matlab 霍夫检测
%霍夫检测
BW=imread('lexp_1_2.bmp');
BW=rgb2gray(BW);
thresh=[0.01,0.17];
sigma=2;%定义高斯参数
f = edge(double(BW),'canny',thresh,sigma);
figure(1),imshow(f,[]);
title('canny 边缘检测');
[H, theta, rho]= hough(f,'RhoResolution', 0.5);
%imshow(theta,rho,H,[],'notruesize'),axis on,axis normal
%xlabel('\theta'),ylabel('rho');
peak=houghpeaks(H,5);
hold on
lines=houghlines(f,theta,rho,peak);
figure,imshow(f,[]),title('Hough Transform Detect Result'),hold on
for k=1:length(lines)
xy=[lines(k).point1;lines(k).point2];
plot(xy(:,1),xy(:,2),'LineWidth',4,'Color',[.6 .6 .6]);
end
%%
I=imread('1.jpg');
Ihsv=rgb2hsv(I);
Iv=Ihsv(:,:,3); %提取v空间
Ivl=Iv(500:end,:); %截取下半部
Iedge=edge(Ivl,'sobel'); %边沿检测
Iedge = imdilate(Iedge,ones(3));%图像膨胀
%新建窗口,绘图用
figure (2)
imshow(Iedge);
hold on
%左方直线检测与绘制
%得到霍夫空间
[H1,T1,R1] = hough(Iedge,'Theta',20:0.1:75);
%求极值点
Peaks=houghpeaks(H1,5);
%得到线段信息
lines=houghlines(Iedge,T1,R1,Peaks);
%绘制线段
for k=1:length(lines)
xy=[lines(k).point1;lines(k).point2];
plot(xy(:,1),xy(:,2),'LineWidth',4);
end
%右方直线检测与绘制
[H2,T2,R2] = hough(Iedge,'Theta',-75:0.1:-20);
Peaks1=houghpeaks(H2,5);
lines1=houghlines(Iedge,T2,R2,Peaks1);
for k=1:length(lines1)
xy1=[lines1(k).point1;lines1(k).point2];
plot(xy1(:,1),xy1(:,2),'LineWidth',4);
end
hold off
%%
%以下只是做一个带直线的图像而已
r=300;
jiaodu=30; %更改这个值测试,90度270度时不管用
jiaodu1=mod(jiaodu,360);
flag=0;
if jiaodu1>=0 && jiaodu1<90
jiaodu1=jiaodu1;
flag=1;
end
if jiaodu1>=90 && jiaodu1<180
jiaodu1=180-jiaodu1;
flag=2;
end
if jiaodu1>=180 && jiaodu1<270
jiaodu1=jiaodu1-180;
flag=3;
end
if jiaodu1>=270 && jiaodu1<360
jiaodu1=360-jiaodu1;
flag=4;
end
H=floor(r*sin(jiaodu1*pi/180));
W=floor(r*cos(jiaodu1*pi/180));
if mod(H,2)==0
H=H+1;
end
if mod(W,2)==0
W=W+1;
end
w=zeros(H,W);
if jiaodu1 ~= 90 && jiaodu1 ~= 270
for i=1:H
for j=1:W
tmp=floor(j*tan(jiaodu1*pi/180));
if tmp+1==i
w(i,j)=r;
end
end
end
else
for i=1:H
w(i,1)=r;
end
end
if flag==1 || flag==3 %如果角度在1,3象限,卷积矩阵上下翻转
w=flipud(w);
end
%下面是真正的霍夫变换
img=mat2gray(w); %处理这个图像
[m n]=size(img);
imshow(img);
data=zeros(314,2*(m+n));
for i=1:m %将图像二维空间的一个点映射到p=x*cos(theta)+y*sin(theta)方程对应的参数空间的一条曲线
for j=1:n
if img(i,j)==1
for theta=0.01:0.01:3.14
data(round(theta*100),round(i*sin(theta)+j*cos(theta)+m+n))= ...
data(round(theta*100),round(i*sin(theta)+j*cos(theta)+m+n))+1;
end
end
end
end
theta=0;
ma=0;
for i=1:314 %寻找曲线相交最多的那个点,即找最大值
for j=1:2*(m+n)
if data(i,j)>ma
ma=data(i,j);
theta=i/100;
rou=j-m-n;
end
end
end
figure;imshow(data) %形象的显示参数空间曲线
sr_k=tan(jiaodu*pi/180) %设置的斜率
re_k=cos(theta)/sin(theta) %求得的斜率