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From: ImageAnalyst <imageanalyst@mailinator.com>
Newsgroups: comp.soft-sys.matlab
Subject: Re: How to find similar images
Date: Sat, 29 Nov 2008 07:15:28 -0800 (PST)
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On Nov 29, 9:29=A0am, "akshu " <akkire...@gmail.com> wrote:
> Hey if u got ans 4 this ans this than plzzzzz reply me........Akshu
>
>
>
> "Yair Altman" <altmany...@gmailDEL.comDEL> wrote in message <f9dggq$lu...=
@fred.mathworks.com>...
> > I have a large set of color images. I wish to find a
> > characteristic number for each of them, so closer numbers
> > would represent "similar" images (in very loose terms). I'd
> > like the characteristic to be tolerant to cropping &
> > resizing and if possible also to rotation, flipping &
> > saturation. If possible, I'd also like it to be computed
> > quickly (my set is very large).
>
> > The ultimate aim is to winnow down the large set to a much
> > smaller subset of potential matching images, that would then
> > be inspected manually.
>
> > Some simple functions that I thought of were the grayscale
> > rms/mode/std/kurtosis/skewness. Could anyone please comment
> > on which of these functions (or any other) would be best for
> > my needs?
>
> > (I'm not an imaging expert nor have the Image Processing
> > Toolbox...)
>
> > Thanks in advance,
> > Yair- Hide quoted text -
>
> - Show quoted text -

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akshu:
This is a whole field of research called "content based image
retrieval."
You might take a look at these links:
http://www.tasi.ac.uk/resources/searchengines.html  - A review of
image search engines and algorithms.
http://tinyurl.com/6f8vfs
Essentially you need to make up a "feature vector" that lists a bunch
of data that describes your data.  Then you need to define some kind
of distance metric and return all images with feature vectors that are
within this distance of your example image.
Regards,
ImageAnalyst