matlab车道线检测

1、共享知识分享快乐 clc % 读图 最后得到灰度图像rg A=imread(999.p ng); r c d=size(A); r2g=zeros(r,c); red=zeros(r,c); gree n=zeros(r,c); blue=zeros(r,c); rg=zeros(r,c); for i=1:r; for j=1:c; red(i,j)=A(i,j,1); %提取图像的红色分量 green(i,j)=A(i,j,2); %提取图像的绿色分量 blue(i,j)=A(i,j,3); %提取图像的蓝色分量 end end for i=1:r; for j=1:c; rg(i,j)=

2、0.5*red(i,j)+0.5*gree n(i,j); end end rg=ui nt8(rg); for i=1:r; for j=1:c; if rg(i,j)178; rg(i,j)=255; end end end figure; subplot(2,2,1);imshow(A);title(原图)% 显示原图像 subplot(222);imshow(rg);title(彩色通道提取法-灰度图); % % figure r2g=rg; i=r2g; %输入灰度变换后的图像 subplot(221);imshow(i);title(原图) subplot(223);imhist(

3、i); % 显示直方图 h1=histeq(i); subplot(222);imshow(h1);title(直方图均衡化后的图) subplot(224);imhist(h1); % % i=h1;%直方图均衡化后的图像 j=imno ise(i, salt figure; subplot(121);imshow(j);title(添加椒盐噪声图像) subplot(122);imshow(k1);title( 3*3模板中值滤波) % % clc r2g; figure; subplot(221);imshow(r2g); title(原图像)； W_H仁2 3 0; %选用自定义差分模

4、板增强左车道标记线 3 0 -3; 0 -3 -2; W_V1= 0 3 2; %选用自定义差分模板增强右车道标记线 -3 0 3; -2 -3 0; T = 0.28;% the threshold in the 2-value I = r2g; % read the image height,width = size(I); 11 = double(l); 13 = double(l); 14 = double(l); % put the images data into a bigger array to % move the wi ndow and calculate the grad

5、s %不同方向的模板算子 12 = zeros(height+2,width+2); void the edge I2(2:height+1,2:width+1) = I1; for i=2:height+1 for j=2:width+1 sum3 = 0; sum4 = 0; for m=-1:1 for n=-1:1 sum3= sum3 + W_H1(m + 2,n + 2) * I2(i + m,j + n); end end for m=-1:1 for n=-1:1 sum4 = sum4 + W_V1(m + 2,n + 2) * I2(i + m,j + n); end en

6、d grey1 = abs(sum3) + abs(sum4); I3(i-1,j-1) = grey1; end end big = max(max(l3);% 归一化 small = min(min (13); for i=1:height for j=1:width I3(i,j) = (I3(i,j)-small)/(big - small); % 归一化 if(I3(i,j) T) I3(i,j) = 1;% 二值化 else I3(i,j) = 0; end end end subplot(222); imshow(l3);title(sl、sr算子处理的图像) % % figur

7、e;subplot(221);imshow(A);title(原图) gg=bwmorph(l3,thi n ,inf); subplot(222);imshow(gg);title(细化的图像) I = rg; x,y=size(I); height,width = size(I); seedx=r oun d(x); seedy=ro un d(y/2); gr=I(seedx,seedy) W_H = 111; 1 1 1; 1 1 1; II = double(I); I2 = zeros(height+2,width+2); void the edge l2(2:height+1,2

8、:width+1) = I1; for i=2:height+1 for j=2:width+1 % the model in the horiz on direct ion % put the images data into a bigger array to % move the wi ndow and calculate the grads sum1 = 0;% the cumulus for m=-1:1 for n=-1:1 sum1 = sum1 + W_H(m + 2,n + 2) * I2(i + m,j + n); end end grey=sum1/9; I1(i-1,j

9、-1) = grey; end end I1=ui nt8(l1);%邻域平均化灰度图像 %subplot(222);imshow(l1);title(区域生长-路面区域图像) x,y=size(I1); I2=zeros(x,y); l=double(l); I仁 double(I1); for i=1:x; for j=1:y; if abs(l1(i,j)-l(i,j)=70 end end end subplot(223) imshow(l2);title(区域生长-路面区域图像) I4=zeros(x,y); for i=roun d(5):x-4; for j=5:y-4; if

10、gg(i,j)=1 for m=i-4:i+4; for n =j-4:j+4; if I2(m, n)=0 end end end end end end subplot(224) imshow(I4);title(检测图像) % % clc; tO=clock ff=l4;%输入检测的图像 x,y=size(ff); a仁zeros(x,1); b1=zeros(y,1); k=1; for i=1:x for j=1:rou nd(y/2); if ff(i,j)=1; a1(k)=i; b1(k)=j; k=k+1; end end end m=le ngth(a1); a2=max(

11、a1) h=1; for i=1:m; if a1(i)=a2; jiaobiao(h)=i; h=h+1; end end b1=b1(jiaobiao); b1 仁m ax(b1); %ff(a1,b1)为选中的车道线第一个像素点 k=1; for i=roun d(1):ro un d(x); for j=1:rou nd(y/2 ); if ff(i,j)=1 kkb(k)=(b11-j)/(a2-i); bbc(k)=b11-kkb(k)*a2; k=k+1; end end end theta=ata n(-1./kkb); theta仁 theta+pi, roi=bbc.*si

12、 n(theta); roi1= roi+abs(roi); maxtheta=max( thetal); maxroi=max(roi1); accum=zeros(r oun d(maxtheta)+1,r ound( maxroi)+1); for i=1:le ngth(theta); thetai nt=rou nd( maxtheta/2+theta1(i)/2); roii nt=round( maxroi/2+roi1(i)/2)+1; accum(thetai nt,roii nt)=accum( thetai nt,roii nt)+1; end p=max(max(acc

13、um)%出现峰值处的累加器的值 for i=1:le ngth(theta); thetai nt=rou nd( maxtheta/2+theta1(i)/2); roii nt=round( maxroi/2+roi1(i)/2)+1; if accum(theta in t,roii nt)=p; ji=i; end end k=1; m=1; for i=roun d(x/2):x; for j=1:rou nd(y/2); if ff(i,j)=1 kk(k)=(b11-j)/(a2-i); bb(k)=b11-kk(k)*a2; theta(k)=ata n( -1./kk(k); if theta(k) =theta(ji); 刈(m)=i; yj