On Mon, Jun 23, 2008 at 6:08 AM, Casimir <pikEISPAMMMseli / welho.com> wrote:
> Axel Etzold wrote on Thu, 19 Jun 2008 20:33:43 +0900
>
>> well, what does similarity of two images/textures mean for you ?
>
> Perceptual similarity as a human subject would experience it. Let me expand
> (=ramble) on this:
>
> At the moment I am focusing on following the problem: Given any single
> photograph and a random set of photos (20-100), which of the random set is
> most similar, perceptually, to the target photo.
>
> I have made some simple tests that divide image into color-channel
> components and a luminosity channel, downsample the channels into a 16x16
> arrays, and calculates the difference between the target photo to each of
> the random ones. Difference hashing its called?
>
> Results are rather confusing. Most of the time perceived similarity (as I
> experience it) does not exist, even if statistically the images might be
> similar.
....
> What kind of computational algorithm would provide the perceptual similarity
> score, rating or hash of some kind between two or more images that would
> match the way humans perceive best?

If I'm recalling properly, a lot of research has had success doing
histogram comparison.  More or less it's showing images being similar
based on similar color composition.  That sounds silly, but in reality
it's quite effective for a first go at it.

You mention a training library, and since a good deal of computer
vision is still crossing over from AI, an important question becomes,
what type of system will be doing the learning?



--Kyle