scholarly journals Robust and Blind Audio Watermarking Algorithm in Dual Domain for Overcoming Synchronization Attacks

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qiuling Wu ◽  
Aiyan Qu ◽  
Dandan Huang
Keyword(s):  
Time Domain ◽  
Audio Watermarking ◽  
Transform Domain ◽  
Quantization Step ◽  
Blind Audio Watermarking ◽  
Synchronization Mechanism ◽  
The Time Domain ◽  
Value Decomposition ◽  
Dual Domain ◽  
Conventional Signal

How to effectively resist synchronization attacks is the most challenging topic in the research of robust watermarking algorithms. A robust and blind audio watermarking algorithm for overcoming synchronization attacks is proposed in dual domain by considering time domain and transform domain. Based on analysing the characteristics of synchronization attacks, an implicit synchronization mechanism (ISM) is developed in the time domain, which can effectively track the appropriate region for embedding and extracting watermarks. The data in this region will be subjected to discrete cosine transform (DCT) and singular value decomposition (SVD) in turn to obtain the eigenvalue that can be utilized to carry watermarks. In order to extract the watermark blindly, the eigenvalue will be quantized. Genetic algorithm (GA) is utilized to optimize the quantization step to balance both transparency and robustness. The experimental results confirm that the proposed algorithm not only withstands various conventional signal processing operations but also resists malicious synchronization attacks, such as time scale modification (TSM), pitch-shifting modification (PSM), jittering, and random cropping. Especially, it can overcome TSM with strength from −30% to +30%, which is much higher than the standard of the International Federation of the Phonographic Industry (IFPI) and far superior to the other algorithms in related papers.

Audio Watermarking Based on Hybrid Low and High Wavelet Frequencies

2016 ◽  
Vol 5 (1) ◽  
pp. 28
Author(s):  
Aree Ali Mohammed
Keyword(s):  
Time Domain ◽  
Wavelet Transformation ◽  
Signal To Noise Ratio ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Digital Audio ◽  
Test Results ◽  
Digital Audio Watermarking ◽  
Over Time

Transform-domain digital audio watermarking has a performance advantage over time-domain watermarking by virtue of the fact that frequency  transforms offer better exploitation of the human auditory system (HAS). In this research paper an adaptive audio watermarking is proposed based on the low and high wavelet frequencies band (LF, HF). The embedded watermark can be of any types of signal (text, audio and image). The insertion of the watermark data is performing in a frequency domain after applying discrete wavelet transformation on the cover audio segments. The normalize correlation and the signal to noise ratio metrics are used to test the performance of the proposed method in terms of the robustness and imperceptibility. Test results show that an improvement of the robustness against some type of attacks when the watermark is adaptively embedded in a different wavelet bands.

Identification of the Dynamic Characteristics of Long Annular Seals Using a Time Domain Technique

1998 ◽  
Vol 120 (3) ◽  
pp. 705-712 ◽  
Author(s):  
M. Ismail ◽  
R. D. Brown
Keyword(s):  
Dynamic Characteristics ◽  
Time Domain ◽  
Theoretical Models ◽  
Rotational Frequency ◽  
Singular Value Decomposition Method ◽  
Damping Coefficients ◽  
Theoretical Predictions ◽  
The Time Domain ◽  
Value Decomposition ◽  
Annular Seals

This paper describes experimental results from a research program aimed at a study of the static and dynamic characteristics of liquid long annular seals. A seal test rig permits the identification in the time domain of mass, stiffness, and damping coefficients using a least-squares technique based on the singular value decomposition method. The experimental method relies on the forced excitation of a flexibly supported stator by two hydraulic shakers. The forcing signal is composed from a small number of frequencies which are not related to the rotational frequency of the rigid shaft rotating inside the stator. The test data consisting of two inertia, four stiffness, and four damping coefficients is compared with theoretical predictions based on two theoretical models: (i) the model of Black et al. (1971 and 1981) and (ii) the model of Childs and Kim (1985).

A high-capacity audio watermarking scheme in the time domain based on multiple embedding

2013 ◽  
Vol 30 (4) ◽  
pp. 286 ◽  
Author(s):  
Md.Rifat Shahriar ◽  
Sangbock Cho ◽  
Uipil Chong ◽  
Sangjin Cho
Keyword(s):  
Time Domain ◽  
High Capacity ◽  
Audio Watermarking ◽  
The Time Domain ◽  
Watermarking Scheme

Single-Rate Discrete-Time Signals and Systems

2009 ◽  
pp. 1-22
Author(s):  
Ljiljana Milic
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Discrete Time ◽  
Time Domain ◽  
Transform Domain ◽  
Concise Review ◽  
Discrete Signals ◽  
Time Signals ◽  
The Time Domain

This chapter is a concise review of time-domain and transform-domain representations of single-rate discrete-time signals and systems. We consider first the time-domain representation of discrete-time signals and systems. The representation in transform domain comprises the discrete-time Fourier transform (DTFT), the discrete Fourier transform (DFT), and the z-transform. The basic realization structures for FIR and IIR systems are briefly described. Finally, the relations between continuous and discrete signals are given.

scholarly journals Robust audio watermarking in the time domain

2001 ◽  
Vol 3 (2) ◽  
pp. 232-241 ◽  
Author(s):  
P. Bassia ◽  
I. Pitas ◽  
N. Nikolaidis
Keyword(s):  
Time Domain ◽  
Audio Watermarking ◽  
The Time Domain

scholarly journals Frame-synchronous Blind Audio Watermarking for Tamper Proofing and Self-Recovery

2020 ◽  
Vol 5 (1) ◽  
pp. 18-32
Author(s):  
Hwai-Tsu Hu ◽  
Ying-Hsiang Lu
Keyword(s):  
Audio Signal ◽  
Audio Watermarking ◽  
Frame Synchronization ◽  
Content Authentication ◽  
Blind Audio Watermarking ◽  
Synchronization Mechanism ◽  
Related Data ◽  
Perceptual Evaluation ◽  
Reed Solomon Code ◽  
Watermarking Scheme

This paper presents a lifting wavelet transform (LWT)-based blind audio watermarking scheme designed for tampering detection and self-recovery. Following 3-level LWT decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. To suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2nd and 3rd -detail subbands using 2N-ary adaptive quantization index modulation. The frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. To endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a Reed–Solomon code to correct symbol errors. The experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. The incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. Furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. With all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication.

Parametric Studies on Moving Axle Load Identification

2001 ◽  
Author(s):  
Ling Yu ◽  
Tommy H. T. Chan
Keyword(s):  
Time Domain ◽  
Time Domain Method ◽  
Identification Accuracy ◽  
Load Identification ◽  
System Parameters ◽  
Domain Method ◽  
Parametric Studies ◽  
The Time Domain ◽  
Value Decomposition ◽  
Pseudo Inverse

Abstract This study addresses the effects of various parameters on moving axle load identification when vehicles move across a bridge. Main emphases are placed on evaluation of two solutions, pseudo-inverse (PI) and Singular value decomposition (SVD) solutions, to an over-determined set of equations established under the time domain method (TDM) and frequency-time domain method (FTDM). The effects of vehicle-bridge system parameters and of measurement system parameters on the TDM and FTDM are also investigated. Assessment results based on experiments in laboratory show that the TDM is a better and non-sensitive method. The SVD technique can effectively improve identification accuracy when using TDM and FTDM particularly in the case of the FTDM.

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