车道线识别车牌识别系统及其学习机制的研究，matlab源码

a=imread('e:/road15.jpg'); %读取路面图像 b=rgb2gray(a);%如果是彩色图 %b=a; %如果是灰度图 c=double(b)/255;%相当于im2double命令 [X Y]=size(b); MESH=8; %划分网格，30*30 x_begin=floor(X/4); x_end=floor(X/MESH-2)*MESH+MESH-1;%x_end=floor(X/4)+floor(X/(2*MESH))*MESH; y_begin=MESH-1; y_end=floor(Y/MESH-2)*MESH+MESH-1; Image_meshed=zeros(size(b)); %取一个和原矩阵同样大小的全零阵 point=zeros(((x_end-x_begin)*(y_end-y_begin)*2/(MESH/2)),2); %一个n×2的矩阵，存储所求的点，矩阵的行数为网格的极大值，为所含点数的2/15 num=0; %对网格上的点取sobel边缘检测，检测结果水平方向为a，竖直方向为b，最后用(|a|+|b|)/2的形式 %首先进行网格线上所有列的搜索 for i=x_begin:MESH:x_end for j=y_begin:y_end a=abs(round(((c(i-1,j-1)+2*c(i,j-1)+c(i+1,j-1))-(c(i-1,j+1)+2*c(i,j+1)+c(i+1,j+1)))*255)); b=abs(round(((c(i+1,j-1)+2*c(i+1,j)+c(i+1,j+1))-(c(i-1,j-1)+2*c(i-1,j)+c(i-1,j+1)))*255)); Image_meshed(i,j)=(a+b)/2; %%对边缘图像进行阈值操作 也可以将此步骤放在下面再循环执行 Thresh=180 if (Image_meshed(i,j)>180&c(i,j)>(190/255)) % Image_meshed(i,j)=255; num=num+1; point(num,1)=i; point(num,2)=j; else Image_meshed(i,j)=0; end end end %然后进行网格线上所有行的搜索 for j=y_begin:MESH:y_end for i=x_begin:x_end a=abs(round(((c(i-1,j-1)+2*c(i,j-1)+c(i+1,j-1))-(c(i-1,j+1)+2*c(i,j+1)+c(i+1,j+1)))*255)); b=abs(round(((c(i+1,j-1)+2*c(i+1,j)+c(i+1,j+1))-(c(i-1,j-1)+2*c(i-1,j)+c(i-1,j+1)))*255)); Image_meshed(i,j)=(a+b)/2; %%对边缘图像进行阈值操作 也可以将此步骤放在下面再循环执行 Thresh=180 if (Image_meshed(i,j)>180&c(i,j)>(190/255)) % Image_meshed(i,j)=255; num=num+1; point(num,1)=i; point(num,2)=j; else Image_meshed(i,j)=0; end end end point_1=point(1:num,1:2); %出去point矩阵的多余0 Image_mesheduint8=uint8(Image_meshed); imshow(Image_mesheduint8) %%%%%%%%%%%%%%%%%%%%%%%% %%%下一步进行聚类分析%%%% %%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%% %%%%下一步进行直线拟合%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%若需要看见得到的车道线，可以进行膨胀运算，所用的结构元素就是就是最初划分网格的 %%大小，然后对膨胀区域取阈值，大约190以上的白色区域就可以提取出来 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%