matlab车道线检测

matlab车道线检测
clc %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%读图最后得到灰度图像rg
A=imread('999.png');
[r c d]=size(A);
r2g=zeros(r,c);
red=zeros(r,c);
green=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)=0.5*red(i,j)+0.5*green(i,j);
end
end
rg=uint8(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(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=imnoise(i,'salt & pepper',0.02)
k1=medfilt2(j);
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_H1=[2 3 0;%选用自定义差分模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);
I1 = double(I);
I3 = double(I);
I4 = double(I);
I2 = zeros(height+2,width+2); % put the image's data into a bigger array to void the edge
I2(2:height+1,2:width+1) = I1;
for i=2:height+1 % move the window and calculate the grads for j=2:width+1
sum3 = 0; % 不同方向的模板算子
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
end
grey1 = abs(sum3) + abs(sum4);
I3(i-1,j-1) = grey1;
end
end
big = max(max(I3)); % 归一化
small = min(min(I3));
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(I3);title('sl、sr算子处理的图像') %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%% %%%%%
figure;subplot(221);imshow(A);title('原图')
gg=bwmorph(I3,'thin',inf);
subplot(222);imshow(gg);title('细化的图像')
I = rg;
[x,y]=size(I);
[height,width] = size(I);
seedx=round(x);
seedy=round(y/2);
gr=I(seedx,seedy)
W_H = [ 1 1 1; % the model in the horizon direction
1 1 1;
1 1 1];
I1 = double(I);
I2 = zeros(height+2,width+2); % put the image's data into a bigger array to void the edge
I2(2:height+1,2:width+1) = I1;
for i=2:height+1 % move the window and calculate the grads for j=2:width+1
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-1) = grey;
end
end
I1=uint8(I1);%邻域平均化灰度图像
%subplot(222);imshow(I1);title('区域生长-路面区域图像')
[x,y]=size(I1);
I2=zeros(x,y);
I=double(I);
I1=double(I1);
for i=1:x;
for j=1:y;
if abs(I1(i,j)-I(i,j))<=70&abs(I(seedx,seedy)-I1(i,j)<=90)
I2(i,j)=1;
end
end
end
subplot(223)
imshow(I2);title('区域生长-路面区域图像')
I4=zeros(x,y);
for i=round(5):x-4;
for j=5:y-4;
if gg(i,j)==1
for m=i-4:i+4;
for n=j-4:j+4;
if I2(m,n)==0&sqrt((i-m)^2+(j-n^2))<=2
I4(i,j)=1;
end
end
end
end
end
end
subplot(224)
imshow(I4);title('检测图像')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%% %%%%%%%%%%%%%%
clc;
t0=clock
ff=I4;%输入检测的图像
[x,y]=size(ff);
a1=zeros(x,1);
b1=zeros(y,1);
k=1;
for i=1:x
for j=1:round(y/2);
if ff(i,j)==1;
a1(k)=i;
b1(k)=j;
k=k+1;
end
end
end
m=length(a1);
a2=max(a1)
h=1;
for i=1:m;
if a1(i)==a2;
jiaobiao(h)=i;
h=h+1;
end
end
b1=b1(jiaobiao);
b11=max(b1);
%ff(a1,b1)为选中的车道线第一个像素点k=1; for i=round(1):round(x);
for j=1:round(y/2 );
if ff(i,j)==1&i~=a2&j~=b11;
kkb(k)=(b11-j)/(a2-i);
bbc(k)=b11-kkb(k)*a2;
k=k+1;
end
end
end
theta=atan(-1./kkb);
theta1= theta+pi,
roi=bbc.*sin(theta);
roi1= roi+abs(roi);
maxtheta=max( theta1);
maxroi=max(roi1);
accum=zeros(round(maxtheta)+1,round( maxroi)+1); for i=1:length(theta);
thetaint=round( maxtheta/2+theta1(i)/2);
roiint=round( maxroi/2+roi1(i)/2)+1;
accum(thetaint,roiint)=accum( thetaint,roiint)+1; end
p=max(max(accum))%出现峰值处的累加器的值for i=1:length(theta);
thetaint=round( maxtheta/2+theta1(i)/2);
roiint=round( maxroi/2+roi1(i)/2)+1;
if accum(thetaint,roiint)==p;
ji=i;
end
end
k=1;
m=1;
for i=round(x/2):x;
for j=1:round(y/2);
if ff(i,j)==1&i~=a2&j~=b11;
kk(k)=(b11-j)/(a2-i);
bb(k)=b11-kk(k)*a2;
theta(k)=atan(-1./kk(k));
if theta(k) ==theta(ji) ;
xji(m)=i;
yji(m)=j;
m=m+1;
end
k=k+1;
end
end
end
%xji=median(xji);
%yji=median(yji);
ji;
theta(ji);
imshow(I4);hold on;
line( [yji,b11] ,[xji,a2],'linewidth',3);title('根据改进的hough做标记线') time = etime(clock, t0)。