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Abstract:
A new algorithm is presented which approximates the perceived
visual similarity between images. The images are initially
transformed into a feature space which captures visual structure,
texture and color using a tree of filters. Similarity is the
inverse of the distance in this perceptual feature space. Using
this algorithm we have constructed an image database system which
can perform example based retrieval on large image databases. Using
carefully constructed target sets, which limit variation to only a
single visual characteristic, retrieval rates are quantitatively
compared to those of standard methods.
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