A new adaptive digital audio watermarking based on support vector machine

Authors:
Xiang-Yang Wang;Pan-Pan Niu;Wei Qi
Affiliations:
School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China and State Key Laboratory of Information Security, Institute of Software of Chinese Academy of Scienc ...;School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China;School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China
Venue:
Journal of Network and Computer Applications
Year:
2008

Citing 5
Cited 4

The nature of statistical learning theory

The nature of statistical learning theory
An Audio Watermarking Technique That Is Robust Against Random Cropping

Computer Music Journal
Proceedings of the 4th international conference on Digital Watermarking

IWDW'05 Proceedings of the 4th international conference on Digital Watermarking
Spread-spectrum watermarking of audio signals

IEEE Transactions on Signal Processing
A Novel Synchronization Invariant Audio Watermarking Scheme Based on DWT and DCT

IEEE Transactions on Signal Processing

Using Support Vector Machines for feature-oriented profile-based recommendations

International Journal of Advanced Intelligence Paradigms
Copyright-proving scheme for audio with counter-propagation neural networks

Digital Signal Processing
A learning-based audio watermarking scheme using kernel Fisher discriminant analysis

Digital Signal Processing
Genetic swarm based robust image watermarking

Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is a challenging work to design a robust digital audio watermarking scheme against desynchronization attacks. On the basis of support vector machines (SVMs), a new robust digital audio watermarking algorithm against desynchronization attacks is proposed in this paper, and in this the audio statistics characteristics and synchronization code are utilized. Firstly, the optimal embedding positions are located adaptively by using the SVM theory. Secondly, the 16-bit Barker code is chosen as synchronization mark and embedded into the digital audio by modifying the statistics average value of several samples. Finally, the digital watermark are embedded into the statistics average value of low-frequency components in wavelet domain by making full use of auditory masking. Experimental results show that the proposed scheme is inaudible and robust against common signal processing such as MP3 compression, low-pass filtering, noise addition, equalization, etc., and is robust against desynchronization attacks such as random cropping, amplitude variation, pitch shifting, time-scale modification, jittering, etc.