Authors:
Charfeddine Maha
;
Elarbi Maher
;
Koubaa Mohamed
and
Ben Amar Chokri
Affiliation:
University of Sfax, National School of Engineers (ENIS), Tunisia
Keyword(s):
Data Security, Discrete Cosine Transforms, Neural Network, Hamming Codes.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Audio and Speech Processing
;
Digital Signal Processing
;
Multimedia
;
Multimedia and Communications
;
Multimedia Security and Cryptography
;
Multimedia Signal Processing
;
Multimodal Signal Processing
;
Pattern Recognition
;
Software Engineering
;
Telecommunications
Abstract:
During these recent years, different digital audio media are available due to internet and audio processing techniques. This is beneficial to our daily life but it brings the problem of ownership protection. As a solution, audio watermarking technique has been quickly developed. It consists of embedding information into digital audio data. This paper proposes an audio watermarking scheme operating in frequency domain using Discrete Cosine transforms (DCT). We take the advantage of hiding the mark in the frequency domain to guarantee robustness. To increase robustness of our schemes, the watermark is refined by the Hamming error correcting code. We study the band used to hide the watermark bits according essentially to the effects of the MP3 compression on the watermarked audio signal. To assure watermark embedding and extraction, we use neural network architecture. Experimental results show that the watermark is imperceptible and the algorithm is robust to many attacks like MP3 compr
ession with several compression rates and various Stirmark attacks. Furthermore, the watermark can be blind extracted without needing the original audio.
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