实验 四 图像分割与边缘检测.docx

实验 四 图像分割与边缘检测 一实验目的及要求1利用MATLAB研究图像分割与边缘检测的常用算法原理；2掌握MATLAB图像域值分割与边缘检测函数的使用方法；3了解边缘检测的算法和用途，比较Sobel、Prewitt、Canny等算子边缘检测的差异。二、实验内容（一）研究以下程序，分析程序功能；输入执行各命令行，认真观察命令执行的结果。熟悉程序中所使用函数的调用方法，改变有关参数，观察试验结果。1图像阈值分割clear all, close all;I = imread(cameraman.tif);figure (1),imshow(I)figure(2); imhist(I)T=120/255;Ibw1 = im2bw(I,T); figure(3);subplot(1,2,1), imshow(Ibw1);T=graythresh(I); L = uint8(T*255)Ibw2 = im2bw(I,T); subplot(1,2,2), imshow(Ibw2);help im2bw;help graythresh;clear all, close all;I = imread(cameraman.tif);figure (1),imshow(I)figure(2); imhist(I)T=240/255;Ibw1 = im2bw(I,T); figure(3);subplot(1,2,1), imshow(Ibw1);T=graythresh(I); L = uint8(T*255)Ibw2 = im2bw(I,T); subplot(1,2,2), imshow(Ibw2);help im2bw;help graythresh;clear all, close all;I = imread(cameraman.tif);figure (1),imshow(I)figure(2); imhist(I)T=120/255;Ibw1 = im2bw(I,T); figure(3);subplot(1,2,1), imshow(Ibw1);T=graythresh(I); L = uint8(T*255)Ibw2 = im2bw(I,T); subplot(1,2,2), imshow(Ibw2);help im2bw;help graythresh;2边缘检测clear all, close all;I = imread(moon.tif);BW1 = edge(I,sobel);BW2 = edge(I,canny);BW3 = edge(I,prewitt);BW4 = edge(I,roberts);BW5 = edge(I,log);figure(1), imshow(I), title(Original Image);figure(2), imshow(BW1), title(sobel);figure(3), imshow(BW2), title(canny);figure(4), imshow(BW3), title(prewitt);figure(5), imshow(BW4), title(roberts);figure(6), imshow(BW5), title(log);help edgeedgedemo（二）利用MATLAB熟悉并验证其它图像分割方法灰度阈值分割：I=imread(C:UsersAdministratorDesktoprice.jpg); I=rgb2gray(I); I2=im2bw(I); figure,imshow(I2); I2=im2bw(I,140/255); figure,imshow(I2) 区域分割法：I=imread(eight.tif); imshow(I) c=222 272 300 270 221 194; r=21 21 75 121 121 75; BW=roipoly(I,c,r); figure,imshow(BW) H=fspecial(unsharp); J1=roifilt2(H,I,BW); figure,imshow(J1) J2=roifill(I,c,r); figure,imshow(J2) 分水岭分割法：f=imread(C:UsersAdministratorDesktopcell.jpg); imshow(f); g=im2bw(f, graythresh(f); figure,imshow(g); gc=g; D=bwdist(gc); L=watershed(-D); w=L=0; g2=g&w; figure,imshow(g2)（三）采用MATLAB编程实现自动全局阈值算法，对图像rice.tif进行二值化分割算法步骤：1）选取一个的初始估计值T；2）用T分割图像。这样便会生成两组像素集合：G1由所有灰度值大于 T 的像素组成，而G2由所有灰度值小于或等于 T 的像素组成。3）对G1和G2中所有像素计算平均灰度值m1和m2。4）计算新的阈值： T =(m1+m2)/25）重复步骤（2）到（4），直到逐次迭代所得到的 T 值之差小于一个事先定义的参数To，即，如果 |Tn Tn-1|To ，则停止。clc;clear all; I=imread(C:UsersAdministratorDesktoprice.gif);I=double(I)/255; k1=(max(max(I)+min(min(I)/2; rows cols=size(I); count1=0; count2=0; for i=1:rows for j=1:cols if I(i,j)(5/255) k1=k2; count1=0; count2=0; for i=1:rows for j=1:cols if I(i,j)k1 count1=count1+1; G1(count1).I=I(i,j); else count2=count2+1; G2(count2).I=I(i,j); end end end k2=(mean(mean(G1.I)+mean(mean(G2.I)/2; end figure(1);imshow(I); figure(2);II=im2bw(I,k2);imshow(II);三、实验设备1计算机；2MATLA