matlab 霍夫變換(hough) 檢測直線

　　霍夫變換是一種特征檢測(feature extraction)，被廣泛應用在圖像分析（image analysis）、電腦視覺 (computer vision)以及數位影像處理 (digital image processing)。 霍夫變換是用來辨別找出物件中的特征，例如：線條。他的算法流程大致如下，給定一個物件、要辨別的形狀的種類，算法會在參數空間(parameter space)中執行投票來決定物體的形狀， 而這是由累加空間(accumulator space)里的局部最大值(local maximum)來決定。　　

　　Hough變換的基本原理在於，利用點與線的對偶性，將圖像空間的線條變為參數空間的聚集點，從而檢測給定圖像是否存在給定性質的曲線。

clc;clear ; close 
set(0,'defaultfigurecolor',[1,1,1]) 
load DATA2.mat
data = D1;
BW = data;

figure(1)
imshow(BW)
title('原圖像');
figure(2)
subplot 211;
%%進行霍夫變換
[H, theta , rho] = hough (BW);
%%繪制霍夫空間
imshow(imadjust(mat2gray(H)),[],'XData',theta,'YData',rho,...
        'InitialMagnification','fit');
xlabel('\theta (degrees)'), ylabel('\rho');
axis on, axis normal, hold on;
colormap(hot);	
title('霍夫空間')
%%峰值
P = houghpeaks(H,5,'threshold',0.5*max(H(:)));
x = theta(P(:,2));
y = rho(P(:,1));
plot(x,y,'s','color','black');
%lines = houghlines(BW,theta,rho,P,'FillGap',10,'MinLength',10);
lines = houghlines(BW,theta,rho,P,'FillGap',10,'MinLength',10);
subplot 212
imshow(BW) ,hold on
max_len  = 0;
count = 1;
points = zeros(2,2);
for k = 1:length(lines)
   points(count,1) = lines(k).point1(1);
   points(count,2) = lines(k).point1(2);
   count =count +1;
   points(count,1) = lines(k).point2(1);
   points(count,2) = lines(k).point2(2);
   count =count +1;
   xy = [lines(k).point1; lines(k).point2];
   plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');
   % Plot beginnings and ends of lines
   plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');
   plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');
end
title('直線檢測');

　　效果如下：