Content based searching of multimedia Databases using approximate digital signatures

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.