Abstract
We propose a novel algorithm for high-quality data embedding in audio. The algorithm is based on changing the relative length of the middle segment between two successive maximum and minimum peaks to embed data. Spline interpolation is used to change the lengths. To ensure smooth monotonic behavior between peaks, a hybrid orthogonal and nonorthogonal wavelet decomposition is used prior to data embedding. The possible data embedding rates are between 20 and 30 bps. However, for practical purposes, we use repetition codes, and the effective embedding data rate is around 5 bps. The algorithm is invariant after time-scale modification, time shift, and time cropping. It gives high-quality output and is robust to mp3 compression.
Highlights
We introduce a new algorithm for high-capacity data embedding in audio that is suited for marketing, broadcast, and playback monitoring applications
The proposed algorithm is designed to be transparent and robust to most common signal processing operations. It is automatically invariant under time-scale modification (TSM), which is the most severe attack to most data embedding algorithm
In [8], long sequences of zeros or ones are cut by employing high-density bipolar coding (HDBn) scheme in digital communication to add a bit of reverse polarity to a long sequence of similar bits
Summary
We introduce a new algorithm for high-capacity data embedding in audio that is suited for marketing, broadcast, and playback monitoring applications. The embedded data should survive basic operations that the host audio signal may undergo. The decoding is done by quantizing the watermarked signal and deciding the symbol that corresponds to the codebook with minimum quantization error Examples of this technique are described in [6, 7]. We propose a new embedding algorithm that is automatically robust to most synchronization attacks that the signal may undergo. The proposed algorithm is designed to be transparent and robust to most common signal processing operations. It is automatically invariant under time-scale modification (TSM), which is the most severe attack to most data embedding algorithm.
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