Page 163 - Algorithm Collections for Digital Signal Processing Applications using MATLAB

152 Chapter 4

4.2 M-program for Binary Image Rotation
with 45 Degree Anticlockwise Direction

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binimrotationgv.m

A=imread(selectfig8','bmp');
TM=[0.7071 0.7071;-0.7071 0.7071];
[X Y]=find(A==0);
VECT=[X Y];
TRANSVECT=TM*VECT';
TRANSVECT=round(TRANSVECT-min(min(TRANSVECT))+1);
m=max(max(TRANSVECT));
B=ones (m, m);
for k=1:1:length(TRANSVECT)
B(TRANSVECT(1,k),TRANSVECT(2,k))=0;
end
figure
subplot(2,1,1)
imshow(A)
title('ORIGINAL IMAGE')
subplot(2,1,2)
imshow(B)
title('IMAGE AFTER 45 degree ROTATION')
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5. CLUSTERING TEXTURE IMAGES USING
K-MEANS ALGORITHM

To retrieve the similar images from the database, sample image looking like

the same is used as the key. The low level features extracted from the key
ima ge is used as the index for searching. So the data base has to be

maintained based on the low level feature vectors derived from the images.