matlab車(chē)道線(xiàn)檢測(cè)（精編版）

1、clc%讀圖最后得到灰度圖像 rga=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); %提取圖像的紅色分量green(i,j)=a(i,j,2); %提取圖像的綠色分量blue(i,j)=a(i,j,3); %提取圖像的藍(lán)色分量endendfor i=1:r;for j=1:c;rg(i,j)=0.5*red(i,j)+0.5*green(i,j);en

2、dendrg=uint8(rg);for i=1:r;for j=1:c;if rg(i,j)178;rg(i,j)=255;endendendfigure;subplot(2,2,1);imshow(a);title( 原圖)% 顯示原圖像subplot(222);imshow(rg);title(彩色通道提取法 -灰度圖 );%figurer2g=rg;i=r2g;%輸入灰度變換后的圖像subplot(221);imshow(i);title( 原圖)subplot(223);imhist(i);%顯示直方圖h1=histeq(i);subplot(222);imshow(h1);titl

3、e(直方圖均衡化后的圖 )subplot(224);imhist(h1);%i=h1;%直方圖均衡化后的圖像j=imnoise(i,salt & pepper,0.02)k1=medfilt2(j);figure;subplot(121);imshow(j);title( 添加椒鹽噪聲圖像 )subplot(122);imshow(k1);title( 3*3模板中值濾波 )%clcr2g;figure;subplot(221);imshow(r2g);title(原圖像 );w_h1=2 3 0;%選用自定義差分模板增強(qiáng)左車(chē)道標(biāo)記線(xiàn)3 0 -3;0 -3 -2; w_v1= 0 3

4、2;%選用自定義差分模板增強(qiáng)右車(chē)道標(biāo)記線(xiàn)-3 0 3;-2 -3 0;t = 0.28; % the threshold in the 2-valuei = r2g; % read the imageheight,width = size(i);i1 = double(i);i3 = double(i);i4 = double(i);i2 = zeros(height+2,width+2); % put the images data into a bigger array to void the edgei2(2:height+1,2:width+1) = i1;for i=2:height

5、+1 % move the window and calculate the gradsfor j=2:width+1sum3 = 0; % 不同方向的模板算子sum4 = 0;for m=-1:1for n=-1:1sum3= sum3 + w_h1(m + 2,n + 2) * i2(i + m,j + n);endendfor m=-1:1for n=-1:1 sum4 = sum4 + w_v1(m + 2,n + 2) * i2(i + m,j + n);endendgrey1 = abs(sum3) + abs(sum4); i3(i-1,j-1) = grey1;endendbi

6、g = max(max(i3); % 歸一化small = min(min(i3);for i=1:heightfor j=1:widthi3(i,j) = (i3(i,j)-small)/(big - small); % 歸一化if(i3(i,j) t)i3(i,j) = 1; % 二值化elsei3(i,j) = 0;endendendsubplot(222);imshow(i3);title( sl、sr算子處理的圖像 )%figure;subplot(221);imshow(a);title( 原圖)gg=bwmorph(i3,thin,inf);subplot(222);imshow

7、(gg);title(細(xì)化的圖像 )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 direction1 1 1;1 1 1;i1 = double(i);i2 = zeros(height+2,width+2); % put the images data into a bigger array to void the edgei2(2:height+1,2:width+1) =

8、i1;for i=2:height+1 % move the window and calculate the gradsfor j=2:width+1sum1 = 0; % the cumulus for m=-1:1for n=-1:1sum1 = sum1 + w_h(m + 2,n + 2) * i2(i + m,j + n);endendgrey=sum1/9;i1(i-1,j-1) = grey;endendi1=uint8(i1);%鄰域平均化灰度圖像%subplot(222);imshow(i1);title( 區(qū)域生長(zhǎng) -路面區(qū)域圖像 )x,y=size(i1);i2=zer

9、os(x,y);i=double(i);i1=double(i1);fori=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;endendendsubplot(223)imshow(i2);title( 區(qū)域生長(zhǎng) -路面區(qū)域圖像 )i4=zeros(x,y);for i=round(5):x-4;for j=5:y-4;if gg(i,j)=1for m=i-4:i+4;for n=j-4:j+4;if i2(m,n)=0&sqrt(i-m)2+(j-n2)=2i4(i

10、,j)=1;endendendendendendsubplot(224)imshow(i4);title( 檢測(cè)圖像 )%clc;t0=clockff=i4;%輸入檢測(cè)的圖像x,y=size(ff);a1=zeros(x,1);b1=zeros(y,1);k=1;for i=1:xfor j=1:round(y/2);ifff(i,j)=1;a1(k)=i;b1(k)=j;k=k+1;endendendm=length(a1);a2=max(a1)h=1;for i=1:m;if a1(i)=a2;jiaobiao(h)=i;h=h+1;endendb1=b1(jiaobiao);b11=ma

11、x(b1);%ff(a1,b1)為選中的車(chē)道線(xiàn)第一個(gè)像素點(diǎn)k=1;fori=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;endendendtheta=atan(-1./kkb);theta1= theta+pi,roi=bbc.*sin(theta);roi1= roi+abs(roi);maxtheta=max( theta1);maxroi=max(roi1);accum=zeros(round(m

12、axtheta)+1,round( maxroi)+1);fori=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;endp=max(max(accum)%出現(xiàn)峰值處的累加器的值fori=1:length(theta);thetaint=round( maxtheta/2+theta1(i)/2);roiint=round( maxroi/2+roi1(i)/2)+1;ifaccum(thetaint,roiint)=p;ji=i;endendk=1;m=1;fori=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;endk=k+1;endendend%xji