【图像分割】基于matlab C-V模型水平集图像分割【含Matlab源码 1456期】

一、获取代码方式

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二、图像分割简介

理论知识参考：【基础教程】基于matlab图像处理图像分割【含Matlab源码 191期】

三、部分源代码

%   Matlad code implementing Chan-Vese model in the paper 'Active Contours Without Edges'
%  
clear all;
close all;
Img=imread('Head.bmp');   
% Img=imread('vessel3.bmp'); % Note: this an example of images with intensity inhomogeneity. 
                             % CV model does not work for this image. 
Img=double(Img(:,:,1));

% get the size
[nrow,ncol] =size(Img);

ic=nrow/2;
jc=ncol/2;
r=10;  %起始园半径
initialLSF = sdf2circle(nrow,ncol,ic,jc,r);
u=initialLSF;


numIter = 200;
timestep = 0.5;
lambda_1=1;
lambda_2=1;
% h = 1;
h = 1;
epsilon=1;
nu = 0.001*255*255;  % tune this parameter for different images

% figure;
% imagesc(Img,[0 255]);colormap(gray)
% hold on;
% contour(u,[0 0],'r');


% start level set evolution
% for k=1:numIter
%     u=EVOL_CV(Img, u, nu, lambda_1, lambda_2, timestep, epsilon, 1);   % update level set function
%     if mod(k,10)==0
%         pause(.1);
%         imagesc(Img,[0 255]);colormap(gray)
%         hold on;
%         contour(u,[0 0],'r');
%         hold off;
%     end    
% end;

% start level set evolution
% figure;
% imagesc(Img, [0, 255]);colormap(gray);hold on;
% contour(u,[0 0],'r');                          
% title('Initial contour');   

for k=1:numIter
    u=EVOL_CV(Img, u, nu, lambda_1, lambda_2, timestep, epsilon, 1);   % update level set function
    if mod(k,10)==0
        pause(.1);
        imagesc(Img,[0 255]);colormap(gray)
         hold on;
        contour(u,[0 0],'r'); 
        iterNum=[num2str(k), ' iterations'];        
        title(['process of evolution,',iterNum]);
        hold off;
    end    
end;

figure;
imagesc(Img, [0, 255]);colormap(gray);hold on;
contour(u,[0 0],'r'); 
totalIterNum=[num2str(k), ' iterations'];  
title(['Final contour, ', totalIterNum]);
function [C1,C2]= binaryfit(Img,H_phi) 
%   [C1,C2]= binaryfit(phi,U,epsilon) computes c1 c2 for optimal binary fitting 
%   input: 
%       Img: input image
%       phi: level set function
%       epsilon: parameter for computing smooth Heaviside and dirac function
%   output: 
%       C1: a constant to fit the image U in the region phi>0
%       C2: a constant to fit the image U in the region phi<0
%  
%   Author: Chunming Li, all right reserved
%   email: li_chunming@hotmail.com
%   URL:   http://www.engr.uconn.edu/~cmli/research/

a= H_phi.*Img;
numer_1=sum(a(:)); 
denom_1=sum(H_phi(:));
C1 = numer_1/denom_1;

b=(1-H_phi).*Img;
numer_2=sum(b(:));
c=1-H_phi;
denom_2=sum(c(:));
C2 = numer_2/denom_2;
function f = sdf2circle(nrow,ncol, ic,jc,r)
%   sdf2circle(nrow,ncol, ic,jc,r) computes the signed distance to a circle
%   input: 
%       nrow: number of rows
%       ncol: number of columns
%       (ic,jc): center of the circle
%       r: radius of the circle
%   output: 
%       f: signed distance to the circle
%  
%   created on 04/26/2004
%   author: Chunming Li
%   email: li_chunming@hotmail.com
%   Copyright (c) 2004-2006 by Chunming Li


[X,Y] = meshgrid(1:ncol, 1:nrow);

f = sqrt((X-jc).^2+(Y-ic).^2)-r;

%f=sdf2circle(100,50,51,25,10);figure;imagesc(f)



  

 

  
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四、运行结果

五、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1] 蔡利梅.MATLAB图像处理——理论、算法与实例分析[M].清华大学出版社，2020.
[2]杨丹,赵海滨,龙哲.MATLAB图像处理实例详解[M].清华大学出版社，2013.
[3]周品.MATLAB图像处理与图形用户界面设计[M].清华大学出版社，2013.
[4]刘成龙.精通MATLAB图像处理[M].清华大学出版社，2015.
[5]赵勇,方宗德,庞辉,王侃伟.基于量子粒子群优化算法的最小交叉熵多阈值图像分割[J].计算机应用研究. 2008,(04)

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