北航机器视觉第一次作业——八边形识别

1、八边形识别本文将四个八边形的图像称为源图像（test.jpg），将单个多边形的图像称为待匹配图像（test1.jpg、test2.jpg）。步骤1：角点检测函数octagon_corner.m函数是利用课本上提到的Harris角点探测器，对整个图像提取角点。步骤2：图像的预处理及角点匹配octagon_search.m和octagon_source.m函数，分别对源图像和待匹配图像处理，用于将检测出的角点与各自归属的八边形匹配。步骤3：交比计算octagon_cal_much.m和octagon_cal_one.m函数，分别用于对源图像和待匹配图像计算交比。步骤4：找到最像的八边形octago

2、n_main.m主函数，将待匹配图像与源图像匹配。匹配结果1：匹配结果2：代码function theta=angle1(x1,y1,x2,y2,x3,y3)theta=acosd(dot(x1-x2,y1-y2,x3-x2,y3-y2)/(norm(x1-x2,y1-y2)*norm(x3-x2,y3-y2);function octagon_CR=octagon_cal_much(point_devide)number_octagon=size(point_devide,3);octagon_angle=zeros(8,4,number_octagon);octagon_CR=zeros(

3、8,number_octagon);x=zeros(4,1);y=zeros(4,1);l=zeros(4,1);for i=1:number_octagon for j=1:8 xx=point_devide(j,1,i); yy=point_devide(j,2,i); for k=1:4 if(j+k=8) x(k)=point_devide(8,1,i); y(k)=point_devide(8,2,i); else x(k)=point_devide(rem(j+k,8),1,i); y(k)=point_devide(rem(j+k,8),2,i); end end octagon

4、_angle(j,1,i)=sind(angle1(x(1),y(1),xx,yy,x(3),y(3); octagon_angle(j,2,i)=sind(angle1(x(2),y(2),xx,yy,x(3),y(3); octagon_angle(j,3,i)=sind(angle1(x(1),y(1),xx,yy,x(4),y(4); octagon_angle(j,4,i)=sind(angle1(x(2),y(2),xx,yy,x(4),y(4); octagon_CR(j,i)=(octagon_angle(j,1,i)/octagon_angle(j,2,i)/(octagon

5、_angle(j,3,i)/octagon_angle(j,4,i); endendfunction octagon_CR=octagon_cal_one(point_devide)number_octagon=size(point_devide,3);octagon_angle=zeros(8,4);octagon_CR=zeros(8,1);x=zeros(4,1);y=zeros(4,1);l=zeros(4,1); for j=1:8 xx=point_devide(j,1); yy=point_devide(j,2); for k=1:4 if(j+k=8) x(k)=point_d

6、evide(8,1); y(k)=point_devide(8,2); else x(k)=point_devide(rem(j+k,8),1); y(k)=point_devide(rem(j+k,8),2); end end octagon_angle(j,1)=sind(angle1(x(1),y(1),xx,yy,x(3),y(3); octagon_angle(j,2)=sind(angle1(x(2),y(2),xx,yy,x(3),y(3); octagon_angle(j,3)=sind(angle1(x(1),y(1),xx,yy,x(4),y(4); octagon_ang

7、le(j,4)=sind(angle1(x(2),y(2),xx,yy,x(4),y(4); octagon_CR(j)=(octagon_angle(j,1)/octagon_angle(j,2)/(octagon_angle(j,3)/octagon_angle(j,4);endfunction ROW COLUMN=octagon_corner(Image) %Image = im2uint8(rgb2gray(Image); dx = -1 0 1;-1 0 1;-1 0 1; %dx：横向Prewitt差分模版 Ix2 = filter2(dx,Image).2; Iy2 = fil

8、ter2(dx',Image).2; Ixy = filter2(dx,Image).*filter2(dx',Image); %生成 9*9高斯窗口。窗口越大，探测到的角点越少。 h= fspecial('gaussian',9,2); A = filter2(h,Ix2); % 用高斯窗口差分Ix2得到A B = filter2(h,Iy2); C = filter2(h,Ixy); nrow = size(Image,1); ncol = size(Image,2); Corner = zeros(nrow,ncol); %矩阵Corner用来保存候选角点

9、位置,初值全零，值为1的点是角点 %真正的角点在137和138行由(row_ave,column_ave)得到 %参数t:点(i,j)八邻域的“相似度”参数，只有中心点与邻域其他八个点的像素值之差在 %（-t,+t）之间，才确认它们为相似点，相似点不在候选角点之列 t=20; %我并没有全部检测图像每个点，而是除去了边界上boundary个像素， %因为我们感兴趣的角点并不出现在边界上 boundary=8; for i=boundary:nrow-boundary+1 for j=boundary:ncol-boundary+1 nlike=0; %相似点个数 if Image(i-1,j-

10、1)>Image(i,j)-t && Image(i-1,j-1)<Image(i,j)+t nlike=nlike+1; end if Image(i-1,j)>Image(i,j)-t && Image(i-1,j)<Image(i,j)+t nlike=nlike+1; end if Image(i-1,j+1)>Image(i,j)-t && Image(i-1,j+1)<Image(i,j)+t nlike=nlike+1; end if Image(i,j-1)>Image(i,j)-t &a

