sanlinyucz.rar_邻域边缘检测

clear all; close all; clc; I = imread('D:\无牌车\1.jpg'); %subplot(231) figure,imshow(I); f = rgb2gray(I); figure,imhist(f); f = im2double(f); [M,N] = size(f); for x = 2:M-1 for y = 2:N-1 a = f(x,y)-f(x+1,y-1); b = f(x,y)-f(x+1,y); c = f(x,y)-f(x+1,y+1); e = max(max(a,b),c); if(e<0) e=0; end f(x,y) = e*255; end end J=uint8(f); %subplot(232);imshow(J);title('三邻域差值边缘检测 不乘2'); figure,imhist(J); % % %膨胀 % B=[0 1 0,0 1 0,0 0 1]; % A2=imdilate(J,B);%图像A2被结构元素B膨胀 % subplot(223),imshow(A2);title('使用B后1次膨胀后的图像'); %%闭运算 % se = strel('disk',13); % bg1=imclose(J,se); % %bg1=imclose(J,strel('rectangle',[10,10]));%取矩形框的闭运算 % subplot(233),imshow(bg1);title('图像闭运算');%输出闭运算的图像 % %%取得最佳阈值，将图像二值化 % fmax1=double(max(max(J)));%egray的最大值并输出双精度型 % fmin1=double(min(min(J)));%egray的最小值并输出双精度型 % level=(fmax1-(fmax1-fmin1)/2)/255;%获得最佳阈值 % YZ = level*255; % %level = ((fmax1-fmin1)/3)/255; % bw22=im2bw(J,level);%转换图像为二进制图像 % bw2=double(bw22); % subplot(233),imshow(bw2);title('小阈值二值图像'); % B=[0 1 0,0 1 0,1 1 1]; % A2=imdilate(bw2,B);%图像A1被结构元素B膨胀 % subplot(235),imshow(A2);title('使用B后1次膨胀后的图像'); % % BW1 = edge(A2,'sobel'); % %prewitt图像边缘提取 % subplot(236),imshow(BW1);title('sobel算子'); %%水平投影 % [m,n] = size(J); % for x = 1:m % S(x) = sum(J(x,:)); % end % x = 1:m; % %figure(2) % subplot(224);plot(x,S(x)); % title('水平投影'); % y = S(x); % IndMin=find(diff(sign(diff(y)))>0)+1; % IndMax=find(diff(sign(diff(y)))<0)+1; % plot(1:length(y),y); % hold on;grid on; % plot(IndMin,y(IndMin),'r^'); % plot(IndMax,y(IndMax),'k*'); %legend('曲线','波谷点','波峰点') %标注