Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Robust audio watermarking using perceptual masking
Signal Processing
Information Hiding Techniques for Steganography and Digital Watermarking
Information Hiding Techniques for Steganography and Digital Watermarking
Speech authentication system using digital watermarking and pattern recovery
Pattern Recognition Letters
A temporal domain audio watermarking technique
IEEE Transactions on Signal Processing
A Novel Synchronization Invariant Audio Watermarking Scheme Based on DWT and DCT
IEEE Transactions on Signal Processing
Robust audio watermarking in the time domain
IEEE Transactions on Multimedia
Histogram-Based Audio Watermarking Against Time-Scale Modification and Cropping Attacks
IEEE Transactions on Multimedia
Attacks on digital watermarks: classification, estimation based attacks, and benchmarks
IEEE Communications Magazine
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
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An algorithm in which a multi-bit watermark is embedded into the important frequency peaks of an audio file is presented. In this algorithm, an advanced Wigner distribution method is used to estimate the most significant frequency band of the audio file. This method is based on the short-time Fourier transform (STFT) and the Wigner distribution methods, and has advantages over other methods. The important frequency peaks are selected from the most significant frequency band. Once broadcasted, an audio file is subject to many attacks such as compression and quantization. However, the main feature of the audio signal is its important frequency peaks, which are invariant. We exploit this invariance to embed the multi-bit watermark into the important frequency peaks. The simulation results show that the proposed algorithm is robust to the strong attacks such as noise addition, filtering, re-sampling and MP3 compression.