本代碼提供了matlab下求取經(jīng)過霍夫變換的直線斜率，并將其聯(lián)合，代碼見下方，實(shí)驗(yàn)結(jié)果見文末。

1. %入口圖像為BW，出口圖像為f
2. %optimizefrommain_optimize,merelyselect2lines,onehaspositive
3. %slope,theotherhasnegativeslope
4. clearall,closeall
5. BW=imread('D:ImagesNEWimg4b9faef664e03.jpg');
6. figure,imshow(BW);
8. BW=rgb2gray(BW);
9. %thresh=[0.01,0.17];
10. thresh=[0.01,0.10];
11. sigma=2;%定義高斯參數(shù)
12. f=edge(double(BW),'canny',thresh,sigma);
13. figure,subplot(121);
14. imshow(f,[]);
15. title('cannyEdgeDetectResult');
17. [H,theta,rho]=hough(f,0.1);%cos(theta)*x+sin(theta)*y=rho
18. %imshow(theta,rho,H,[],'notruesize'),axison,axisnormal
19. %xlabel('theta'),ylabel('rho');
21. [r,c]=houghpeaks(H,10);
22. holdon
25. lines=houghlines(f,theta,rho,r,c);
27. subplot(122);
28. imshow(f,[]),title('HoughTransformDetectResult'),holdon
29. nlind=0;%newlineindex
30. st=1;
31. %%%%%%%%%求斜率%%%%%%%%%%%%
32. fork=1:length(lines)
33. %xy=[lines(k).point1;lines(k).point2];
34. xielv(k)=(lines(k).point2(1)-lines(k).point1(1))/(lines(k).point2(2)-lines(k).point1(2)+0.0001)
35. end
37. %%%%%%%%%將相同斜率的直線連起來%%%%%%%%%%%%
38. k=1;
39. while(k<=length(lines))
40. if(k~=length(lines))
41. k=k+1;
42. end
43. while(abs(xielv(k)-xielv(k-1))<0.0001)
44. k=k+1;
45. if(k>length(lines))
46. break;
47. end
48. end
50. if(abs(xielv(k-1))<0.05||abs(xielv(k-1))>=10)%eliminatehorizontalandverticallines,防治水平線和樓房
51. st=k;
52. if(k~=length(lines))
53. continue;
54. end
55. end
57. if(st==length(lines)&&k==st)
58. if(abs(xielv(k))>0.05&&abs(xielv(k))<10)
59. nlind=nlind+1;
60. newlines(nlind)=lines(st);
61. newlines(nlind).point2=lines(k).point2;
62. newxy=[newlines(nlind).point1;newlines(nlind).point2];
63. plot(newxy(:,2),newxy(:,1),'LineWidth',4,'Color',[.61.0.8]);
64. end
65. break;
66. end
68. %end=k-1,start=st;drawline
69. nlind=nlind+1;
70. newlines(nlind)=lines(st);
71. newlines(nlind).point2=lines(k-1).point2;
72. newxy=[newlines(nlind).point1;newlines(nlind).point2];
73. plot(newxy(:,2),newxy(:,1),'LineWidth',4,'Color',[.61.0.8]);
75. st=k;
76. end
78. fprintf('%dlinesaredetectedinsum.n',nlind);
    

