Understanding Voronoi Skeleton and extract the Algorithm ?
2 views (last 30 days)
Show older comments
Can any one help me to extract the Algorithm of the Voronoi Skeleton code below in order to understand it:
function [skel v e]=squelette(BW,varargin)
iptcheckinput(BW,{'numeric' 'logical'},{'real' 'nonsparse' '2d'}, ...
mfilename, 'BW', 1);
trim=0;
factor=-1;
boundary=false;
for i=1:length(varargin)
switch lower(varargin{i})
case 'trim'
trim=varargin{i+1};
case 'fast'
factor=varargin{i+1};
case 'boundary'
boundary=true;
if nargout~=2
error(['If boundary is specified, the function cannot
generate'...
char(10) 'the BW inage of the skeleton.' char(10)...
'Use [v e]=voronoiSkel(...) instead'])
end
if size(BW,2)~=2
if size(BW,1)~=2
error('If you use the ''boundary'' option, the imput must
be a 2 x n or n x 2 matrix')
else
BW=BW';
end
end
end
end
if trim<1; trim=pi; end
if factor<0; factor=1; end;
if ~islogical(BW) && ~boundary
BW = (BW ~= 0);
end
%construct voronoi
if ~boundary
b=bwboundaries(BW);
else
b={BW};
end
if factor>1
for i=1:length(b)
inds=round(1:factor:size(b{i},1));
b{i}=b{i}(inds,:);
end
end
i=1;
inds=[];
while i<=length(b)
if size(b{i},1)<4
b(i)=[];
continue;
end
inds(i)=length(b{i}); %#ok<AGROW>
i=i+1;
end
inds=[0 cumsum(inds)];
p=cell2mat(b);
[v e]=costumVoronoi(p);
%clear bad vertices (bv) which are outside of the object.
if ~boundary
rv=round(v);
M=max(p);
m=min(p);
bv=v(:,1)<m(1)|v(:,1)>M(1)|v(:,2)>M(2)|v(:,2)<m(2);
bv2=find(~bv);
tmp=sub2ind(size(BW),rv(bv2,1),rv(bv2,2));
bv2(BW(tmp))=[];
bv=[find(bv); bv2];
else
bv=find(~inpolygon(v(:,1),v(:,2),p(:,1),p(:,2)));
end
be=ismember(e(:,3),bv)|ismember(e(:,4),bv);
e=e(~be,:);
clear bv2 m M rv tmp;
% build distance table
D=cell(size(b));
for i=1:length(D);
tmp=diff(b{i});
tmp=sqrt(sum(tmp'.^2)');
D{i}=[0 ;cumsum(tmp)];
end
% trim
be=false(size(e,1),1);
for i=1:size(e,1)
i1=find(inds>=e(i,1),1,'first')-1;
i2=find(inds>=e(i,2),1,'first')-1;
if i1~=i2; continue; end;
offset=inds(i1);
contourDistance=abs(D{i1}(e(i,1)-offset)-D{i1}(e(i,2)-offset));
contourDistance=min(contourDistance,D{i1}(end)-contourDistance);
realDistance=norm(p(e(i,1),:)-p(e(i,2),:));
if (contourDistance<realDistance*trim)
be(i)=1;
end
end
% keep only good edges
e=e(~be,3:4);
outputVertices=(nargout>1);
outputSkel=(nargout~=2);
if (outputSkel)
skel=false(size(BW));
for i=1:size(e);
v1=v(e(i,1),:);
v2=v(e(i,2),:);
t=linspace(0,1,max(ceil(1.3*norm(v2-v1)),4));
x=v1(:,1).*t+(1-t).*v2(:,1);
y=v1(:,2).*t+(1-t).*v2(:,2);
inds=unique(round([x' y']),'rows');
skel(sub2ind(size(skel),inds(:,1),inds(:,2)))=1;
end
end
if outputVertices
tmp=1:length(v);
tmp=~ismember(tmp,e(:,1:2));
inds=cumsum(tmp);
e(:,1)=e(:,1)-inds(e(:,1))';
e(:,2)=e(:,2)-inds(e(:,2))';
v=v(~tmp,:);
end
if nargout==2
skel=v;
v=e;
end
end
function [v e]=costumVoronoi(V)
% Calculates the voronoi diagram of the vertices in V.
% v should be a n x 2 real matrix.
% qhull (www.qhull.org) MUST be executable from the current directory.
%
% Output: v is the matrix of the Voronoi vertices.
% e is the matrix of the Voronoi edges.
% each row of e represents an edge in the following way:
% e(k,[1 2]) are the row indices (in V) of the points which
% generated the k-th edge.
% e(k,[3 4]) are the row indices (in v) of the endpoints of the
% k-th edge.
%
% write to temp file
namein=tempname;
fid=fopen(namein,'w');
fprintf(fid,'%d\n%d\n',2,size(V,1));
fprintf(fid,'%d %d\n',V');
fclose(fid);
[a s]=dos(['qhull v p Fv TI ' namein]);
if (a~=0)
delete(namein);
error(['qhull returned an error:' char(10) s]);
end
[junk s]=strtok(s);
[Nv s]=strtok(s);
Nv=str2double(Nv);
[v pos]=textscan(s,'%f %f',Nv);
v=cell2mat(v);
s=s(pos:end);
[Ne s]=strtok(s);
e=double(cell2mat(textscan(s,'%d %d %d %d %d',Ne)));
e=e(:,2:5);
e(:,1:2)=e(:,1:2)+1;
e(e(:,3)==0,:)=[];
e(e(:,4)==0,:)=[];
%clean up
delete(namein);
end
i'm new with matlab
Help is much appreciated
thank you !
0 Comments
Accepted Answer
Walter Roberson
on 4 Feb 2014
The routine costumVoronoi calls qhull which does the major part of the work.
More Answers (0)
See Also
Categories
Find more on Voronoi Diagram in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!