diff options
Diffstat (limited to 'SD-VBS/common/toolbox/toolbox_basic/textons/find_textons.m')
-rwxr-xr-x | SD-VBS/common/toolbox/toolbox_basic/textons/find_textons.m | 46 |
1 files changed, 46 insertions, 0 deletions
diff --git a/SD-VBS/common/toolbox/toolbox_basic/textons/find_textons.m b/SD-VBS/common/toolbox/toolbox_basic/textons/find_textons.m new file mode 100755 index 0000000..e7fa4b0 --- /dev/null +++ b/SD-VBS/common/toolbox/toolbox_basic/textons/find_textons.m | |||
@@ -0,0 +1,46 @@ | |||
1 | function [centers,label,post,d2]=find_textons(FIw,ncenters,centers_in,n_iter); | ||
2 | % [centers,label,post,d2]=find_textons(FIw,ncenters,centers_in,n_iter); | ||
3 | % | ||
4 | % find textons using kmeans for windowed portion FIw of filtered image | ||
5 | % | ||
6 | % to start with centers pulled randomly from image, set centers_in=[] | ||
7 | |||
8 | % define number of textons | ||
9 | %ncenters=25; | ||
10 | |||
11 | [N1,N2,N3]=size(FIw); | ||
12 | % reshape filtered image stack into a long array of feature vectors | ||
13 | fv=reshape(FIw,N1*N2,N3); | ||
14 | % (each row is a feature vector) | ||
15 | |||
16 | %centers=.01^2*randn(ncenters,N3); | ||
17 | % take centers randomly from within image | ||
18 | if isempty(centers_in) | ||
19 | rndnum=1+floor(N1*N2*rand(1,ncenters)); | ||
20 | centers_in=fv(rndnum,:); | ||
21 | end | ||
22 | |||
23 | options = foptions; | ||
24 | options(1)=1; % Prints out error values. | ||
25 | options(5) = 0; | ||
26 | if nargin<4 | ||
27 | n_iter=15; | ||
28 | end | ||
29 | options(14) = n_iter; % Number of iterations. | ||
30 | |||
31 | [centers,options,d2,post]=kmeans2(centers_in,fv,options); | ||
32 | |||
33 | % reshuffle the centers so that the one closest to the origin | ||
34 | % (featureless) comes last | ||
35 | norms=sum(centers.^2,2); | ||
36 | [sortval,sortind]=sort(-norms); | ||
37 | centers=centers(sortind,:); | ||
38 | d2=reshape(d2,N1,N2,ncenters); | ||
39 | post=reshape(post,N1,N2,ncenters); | ||
40 | d2=d2(:,:,sortind); | ||
41 | post=post(:,:,sortind); | ||
42 | |||
43 | |||
44 | % retrieve cluster number assigned to each feature vector | ||
45 | [minval,label]=min(d2,[],3); | ||
46 | |||