车牌定位及字符识别的MATLAB程序

function lpr_loc() % license plate recognition - car plate location based on color model % modified by ZHAO Hui, April 30th,2005 I=imread('Car.jpg'); [y,x,z]=size(I); myI=double(I); %%%%%%%%%%% RGB to HSI %%%%%%%% tic % 测定算法执行的时间，开始计时 %%%%%%%%%%% 统计分析 %%%%%%%%%%%%%%% %%%%%%%% Y 方向 %%%%%%%%%% Blue_y=zeros(y,1); for i=1:y for j=1:x if((myI(i,j,1)<=121)&&myI(i,j,1)>=110&&((myI(i,j,2)<=155)&&(myI(i,j,2)>=141))&&((myI(i,j,3)<=240)&&(myI(i,j,3)>=210))) % 蓝色RGB的灰度范围 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 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)<=121)&&myI(i,j,1)>=110&&((myI(i,j,2)<=155)&&(myI(i,j,2)>=141))&&((myI(i,j,3)<=240)&&(myI(i,j,3)>=210))) 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=PX1-2; % 对车牌区域的修正 PX2=PX2+2; Plate=I(PY1:PY2,PX1-2:PX2,:); t=toc % 读取计时 Plate2=rgb2gray(Plate);%图像灰度化 figure,imshow(I);%显示车 figure,plot(Blue_y);grid%y方向蓝色象素点统计 figure,plot(Blue_x);grid%x方向蓝色象素点统计 figure,imshow(IY);%Y方向截取结 figure,imshow(Plate);% 提取的车牌 figure,imshow(Plate2);%车牌的灰度化 Plate3=im2bw(Plate2,0.7);%将图象二值化，二值化图像函数主要有dither和im2bw函数。 dither 函数通过颜色抖动来达到转换图像的目的。 语法：BW = dither(I)。 Image 是图像矩阵资料，BW 是二值化图像矩阵 ;im2bw 函数通过对灰度值进行阈值判断的方法达到目的。 语法：BinaryImage = im2bw( Image, [Level] )。Image 是输入图像矩阵资料，Level 是二值化程度值，其为介于0到1之间值，BW 是二值化图像矩阵。 figure,imshow(Plate3); [n,m]=size(Plate3) ; Plate3x{1}=Plate3(1:n,1:17*m/129); figure,imshow(Plate3x{1}) Plate3x{2}=Plate3(1:n,17*m/129:35*m/129); figure,imshow(Plate3x{2}) Plate3x{3}=Plate3(1:n,39*m/129:60*m/129); figure,imshow(Plate3x{3}) Plate3x{4}=Plate3(1:n,60*m/129:77*m/129); figure,imshow(~Plate3x{4}) Plate3x{5}=Plate3(1:n,77*m/129:94*m/129); figure,imshow(Plate3x{5}) Plate3x{6}=Plate3(1:n,94*m/129:111*m/129); figure,imshow(Plate3x{6}) Plate3x{7}=Plate3(1:n,111*m/129:m); figure,imshow(Plate3x{7}) % result=''; %%%制作模板 for i=1:36 ii=int2str(i-1); t=imread(['车牌字符模板\',ii,'.bmp']); t=rgb2gray(t); level=graythresh(t); t=im2bw(t,level); t=~t; pattern{i}=imresize(t,[10 6],'nearest'); % figure(8);subplot(4,10,i),imshow(pattern{i}); end for n=2:7 %%%将字符与模板作比较 DIST=10000; %字符与模板距离 cn(n)=10000; %%%前三个字符和字母模板比较 Char{n}=imresize(Plate3x{n},[10,6],'nearest'); if n<=3 for pn=10:35 dist=sum(sum( xor(Char{n} , pattern{pn+1}))); if dist<=DIST DIST=dist; cn(n)=pn; end end end %%%后四个字符与数字模板比较 if n>=3 for pn=0:9 dist=sum(sum( xor(Char{n} , pattern{pn+1}))); if dist<=DIST DIST=dist; cn(n)=pn; end end end %根据代号判断字符内容 switch cn(n) case 0 char=' 0' case 1 char=' 1' case 2 char=' 2' case 3 char=' 3' case 4 char=' 4' case 5 char=' 5' case 6 char=' 6' case 7 char=' 7' case 8 char=' 8' case 9 char=' 9' case 10 char=' A' case 11 char=' B' case 12 char=' C' case 13 char=' D' case 14 char=' E' case 15 char=' F' case 16 char=' G' case 17 char=' H' case 18 char=' I' case 19 char=' J' case 20 char=' K' case 21 char=' L' case 22 char=' M' case 23 char=' N' case 24 char=' O' case 25 char=' P' case 26 char=' Q' case 27 char=' R' case 28 char=' S' case 29 char=' T' case 30 char=' U' case 31 char=' V' case 32 char=' W' case 33 char=' X' case 34 char=' Y' case 35 char=' Z' otherwise char=' 识别失败' end % result=strcat(result,char); end % str='Stop' % figure, imshow(result)