A number of different multimedia fingerprinting algorithms and identification techniques were proposed and analyzed recently. This paper presents a content identification setup for a class of multimedia data that can be modeled by the Gauss-Markov process. We advocate a constrained order statistics decoding scheme based on digital fingerprints extracted from correlated data to identify contents. Finally, we investigate the fundamental limits of the proposed setup by deriving bounds on the miss and false acceptance probabilities.
|Title of host publication||2011 IEEE Information Theory Workshop (ITW)|
|Place of Publication||Paraty, Brazil|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 2011|