌区域的校正PX2=PX2+2;dw=I(PY1+2:PY2-2,PX1+6:PX2-6,:);

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);imwrite(b,'车牌灰度图像.jpg');figure(8);subplot(1,2,1),imshow(b),title('车牌灰度图像')thresh=graythresh(b);d=im2bw(b,thresh);%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%[m,n]=size(b);%d=(double(b)>=T);%d:⼆值图像imwrite(d,'2.车牌⼆值图像.jpg');figure(8);subplot(1,2,2),imshow(d),title('2.车牌⼆值图像')figure(9),subplot(1,2,1),imshow(d),title('3.中值滤波前')%滤波h=medfilt2(d);%h=fspecial('average',3);d=im2bw(h)%d=im2bw(round(filter2(h,d)));%BW=im2bw(I,level)将灰度图像I转换为⼆进制图像。输出图像%BW将输⼊图像中亮度值⼤于level的像素替换为值1(⽩⾊)，其他替换为值0(⿊⾊imwrite(d,'4.中值滤波.jpg');figure(9),subplot(1,2,2),imshow(d),title('4.中值滤波后')%膨胀或腐蚀se=eye(2);%eye(n)returnsthen-by-nidentitymatrix单位矩阵[m,n]=size(d);ifbwarea(d)/m/n>=0.365%计算⾯积d=imerode(d,se);%imerode实现图像腐蚀d为待处理图像，se是结构元素对象elseifbwarea(d)/m/n<=0.235d=imdilate(d,se);%imdilate图像膨胀endimwrite(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')%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);k1=1;k2=1;s=sum(d);j=1;whilej~=nwhiles(j)==0j=j+1;endk1=j;whiles(j)~=0&&j<=n-1j=j+1;endk2=j-1;ifk2-k1>=round(n/6.5)[val,num]=min(sum(d(:,[k1+5:k2-5])));d(:,k1+num+5)=0;%分割endendd=qiege(d);y1=10;y2=0.25;flag=0;word1=[];whileflag==0[m,n]=size(d);left=1;wide=0;whilesum(d(:,wide+1))~=0wide=wide+1;endifwided(:,[1:wide])=0;d=qiege(d);elsetemp=qiege(imcrop(d,[11widem]));[m,n]=size(temp);all=sum(sum(temp));

two_thirds=sum(sum(temp([round(m/3):2*round(m/3)],:)));iftwo_thirds/all>y2flag=1;word1=temp;%WORD1endd(:,[1:wide])=0;d=qiege(d);endend%分割出第⼆个字符[word2,d]=getword(d);%分割出第⼆个字符[word3,d]=getword(d);%分割出车牌的点舍弃不要[word4,d]=getword(d);%分割出第三个字符[word5,d]=getword(d);%分割出第四个字符[word6,d]=getword(d);%分割出第五个字符[word7,d]=getword(d);%分割出第六个字符%[word8,d]=getword(d);%分割出第七个字符[m,n]=size(word1);word1=imresize(word1,[4020]);word2=imresize(word2,[4020]);word2=imresize(word3,[4020]);word4=imresize(word4,[4020]);word5=imresize(word5,[4020]);word6=imresize(word6,[4020]);word7=imresize(word7,[4020]);%word8=imresize(word8,[4020]);figure(16),subplot(1,8,1),imshow(word1),title('1');subplot(1,8,2),imshow(word2),title('2');subplot(1,8,3),imshow(word2),title('3');subplot(1,8,4),imshow(word4),title('4');subplot(1,8,5),imshow(word5),title('5');subplot(1,8,6),imshow(word6),title('6');subplot(1,8,7),imshow(word7),title('7');%subplot(1,8,7),imshow(word8),title('8');%⼦程序：(getword⼦程序)

function[word,result]=getword(d)word=[];flag=0;y1=8;y2=0.5;whileflag==0[m,n]=size(d);wide=0;whilesum(d(:,wide+1))~=0&&wide<=n-2%有⽩⾊加1知道没有⽩⾊，也就%是找出⼀个⽩⾊区域wide=wide+1;endtemp=qiege(imcrop(d,[11widem]));[m1,n1]=size(temp);ifwidey2d(:,[1:wide])=0;ifsum(sum(d))~=0d=qiege(d);%切割出最⼩范围elseword=[];flag=1;endelseword=qiege(imcrop(d,[11widem]));d(:,[1:wide])=0;ifsum(sum(d))~=0d=qiege(d);flag=1;elsed=[];endendendresult=d;functione=qiege(d)[m,n]=size(d);top=1;bottom=m;left=1;right=n;%initwhilesum(d(top,:))==0&&top<=m%切割出⽩⾊区域(横切)top=top+1;en