基于随机游走算法的图像分割
基于随机游走算法的图像分割：代码经过，提炼抽取，请参考百度网盘：链接：https://pan.baidu.com/s/1Se-Rd7ccDk4gzH4PkO4OLw 提取码：t09e function = random_walker(img,seeds,labels,beta)
%
%Available at: http://www.cns.bu.edu/~lgrady/grady2006random.pdf
%
%Note: Requires installation of the Graph Analysis Toolbox available at:
%http://eslab.bu.edu/software/graphanalysis/
%Find image size
img=im2double(img);
=size(img);
%Build graph
=lattice(X,Y);
% save data.mat points edges
%Generate weights and Laplacian matrix
if(Z > 1) %Color images
tmp=img(:,:,1);
imgVals=tmp(:);
tmp=img(:,:,2);
imgVals(:,2)=tmp(:);
tmp=img(:,:,3);
imgVals(:,3)=tmp(:);
else
imgVals=img(:);
end
weights=makeweights(edges,imgVals,beta);
L=laplacian(edges,weights);
%L=laplacian(edges,weights,length(points),1);
%Determine which label values have been used
label_adjust=min(labels); labels=labels-label_adjust+1; %Adjust labels to be > 0
labels_record(labels)=1;
labels_present=find(labels_record);
number_labels=length(labels_present);
%Set up Dirichlet problem
boundary=zeros(length(seeds),number_labels);
for k=1:number_labels
boundary(:,k)=(labels(:)==labels_present(k));
end
%Solve for random walker probabilities by solving combinatorial Dirichlet
%problem
probabilities=dirichletboundary(L,seeds(:),boundary);
%Generate mask
=max(probabilities,[],2);
mask=labels_present(mask)+label_adjust-1; %Assign original labels to mask
mask=reshape(mask,);
probabilities=reshape(probabilities,);
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