matlab棋盘格角点自动检测提取程序

clc clear close all %结果数据是CC % rootFolder = fullfile('D:\Data\2016.5.18棋盘格'); rootFolder = fullfile('D:\程序\总'); imgSets = imageSet(rootFolder); count=imgSets.Count(1,1); row=7;%棋盘格的行数 col=10;%棋盘格的列数 rho=12;%ρ为图像中角点弥散斑直径。 bianchang=160;%棋盘格的边长 theta=0.2;%角度步进 jd=cell(1,count); for img=1:count I=read(imgSets,img);%读取第i幅图 I=rgb2gray(I); %做标准差为3的高斯滤波，然后以0.08为低门槛，0.2为高门槛，进行canny边缘检测 %考虑到棋盘格信息对比度明显，选择较高的灰度梯度门槛值进行边缘检测 %可以考虑使用OTSU算法对棋盘格图像进行预处理 [BW,thresh]=edge(I,'canny',[0.2*0.4,0.2],3);%BW为二值化的边缘图像 % figure;imshow(I,[]); % figure;imshow(BW,[]); %% %hough变换检测竖线 [H,T,R]=hough(BW,'RhoResolution',rho,'Theta',-10:theta:10); P=houghpeaks(H,col+3,'threshold',ceil(0.2*max(H(:))));%预留4个裕量 lines=houghlines(BW,T,R,P,'FillGap',bianchang*1.5,'MinLength',bianchang*3); % h2=figure; % imshow(I,'InitialMagnification',30); % title('霍夫变换直线检测'); % grid on; % axis on; % hold on; shu=[]; ps=[]; for k=1:length(lines) xy=[lines(k).point1;lines(k).point2]; dis=(xy(1,1)+xy(2,1))/2; shu=[shu,dis]; sign=0; if length(shu)>1 for i=1:length(shu)-1 if abs(dis-shu(i))<rho*2.5 shu(end)=[];%删除重复直线 sign=1; break end end end if sign continue end t=lines(k).theta; r=lines(k).rho; %写成x=p1*y+p2的形式避免斜率为无穷 p=[-tan(t*pi/180),r/cos(t*pi/180)]; ps=[ps;p]; % y=1:max(size(I)); % x=polyval(p,y); % plot(x,y,'LineWidth',2,'Color','green'); end %删除可能存在的棋盘格边缘线 %限制条件：棋盘格必须位于图像正中，偏差不能超过一个棋盘格 %这里是偷懒了、、凑合用 switch length(shu) case col+1 for u=1:2 [m1,index1]=max(shu); m1=size(I,2)-m1; [m2,index2]=min(shu); if m1<m2 ps(index1,:)=[]; shu(index1)=[]; else ps(index2,:)=[]; shu(index2)=[]; end end case col [m1,index1]=max(shu); m1=size(I,2)-m1; [m2,index2]=min(shu); if m1<m2 ps(index1,:)=[]; shu(index1)=[]; else ps(index2,:)=[]; shu(index2)=[]; end end if length(shu)<col-1 disp(strcat('第',num2str(img),'张棋盘格竖线漏检')); end %% %hough变换检测横线 [H,T,R]=hough(BW,'RhoResolution',rho,'Theta',[-90:theta:-80,80:theta:90-theta]); P=houghpeaks(H,row+3,'threshold',ceil(0.2*max(H(:)))); lines=houghlines(BW,T,R,P,'FillGap',bianchang*1.5,'MinLength',bianchang*3); heng=[]; ph=[]; for k=1:length(lines) xy=[lines(k).point1;lines(k).point2]; dis=(xy(1,2)+xy(2,2))/2; heng=[heng,dis]; sign=0; if length(heng)>1 for i=1:length(heng)-1 if abs(dis-heng(i))<rho*2.5 heng(end)=[]; sign=1; break end end end if sign continue end t=lines(k).theta; r=lines(k).rho; p=[-cot(t*pi/180),r/sin(t*pi/180)]; ph=[ph;p]; % x=1:max(size(I)); % y=polyval(p,x); % plot(x,y,'LineWidth',2,'Color','blue'); end %删除可能存在的棋盘格边缘线 switch length(heng) case row+1 for u=1:2 [m1,index1]=max(heng); m1=size(I,1)-m1; [m2,index2]=min(heng); if m1<m2 ph(index1,:)=[]; heng(index1)=[]; else ph(index2,:)=[]; heng(index2)=[]; end end case row [m1,index1]=max(heng); m1=size(I,1)-m1; [m2,index2]=min(heng); if m1<m2 ph(index1,:)=[]; heng(index1)=[]; else ph(index2,:)=[]; heng(index2)=[]; end end if length(heng)<row-1 disp(strcat('第',num2str(img),'张棋盘格横线漏检')); end %% %求纵横线交点 corner0=zeros(2,(row-1)*(col-1)); for i=1:row-1 for j=1:col-1 n=(i-1)*(col-1)+j; corner0(1,n)=(ps(j,1)*ph(i,2)+ps(j,2))/(1-ps(j,1)*ph(i,1)); corner0(2,n)=(ph(i,1)*ps(j,2)+ph(i,2))/(1-ph(i,1)*ps(j,1)); end end % figure; % imshow(I,'InitialMagnification',30); % title('角点粗略检测'); % grid on; % axis on; % hold on; % plot(corner0(1,:),corner0(2,:),'rx'); %% %求精确角点 if rho>10 Image=imresize(I,1/2); C=corner(Image,'FilterCoefficients',fspecial('gaussian',[5 1],3)); % figure,imshow(Image,'InitialMagnification',60); % hold on % plot(C(:,1), C(:,2), 'rx'); C=C.*2; else Image=I; C=corner(Image,'FilterCoefficients',fspecial('gaussian',[5 1],3)); % figure,imshow(Image,'InitialMagnification',30); % hold on % plot(C(:,1), C(:,2), 'rx'); end C0=corner0'; CC=zeros(size(C0)); % finds the nearest neighbor in C for each point in C0 [nv,d]=knnsearch(C,C0,'k',2); for i=1:size(corner0,2) a=C(nv(i,:),:); CC(i,:)=mean(a(d(i,:)<rho+5,:),1); end figure; imshow(I,'InitialMagnification',30); title('角点精确检测'); grid on; axis on; hold on; plot(CC(:,1),CC(:,2),'rx'); jd{1,img}=CC; end