Usually, surface roughness are measured with stylus type instrument which gives idea of roughness about thin line that should not be the roughness of whole surface.
I think 2d Fourier transform of image of the surface illuminated
with a single wavelength light source would yield information for classifying
the results. I expect rougher surfaces to produce more scatter and smoother surface
to reproduce source image more closely as in a mirror.
please see attached pdf using scilab 5.3.3 as a possible method . It is just a suggestion . I have not tried it on any real case but I think it might lead you to some good results .
what you need to do is
1 just capture the image of two surfaces ( even with a mobile/web
camera using ordinary incandescent bulb.. but adjust the shutter speed / aperture
to limit max intensity within range .or some dark film as filter.)
2. Store the image as say .bmp file
3. Convert to b/w image see code..
4. Think of using some metric to identify the distance between
ideal smooth surface (constant pixel values ) and test matrix
some normalization may be required.
cheers
An increase in the surface leads usually to an increase in the surface roughness , neverteless this increase is not necessarily equivalent from one area to anther .
You can sum the roughness rms of each lines measured by your stylus and divided by the number N of lines on length L .
then plot the rms as a function of N. This will give you an idea of the dependance of the RMS with the surface.
cheers
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