汽车车牌自动定位与字符分割.doc

I=imread(Car.jpg); %读入图片 figure(1),imshow(I); %显示出图片 [y,x,z]=size(I); myI=double(I); %转化数据为双精度型 %%%%%%%%%%% RGB to HIS %%%%%%%% 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)=30)((myI(i,j,2)=62)(myI(i,j,2)=51))((myI(i,j,3)=142)(myI(i,j,3)=119))) % 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)(PY11)) PY1=PY1-1; end PY2=MaxY; while ((Blue_y(PY2,1)=5)(PY2y)) 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)=30)((myI(i,j,2)=62)(myI(i,j,2)=51))((myI(i,j,3)=142)(myI(i,j,3)=119))) Blue_x(1,j)= Blue_x(1,j)+1; end end end PX1=1; while ((Blue_x(1,PX1)3)(PX1x)) PX1=PX1+1; end PX2=x; while ((Blue_x(1,PX2)8)(PX2PX1)) PX2=PX2-1; end %======对车牌区域的修正========= PX1=PX1-2; % PX2=PX2+2; Plate=I(PY1:PY2,PX1-2:PX2+2,:); %======像素点数在X、Y方向上的统计并且显示数量统计图 t=toc; % 读取计时 figure(2),plot(Blue_x);grid figure(3),plot(Blue_y);grid figure(4),imshow(IY); figure(5),imshow(Plate); %======字符分割并且分别显示 IA=I(PY1:PY2,PX1-2:PX1+12,:); figure(6),imshow(IA); IB=I(PY1:PY2,PX1+ 12:PX1+26,:); figure(7),imshow(IB); IC=I(PY1:PY2,PX1+28:PX1+44,:); figure(8),imshow(IC); ID=I(PY1:PY2,PX1+44:PX1+56,:); figure(9),imshow(ID); IE=I(PY1:PY2,PX1+58:PX1+70,:); figure(10),imshow(IE); IF=I(PY1:PY2,PX1+70:PX1+84,:); figure(11),imshow(IF); IG=I(PY1:PY2,PX1+84:PX2+2,:); figure(12),imshow(IG); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 字符分割模块算法 % 定位剪切后的彩色车牌图像－－灰度－－二值化－－统一到黑底白字－－去除上下边框 % －－切割出最小范围－－滤波－－形态学处理－－分割出7个字符 % 去除上下边框算法： % 1.黑白跳变小于阈值则被视为背景；2.连续白线大于某阈值则该白线被认为是背