计算机视觉实验5形态学滤波实验报告

1、Experiment 4：Thresholding & mathematical morphology 王影 电子1203班 学号：. AimThe aim of this laboratory session is to learn to deal with image data by Matlab. By the end of this session, you should be able to perform image preprocessing of thresholding and mathematical morphology. Knowledge required in th

2、e Experiment.You are supposed to have learned the basic skills of using Matlab;.You need to review Matlab programming language and M-file format. You should have studied image segmentation and mathematical morphology methods. Experiment Contents.Read “bac.bmp” file (to do this by imread function), c

3、onvert the color image into grayscale image, and then perform thresholding by auto threshoding method using “while loop” and display the results in a Matlab window.程序：%Iterative thresholdiclear all;im=imread(bac.bmp); subplot(1,2,1);imshow(im); title(Gray image);Y X=size(im);S=sum(sum(im);S=S/(X*Y);

4、D=0.1;T=0;im_bi=imS;while(abs(S-T)D) im1=double(im_bi).*double(im); im2=double(abs(1-im_bi).*double(im); S1=sum(sum(im1)/sum(sum(im_bi); S2=sum(sum(im2)/sum(sum(abs(1-im_bi); T=S; S=(S1+S2)/2; im_bi=imS;end subplot(1,2,2);imshow( im_bi);title(image after Auto_thresholding); . Read “bw_bac.bmp” file

5、and “bw_bac2.bmp”(to do this by imread function), perform mathematical morphology to fill the small holes in objects and display the results in a Matlab window.腐蚀：mask=1 1 1;1 1 1;1 1 1;im=imread(bw_bac.bmp);figure(1)subplot(1,2,1);imagesc(im);colormap(gray);Y,X=size(im);im_new=zeros(Y,X);T=sum(sum(

6、mask);for kk=2:Y-1 for k=2:X-1 %Calculating sigma imblock=im(k-1:k+1,kk-1:kk+1); sigma=sum(sum(imblock&mask); if sigma 0 im_new(i,j)=1; else im_new(i,j)=im(i,j); end endendsubplot(1,2,2)imagesc(im_new);colormap(gray);iii. Read “Plate.jpg” file, convert the color image into gray scale image, then per

7、form thresholding & mathematical morphology operation, display the results in Matlab window.程序：clear;I=imread(Plate.JPG); im=rgb2gray(I);subplot(3,2,1);imshow(im); title(Gray image);Y X=size(im);S=sum(sum(im);S=S/(X*Y);D=0.1;T=0;im_bi=imS;while(abs(S-T)D) im1=double(im_bi).*double(im); im2=double(ab

8、s(1-im_bi).*double(im); S1=sum(sum(im1)/sum(sum(im_bi); S2=sum(sum(im2)/sum(sum(abs(1-im_bi); T=S; S=(S1+S2)/2; im_bi=imS;end subplot(3,2,2);imshow( im_bi);title(image after Auto_thresholding);mask=1 1 1;1 1 1;1 1 1;im_new=zeros(Y,X);T=sum(sum(mask);for kk=2:X-1 for k=2:Y-1 imblock=im_bi(k-1:k+1,kk-1:kk+1); sigma=sum(sum(imblock&mask); if s