zernike.rar_matlab 图像处理_subpixel_zernike_亚像素_边缘检测 zernike

%function zernike7(I) clear; clc; I=imread('1.bmp'); if length(size(I))==3 I=rgb2gray(I); end %I=rgb2gray(I); %I = edge(I,'canny',0.2); % I=im2bw(I,0.25); % I=imnoise(I,'gaussian'); figure(1);imshow(I); % 7*7Zernike模板 M00=... [ 0 0.0287 0.0686 0.0807 0.0686 0.0287 0 0.0287 0.0815 0.0816 0.0816 0.0816 0.0815 0.0287 0.0686 0.0816 0.0816 0.0816 0.0816 0.0816 0.0686 0.0807 0.0816 0.0816 0.0816 0.0816 0.0816 0.0807 0.0686 0.0816 0.0816 0.0816 0.0816 0.0816 0.0686 0.0287 0.0815 0.0816 0.0816 0.0816 0.0815 0.0287 0 0.0287 0.0686 0.0807 0.0686 0.0287 0 ]; M11R=... [ 0 -0.015 -0.019 0 0.019 0.015 0 -0.0224 -0.0466 -0.0233 0 0.0233 0.0466 0.0224 -0.0573 -0.0466 -0.0233 0 0.0233 0.0466 0.0573 -0.069 -0.0466 -0.0233 0 0.0233 0.0466 0.069 -0.0573 -0.0466 -0.0233 0 0.0233 0.0466 0.0573 -0.0224 -0.0466 -0.0233 0 0.0233 0.0466 0.0224 0 -0.015 -0.019 0 0.019 0.015 0 ]; M11I=... [ 0 -0.0224 -0.0573 -0.069 -0.0573 -0.0224 0 -0.015 -0.0466 -0.0466 -0.0466 -0.0466 -0.0466 -0.015 -0.019 -0.0233 -0.0233 -0.0233 -0.0233 -0.0233 -0.019 0 0 0 0 0 0 0 0.019 0.0233 0.0233 0.0233 0.0233 0.0233 0.019 0.015 0.0466 0.0466 0.0466 0.0466 0.0466 0.015 0 0.0224 0.0573 0.069 0.0573 0.0224 0 ]; M20=... [ 0 0.0225 0.0394 0.0396 0.0394 0.0225 0 0.0225 0.0271 -0.0128 -0.0261 -0.0128 0.0271 0.0225 0.0394 -0.0128 -0.0528 -0.0661 -0.0528 -0.0128 0.0394 0.0396 -0.0261 -0.0661 -0.0794 -0.0661 -0.0261 0.0396 0.0394 -0.0128 -0.0528 -0.0661 -0.0528 -0.0128 0.0394 0.0225 0.0271 -0.0128 -0.0261 -0.0128 0.0271 0.0225 0 0.0225 0.0394 0.0396 0.0394 0.0225 0 ]; tic; K=double(I); [m n]=size(K); xs=double(zeros(m,n)); ys=double(zeros(m,n)); %imshow(I); % 卷积运算 A11I=conv2(M11I,K); A11R=conv2(M11R,K); A20=conv2(M20,K); % 截掉多余部分 A11I=A11I(4:end-3,4:end-3); A11R=A11R(4:end-3,4:end-3); A20=A20(4:end-3,4:end-3); J=zeros(size(K)); boundary=J; theta=atan2(A11I,A11R);%计算theta %计算边缘的三个参数 A11C=A11R.*cos(theta)+A11I.*sin(theta); l=A20./A11C; k=1.5*A11C./((1-l.^2).^1.5); e=abs(l)>1/3.5; k(e)=0; %边缘判断条件 a=abs(l)<1/2.5*2/7; b=abs(k)>max(I(:))/6; % a,b分别为距离和边缘强度判断结果 J(a&b)=1; %将图像的最边缘去除 % boundary(2:end-1,2:end-1)=1; % J(~boundary)=0; format short [x,y]=find(J==1);%边缘的像素级坐标 O=[x y]; Z=[x+l(find(J==1)).*cos(theta(find(J==1))) y+l(find(J==1)).*sin(theta(find(J==1)))];%亚像素坐标 toc; % fprintf('%.4f %.4f\n',Z'); figure(2);imshow(J); % [L,num]=bwlabel(J,8);%对二值图像进行标记 % %自动化搜索连通域 % s=zeros(1,num); % for i=1:num % s(i)=size(find(L==i),1); % end % [bwL,label]=sort(s,'descend');