Audio Watermarking and Fingerprinting: For Which Applications?

Abstract

Although not a new issue, music piracy has acquired a new status in the digital era, as recordings can be easily copied and distributed. Watermarking has been proposed as a solution to this problem. It consists in embedding into the audio signal an inaudible mark containing copyright information. A different approach, called fingerprinting, consists in extracting a "fingerprint" from the audio signal. In association with a database, this fingerprint can be used to identify a recording, which is useful, for example, to monitor audio excerpts played by broadcasters and webcasters. There are far more applications to watermarking and fingerprinting. After a brief technical review, this article describes potential applications of both methodologies, showing which one is more suitable for each application.

Radon transform and DWT based audio watermarking algorithm against DA/AD conversion

“…The instantaneous frequency at time 0 is 0 F Hertz. The instantaneous frequency 1 F is achieved at time 1 T . Step4: Combined with step (1) ~ step (3), before adding the watermarking bits, we add the chirp signal into wavelet subband coefficients:…”

“…In other words, if two points in the waveform are chosen, 1 t and 2 t , and the time interval between them 2 1 t t − is kept constant, the frequency ratio ( ) ( ) 2 1 f t f t will also be constant.…”

“…Through the common computer network and audio device, Gomes [1] realized a watermarking technology in point-to-point voice secure communication. Hering [2] carried out one watermarking system in air traffic management for secure communication.…”

“…the result R is a column vector containing the Radon transform for θ degrees. Here, the θ is a vector, the 1 R and 2 R is a matrix in which each column is the Radon transform for one of the angles inθ 1. xp and 2 xp is vector containing the radial coordinates corresponding to each row of 1 R and 2 R .…”

“…xp and 2 xp is vector containing the radial coordinates corresponding to each row of 1 R and 2 R . Step6: Calculate the statistical moment of radon transform used equation(9), denoted by1 M and 2 M . Then the new chirp signal is generated by Step 3 as to be added in wavelet coefficients…”