KEYWORDS: Binary data, Databases, Multimedia, Image retrieval, Feature extraction, Data modeling, RGB color model, Systems modeling, Error control coding, Computing systems
We propose the use of approximate digital signatures of selected
multimedia feature vectors for fast content based retrieval in
very large multimedia databases. We adapt and extend the
Approximate Message Authentication Code (AMAC), introduced by some
of the authors recently in the area of message authentication, to
the multimedia searching problem. An AMAC is a binary signature
with the ability to reflect changes in the message it represents.
The hamming distance between two AMACs is used to measure the
degree of the similarity between multimedia objects. We develop a
method to compress AMAC signatures to create a direct lookup table
that allows fast searching of a database. The color histogram is
used as the example feature space to show how the signature is applied. Experimental results show that the performance of the
proposed method is comparable with existing methods based on other
popular metrics, but significantly decreases search
time.
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