Abstract: A system and a method of effectively detecting watermarks in a significant amount of data signals. The method, in overview, consists in pre-filtering the significant amount of data signals in order to eliminate from the final watermark detection the segments of the data signals which have no significant relevance to the owner of the copyrights of the watermark under investigation, and then performing the actual watermark detection over the remaining segments of data signals relevant to the investigation. The pre-filtering feature being implemented by a definition of one or more goal descriptors, extraction of one or more descriptors from the data signals and its content and a comparison between goal descriptors and extracted descriptors.

Abstract: A lossless, reversible data embedding technique uses a generalization of least-significant-bit modification. The portions of the signal that are susceptible to embedding distortion are compressed and sent as part of the embedded payload. A prediction-based conditional entropy coder uses unaltered portions of the host signal to improve lossless data capacity.

Abstract: A lossless, reversible data embedding technique uses a generalization of least-significant-bit modification. The portions of the signal that are susceptible to embedding distortion are compressed and sent as part of the embedded payload. A prediction-based conditional entropy coder uses unaltered portions of the host signal to improve lossless data capacity.