3. Introduction
It
classify face images using k-means.
It performs some process to many images, and
classifies into three classes using the k-means.
It performs morphing using the image of each
class.
image1
image2
middle image
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4. Method
The file of 200 image data is selected and
loaded.
2. The image is normalized, and it converts it to
the gray and mosaic.
3. Each image is converts to the feature vector.
4. It classifies these feature vectors into three
classes using k-means.
1.
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5. Method (Cont.)
5. It sorts it in ascending order for each class.
6. In experiment 1, it performs morphing two
images difference in luminance value in each
class.
7. In experiment 2, it chooses one image from
each class, and performs morphing two
images.
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6. Result – Experiment 1
Processing time : 3.5[s]
These three images are the face image made most
throughout the experiment.
We repeated many times the experiment, however, the
result was alomost these three images.
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7. Result – Experiment 2
Processing time : 3.5[s]
It is an unnatural image because there are images made
by the image that does not look like.
It made several images others, however, these three
images were more unnatural images.
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8. Discussion
In
experiment 1, it made a natural face image
as a whole. Since the result is not changed
even though repeating the experiment, the
result is stable even with the k-means method.
Image
made of experiment 2 was a very
unnatural image because contour of the face
was not match and there was a shadow.
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