Question

跪求matlab程序代码 关于医学图像分割处理 边缘检测 阈值法

Answer 1

图像分割程序：
% This is a program for extracting objects from an image. Written for vehicle number plate segmentation and extraction
% Authors : Jeny Rajan, Chandrashekar P S
% U can use attached test image for testing
% input - give the image file name as input. eg :- car3.jpg
clc;
clear all;
k=input('Enter the file name','s'); % input image; color image
im=imread(k);
im1=rgb2gray(im);
im1=medfilt2(im1,[3 3]); %Median filtering the image to remove noise%
BW = edge(im1,'sobel'); %finding edges
[imx,imy]=size(BW);
msk=[0 0 0 0 0;
0 1 1 1 0;
0 1 1 1 0;
0 1 1 1 0;
0 0 0 0 0;];
B=conv2(double(BW),double(msk)); %Smoothing image to reduce the number of connected components
L = bwlabel(B,8);% Calculating connected components
mx=max(max(L))
% There will be mx connected components.Here U can give a value between 1 and mx for L or in a loop you can extract all connected components
% If you are using the attached car image, by giving 17,18,19,22,27,28 to L you can extract the number plate completely.
[r,c] = find(L==17);
rc = [r c];
[sx sy]=size(rc);
n1=zeros(imx,imy);
for i=1:sx
x1=rc(i,1);
y1=rc(i,2);
n1(x1,y1)=255;
end % Storing the extracted image in an array
figure,imshow(im);
figure,imshow(im1);
figure,imshow(B);
figure,imshow(n1,[]);

边缘检测：
I=imread('lena.jpg');
imshow(I);
title('原始图像');
BW1= edge(I,'Canny',0.00) ; %edge调用Canny为检测算子判别阈值为0.00
figure,imshow(BW1);
title( '阈值为0.00的Canny算子边缘检测图像 ');
BW2= edge(I,'Canny',0.05) ; %edge调用Canny为检测算子判别阈值为0.05
figure,imshow(BW2);
title( '阈值为0.05的Canny算子边缘检测图像');
BW20= edge(I,'Canny',0.1) ; %edge调用Canny为检测算子判别阈值为0.1
figure,imshow(BW20);
title( '阈值为0.1的Canny算子边缘检测图像');
BW21= edge(I,'Canny',0.2) ; %edge调用Canny为检测算子判别阈值为0.2
figure,imshow(BW21);
title( '阈值为0.2的Canny算子边缘检测图像 ');
BW22= edge(I,'Canny',0.3) ; %edge调用Canny为检测算子判别阈值为0.3
figure,imshow(BW22);
title( '阈值为0.3的Canny算子边缘检测图像 ');