October 2013
Beginner to intermediate
350 pages
13h 7m
English
Content preview from Feature Extraction and Image Processing
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332 Feature Extraction and Image Processing
This gives the famous bell-shaped function shown here for a 19 19 window with a
standard deviation of 4. Try changing the standard deviation from 4 to, say, 2 and 8 so you
can see its effect on the width.
Gaussian_template (19, 4)
So let’s apply it: Gaussian_smoothed:=tm_conv(eye,Gaussian_template
(3,0.8))
And the result is:
normalise (Gaussian_smoothed)
This can keep much more detail concerning image features; note here its ability to retain
detail in the eye region which was lost in the earlier direct averaging. Again, it can be
implemented in the frequency domain, as can any template convolution process.
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