% 入口圖像為 BW，出口圖像為f%optimize from main_optimize, merely select 2 lines, one has positive%slope,the other has negative slopeclear all,close allBW=imread('D:ImagesNEWimg4b9faef664e03.jpg');figure,imshow(BW);BW=rgb2gray(BW);%thresh=[0.01,0.17];thresh=[0.01,0.10];sigma=2;%定義高斯參數(shù)f = edge(double(BW),'canny',thresh,sigma);figure,subplot(121);imshow(f,[]);title('canny Edge Detect Result');[H, theta, rho]= hough(f, 0.1);%cos(theta)*x+sin(theta)*y=rho%imshow(theta,rho,H,[],'notruesize'),axis on,axis normal%xlabel('theta'),ylabel('rho');[r,c]=houghpeaks(H,10);hold onlines=houghlines(f,theta,rho,r,c);subplot(122);imshow(f,[]),title('Hough Transform Detect Result'),hold onnlind=0;%new line indexst=1;%%%%%%%%%求斜率%%%%%%%%%%%%for k=1:length(lines)    %xy=[lines(k).point1;lines(k).point2];    xielv(k)=(lines(k).point2(1)-lines(k).point1(1))/(lines(k).point2(2)-lines(k).point1(2)+0.0001)end%%%%%%%%%將相同斜率的直線連起來%%%%%%%%%%%%k=1;while(k<=length(lines))    if(k~=length(lines))        k=k+1;    end    while(abs(xielv(k)-xielv(k-1))<0.0001)        k=k+1;        if(k>length(lines))            break;        end    end    if(abs(xielv(k-1))<0.05||abs(xielv(k-1))>=10)%eliminate horizontal and vertical lines,防治水平線和樓房        st=k;        if(k~=length(lines))            continue;        end    end        if(st==length(lines)&&k==st)        if(abs(xielv(k))>0.05&&abs(xielv(k))<10)            nlind=nlind+1;            newlines(nlind)=lines(st);            newlines(nlind).point2=lines(k).point2;            newxy=[newlines(nlind).point1;newlines(nlind).point2];            plot(newxy(:,2),newxy(:,1),'LineWidth',4,'Color',[.6 1.0 .8]);        end        break;    end    %end=k-1,start=st; draw line    nlind=nlind+1;    newlines(nlind)=lines(st);    newlines(nlind).point2=lines(k-1).point2;    newxy=[newlines(nlind).point1;newlines(nlind).point2];    plot(newxy(:,2),newxy(:,1),'LineWidth',4,'Color',[.6 1.0 .8]);    st=k;endfprintf('%d lines are detected in sum.n',nlind);

實(shí)驗(yàn)結(jié)果：

原圖：

未優(yōu)化的霍夫變換：

優(yōu)化后：

轉(zhuǎn)自 ： http://blog.csdn.net/abcjennifer/article/details/6674572

************************************另一版本******************************

總結(jié)如下：
(1)對圖片預(yù)處理，這里必須說明的是，純種的Hough變換只適應(yīng)黑白圖片，換句話說，在使用它之前，你已經(jīng)提取出該圖片的邊緣了。
(2) 找到圖片中的“黑點(diǎn)”也就是要處理的邊緣，假設(shè)其在直角坐標(biāo)系的下標(biāo)為(x,y)，對其進(jìn)行坐標(biāo)變換ρ=x*cosθ+y*sinθ，其中0<θ<2*pi。當(dāng)然，在實(shí)際的操作中，θ要轉(zhuǎn)變?yōu)殡x散的數(shù)組θ1、θ2……θj，ρ也就是相應(yīng)的有ρ1、ρ2……ρj。
(3) 判斷(ρj, θj)與哪個數(shù)組元素對應(yīng)，并讓該數(shù)組元素加1。
(4) 比較數(shù)組元素值的大小，最大值對應(yīng)的(ρj, θj)就是這些共線點(diǎn)對應(yīng)的直線方程的參數(shù)。共線方程為
ρj = xcosθj + ysinθj

在matlab中，使用hough、houghpeaks和houghlines可以簡單的檢測到直線。例子如下。
I = imread('test12.bmp');%讀入示例圖片%
Imshow(I);%顯示示例圖片%

Img =edge(I,'prewitt');%利用prewitt算子提取邊緣%
Imshow(Img);%顯示提取邊緣的圖片%

[H, T, R] =hough(Img);%hough變換%
imshow(sqrt(H),[]);%hough變換的結(jié)果%
P = houghpeaks(H, 15, 'threshold', ceil(0.3*max(H(:))));
%尋找最大點(diǎn)%
lines = houghlines(Img, T, R, P,'FillGap',10,'MinLength',20);
%返回找到的直線%
figure, imshow(I), hold on
max_len = 0;
for k = 1:length(lines)
xy = [lines(k).point1; lines(k).point2];
plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');
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

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