Speech, hearing and neural network models
Speech, hearing and neural network models
Robust audio watermarking using perceptual masking
Signal Processing
Handbook of Applied Cryptography
Handbook of Applied Cryptography
Proceedings of the First International Workshop on Information Hiding
Robust audio watermarking in the time domain
IEEE Transactions on Multimedia
Wideband speech and audio coding
IEEE Communications Magazine
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Digital Signal Processing
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A robust multi bit and high quality audio watermarking technique in time domain is proposed in this paper. Watermarking is a technique used to label digital media by hiding copyright or other information into the underlying data. The watermark must be imperceptible and undetectable by the user and should be robust to various types of distortion. To enhance the robustness and taper-resistance of the embedded watermark, in this paper a multi bit technique is employed. Instead of embedding one bit into an audio frame, multiple bits can be embedded into each audio sub-frame. For attackers, since they do not know the parameters, this significantly reduces the possibility of unauthorized bit detection and removal of watermark. In real-time watermarking applications, robustness is not the only factor that plays an important role. The other factor that plays a very an important role is computational complexity. In general, audio file is transmitted in compressed form. Real-time watermark embedding must take into account this compressed form, because first decompressing the data, adding a watermark and then recompressing the data is computationally too demanding. In this paper, we propose robust and low complexity audio watermarking algorithm. To evaluate the performance of the proposed audio watermarking algorithm, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) were conducted. Compared to traditional one bit embedding algorithm, the proposed algorithm gives highly recovery rate after attack by commonly used audio data manipulations, such as low pass filtering, requantization, resampling, and MP3 compression.