11、mp;& Image(i,j-1)<Image(i,j)+t nlike=nlike+1; end if Image(i,j+1)>Image(i,j)-t && Image(i,j+1)<Image(i,j)+t nlike=nlike+1; end if Image(i+1,j-1)>Image(i,j)-t && Image(i+1,j-1)<Image(i,j)+t nlike=nlike+1; end if Image(i+1,j)>Image(i,j)-t && Image(i+1,j)&l

12、t;Image(i,j)+t nlike=nlike+1; end if Image(i+1,j+1)>Image(i,j)-t && Image(i+1,j+1)<Image(i,j)+t nlike=nlike+1; end if nlike>=2 && nlike<=6 Corner(i,j)=1;%如果周围有0，1，7，8个相似与中心的（i,j） %那(i,j)就不是角点，所以，直接忽略 end; end; end; CRF = zeros(nrow,ncol); % CRF用来保存角点响应函数值,初值全零 CRFmax = 0;

13、 % 图像中角点响应函数的最大值，作阈值之用 t=0.04; %建议取0.04（机器视觉） % 计算CRF %工程上常用CRF(i,j) =det(M)/trace(M)计算CRF，那么此时应该将下面第105行的 %比例系数t设置大一些，t=0.1对采集的这几幅图像来说是一个比较合理的经验值 for i = boundary:nrow-boundary+1 for j = boundary:ncol-boundary+1 if Corner(i,j)=1 %只关注候选点 M = A(i,j) C(i,j); C(i,j) B(i,j); CRF(i,j) = det(M)-t*(trace(M

14、)2; if CRF(i,j) > CRFmax CRFmax = CRF(i,j); end; end end; end; %CRFmax count = 0; % 用来记录角点的个数 t=0.1; % 下面通过一个3*3的窗口来判断当前位置是否为角点 for i = boundary:nrow-boundary+1 for j = boundary:ncol-boundary+1 if Corner(i,j)=1 %只关注候选点的八邻域 if CRF(i,j) > t*CRFmax && CRF(i,j) >CRF(i-1,j-1) . &&

15、; CRF(i,j) > CRF(i-1,j) && CRF(i,j) > CRF(i-1,j+1) . && CRF(i,j) > CRF(i,j-1) && CRF(i,j) > CRF(i,j+1) . && CRF(i,j) > CRF(i+1,j-1) && CRF(i,j) > CRF(i+1,j). && CRF(i,j) > CRF(i+1,j+1) count=count+1;%这个是角点，count加1 else % 如果当前位置（i,j

16、）不是角点，则在Corner(i,j)中删除对该候选角点的记录 Corner(i,j) = 0; end; end; end; end; % toc(t1)p=9;pp=(p-1)/2;ROW=zeros(1,count);COLUNM=zeros(1,count);number=1; for i=boundary:nrow-boundary+1 for j=boundary:ncol-boundary+1 column_ave=0; row_ave=0; k=0; if Corner(i,j)=1 for x=i-pp:i+pp %7*7邻域 for y=j-pp:j+pp if Corne

17、r(x,y)=1 % 用算数平均数作为角点坐标，如果改用几何平均数求点的平均坐标，对角点的提取意义不大 row_ave=row_ave+x; column_ave=column_ave+y; k=k+1; end end end end if k>0 %周围不止一个角点 ROW(number)=row_ave/k; COLUMN(number)=column_ave/k; number=number+1; end end; end; ROW=ROW'COLUMN=COLUMN'temp_m=ROW;temp_n=COLUMN;for i=1:size(temp_m,1)-

18、1 for ii=i+1:size(temp_m,1) if(temp_m(i)=temp_m(ii) if(temp_n(i)=temp_n(ii) temp_m(i)=0; temp_n(i)=0; end end end endj=1;while j<=size(temp_m,1) if(temp_m(j)=0&&temp_n(j)=0) temp_m(j)=; temp_n(j)=; else j=j+1; endendROW=temp_m;COLUMN=temp_n;%clear all%close all%octagon_input=imread('F

19、:/test/test1.jpg');function point_devide=octagon_search(octagon_input)octagon_gray=im2uint8(rgb2gray(octagon_input);row=size(octagon_gray,1);col=size(octagon_gray,2); %角点检测m=zeros(100,1);n=zeros(100,1);m n=octagon_corner(octagon_gray);number_mn=size(m,1);number_octagon=number_mn/8;%判断角点归属temp_m=

20、m;temp_n=n;center_m=row/2;center_n=col/2;point_devide=zeros(8,2,number_octagon);%三列分别为行、列、点序号corner_devide=zeros(32,1);for i=1:number_mn if(temp_m(i)>center_m && temp_n(i)>center_n) corner_devide(i)=1; elseif(temp_m(i)>center_m && temp_n(i)<center_n) corner_devide(i)=2; e

21、lseif(temp_m(i)<center_m && temp_n(i)<center_n) corner_devide(i)=3; elseif(temp_m(i)<center_m && temp_n(i)>center_n) corner_devide(i)=4; else corner_devide(i)=0; endendnumber_devide=ones(1,number_octagon);for i=1:number_mn for j=1:number_octagon if(corner_devide(i)=j) poi

22、nt_devide(number_devide(j),:,j)=temp_m(i) temp_n(i); number_devide(j)=number_devide(j)+1; end endend%clear all%close all%octagon_input=imread('F:/test/test.jpg');function point_devide=octagon_source(octagon_input)octagon_gray=im2uint8(rgb2gray(octagon_input);row=size(octagon_gray,1);col=size(octagon_gray,2); %角点检测m=zeros(100,1);n=zeros(100,1);m n=octag