matlab-图像边缘检测,包括sobel,hough直线提取以及SUSAN角点提取-源码

clc; clear; close all; warning off; addpath(genpath(pwd)); img=imread('house.png');house=img; img=rgb2gray(img); img=im2double(img); figure(); subplot(2,2,1); imshow(house); title('原图'); [m,n]=size(img); hx = [-1 -2 -1;0 0 0 ;1 2 1];%生产sobel垂直梯度模板 hy = hx'; %生产sobel水平梯度模板 %% 预处理 %垂直梯度 gradx = filter2(hx,img,'same'); gradx = abs(gradx); %计算图像的sobel垂直梯度 %水平梯度 grady = filter2(hy,img,'same'); grady = abs(grady); %计算图像的sobel水平梯度 %sobel梯度 grad = gradx + grady; %得到图像的sobel梯度 subplot(2,2,2);imshow(grad);title('Sobel算子提取图像边缘'); I = grad; %均值滤波 [m,n]=size(I); y = zeros(m,n); for i=2:m-1 for j=2:n-1 y(i,j)=I(i-1,j-1)+I(i-1,j)+I(i-1,j+1)+I(i,j-1)+I(i,j)+I(i,j+1)+I(i+1,j-1)+I(i+1,j)+I(i+1,j+1); y(i,j)=y(i,j)/9; end end subplot(2,2,3);imshow(y);title('均值去噪后'); %二值化 q=im2uint8(y); [m,n]=size(q); for i=1:m for j=1:n if q(i,j)>160 q(i,j)=255; else q(i,j)=0; end end end subplot(2,2,4);imshow(q);title('二值化处理后'); %% hough变换检测 theta=180; dis=round(sqrt(m^2+n^2)); s=zeros(theta,2*dis); z=cell(theta,2*dis); for i=1:m for j=1:n if (q(i,j)==255) for k=1:theta p=round(i*cos(pi*k/180)+j*sin(pi*k/180)); %对每个点从1到180度遍历 if(p>0) s(k,dis+p)=s(k,dis+p)+1; z{k,dis+p}=[z{k,dis+p},[i,j]']; else ap=abs(p)+1; s(k,ap)=s(k,ap)+1; z{k,ap}=[z{k,ap},[i,j]']; end end end end end for i=1:theta for j=1:dis*2 if(s(i,j)>120) lp=z{i,j}; for k=1:s(i,j) house(lp(1,k),lp(2,k),1)=255; house(lp(1,k),lp(2,k),2)=0; house(lp(1,k),lp(2,k),3)=0; end end end end figure imshow(house),title('Hough');