New secure and robust audio watermarking algorithm based on QR factorization in wavelet domain

2015 ◽  
Vol 13 (03) ◽  
pp. 1550020 ◽  
Author(s):  
Mustapha Hemis ◽  
Bachir Boudraa ◽  
Thouraya Merazi-Meksen
Keyword(s):  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Audio Signal ◽  
Extraction Process ◽  
Audio Watermarking ◽  
Qr Factorization ◽  
Wavelet Domain ◽  
Content Authentication ◽  
Opinion Score ◽  
Common Signal

Digital watermarking consists in embedding imperceptible information into a host signal. It has been proposed to solve problems as varied as the protection of the copyright, content authentication, fingerprinting and broadcast monitoring. This paper presents a new approach for audio watermarking using the QR factorization in wavelet domain. This approach is based on embedding a watermark binary image in the R matrices of low frequency blocks DWT coefficients of audio signal. In this algorithm, the watermark is embedded by applying a Quantization Index Modulation (QIM) process on the determined optimal sample for each matrix R. The watermark can be blindly extracted without the knowledge of the original audio signal. Experimental results show that the proposed audio watermarking scheme maintains high quality of the audio signal. Signal to Noise Ratio (SNR), Log Spectral Distortion (LSD) and Mean Opinion Score (MOS) are about 40 dB, 0.37 dB and 4.84, respectively. Moreover, the scheme is quite robust against common signal processing attacks such as noise addition, filtering and MP3 compression. In addition, this method ensures a secure extraction process by using a private key, making it suitable for secure applications such as copyright protection.

Digital Audio Watermarking Scheme Based on Independent Component Analysis in DWT Domain

2011 ◽  
Vol 219-220 ◽  
pp. 1121-1125 ◽  
Author(s):  
Rui Chen ◽  
Yu Lin Lan ◽  
Reza Asharif Mohammad
Keyword(s):  
Independent Component Analysis ◽  
Low Frequency ◽  
Component Analysis ◽  
Extraction Process ◽  
Independent Component ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Digital Audio ◽  
Digital Audio Watermarking ◽  
Watermarking Scheme

This paper proposed a digital audio watermarking scheme based on independent component analysis (ICA) in DWT domain. The embedding process make full use of the multi-resolution characteristic of discrete wavelet transform (DWT), performing 3-level DWT. Selecting the low frequency coefficient appropriately as the embed location to make sure of the balance between the transparency and robustness. Then constructing the ICA model to embed the watermarking. The extraction process is similar with ICA’s goal, it’s used in extraction makes the scheme simple for implementation. The experiment results show that the proposed scheme has good robustness against common attacks, as well as transparency.

Wavelet‐domain audio watermarking using optimal modification on low‐frequency amplitude

2015 ◽  
Vol 9 (2) ◽  
pp. 166-176 ◽  
Author(s):  
Shuo‐Tsung Chen ◽  
Chih‐Yu Hsu ◽  
Hunag‐Nan Huang
Keyword(s):  
Low Frequency ◽  
Audio Watermarking ◽  
Wavelet Domain

Digital Audio Watermarking Scheme Based on Independent Component Analysis in Stereo Sound

2012 ◽  
Vol 459 ◽  
pp. 469-473
Author(s):  
Rui Chen ◽  
Yu Lin Lan ◽  
Mohammad Reza Asharif
Keyword(s):  
Independent Component Analysis ◽  
Low Frequency ◽  
Component Analysis ◽  
Extraction Process ◽  
Independent Component ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Digital Audio ◽  
Digital Audio Watermarking ◽  
Watermarking Scheme

This paper proposed a digital audio watermarking scheme based on independent component analysis (ICA) in stereo sound. In order to make full use of the multi-channel characteristic of stereo sound, The watermarking embedded into the two channel, half respectively. Also using the multi-resolution characteristic of discrete wavelet transform, performing 3-level DWT in each channel. Selecting the low frequency coefficient appropriately as the embed location to make sure of the balance between the transparency and robustness. The extraction process is similar with ICA’ s goal, it’s used in extraction makes the scheme simple for implementation. The experiment results show that the proposed scheme has good robustness against common attacks, as well as transparency

Audio Watermarking Based on Wavelet Transform

2012 ◽  
Vol 229-231 ◽  
pp. 2784-2788 ◽  
Author(s):  
Mahmoud A. Osman ◽  
Nasser H. Ali
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Audio Signal ◽  
Frequency Component ◽  
Binary Image ◽  
Audio Watermarking ◽  
High Frequency Component ◽  
Discrete Wavelet ◽  
Copyright Information

The process of hiding the information like text, binary image, audio etc. into another signal source like image, audio etc. is called watermarking. The approach involved in watermarking the binary image signal in the wavelet domain of the audio signal was implemented using MATLAB. In this paper, we propose a Discrete Wavelet Transform low frequency to high frequency. Besides, the high frequency spectrum is less sensitive to human ear. That is the reason why the high frequency component is usually discarded in the compression process. Therefore, information to be hidden can be embedded into the low frequency component to against the compression attack. The characteristic of this scheme is that the user can not only use the DAW to embed the text file in to the audio but also binary image. In this paper we embeds copyright information into audio files as a proof of their ownership, we propose an effective, robust, and an inaudible audio watermarking algorithm. The effectiveness of the algorithm has been brought by virtue of applying the discrete wavelets transform (DWT) . Experimental results will be presented in this paper to demonstrate the effectiveness of the proposed algorithm.

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.

scholarly journals QIM - Based Audio Watermarking with Combination Technique of DCT-QR-CPT

2019 ◽  
Vol 7 (1) ◽  
pp. 112 ◽  
Author(s):  
RENDY DWI RENDRAGRAHA ◽  
GELAR BUDIMAN ◽  
IRMA SAFITRI
Keyword(s):  
Signal To Noise Ratio ◽  
Audio Watermarking ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Opinion Score ◽  
Low Pass ◽  
Band Pass ◽  
Speed Change ◽  
Index Modulation

ABSTRAKAudio watermarking adalah teknik memasukkan informasi ke dalam file audio dan untuk melindungi hak cipta data digital dari distribusi ilegal. Makalah ini memperkenalkan audio stereo watermarking berdasarkan Quantization Index Modulation (QIM) dengan teknik gabungan Discrete Cosine Transform (DCT) - QRCartesian Polar Transform (CPT). Host audio dibagi menjadi beberapa frame, selanjutnya setiap frame ditransformasi oleh DCT, kemudian output DCT diuraikan menjadi matriks orthogonal dan matriks segitiga menggunakan metode QR. Selanjutnya, CPT mengubah dua koefisien kartesian dari matriks segitiga (R) pada posisi (1,1) dan (2,2) menjadi koefisien polar. Setelah itu, penyisipan dilakukan pada koefisien polar oleh QIM. Hasil simulasi menunjukkan bahwa imperseptibilitas audio terwatermark berkualitas baik dengan Signal to Noise Ratio (SNR)> 20, Mean Opinion Score (MOS)> 4 dan tahan terhadap serangan seperti Low Pass Filter (LPF) dan Band Pass Filter (BPF) dengan cut off 25-6k, resampling, Linear Speed Change (LSC) dan MP3 Compression dengan rate diatas 64 kbps.Kata kunci: Audio Watermarking, CPT, DCT, QIM, QR ABSTRACTAudio watermarking is a technique for inserting information into an audio file and to protect the copyright of digital data from illegal distribution. This paper introduces a stereo audio watermarking based on Quantization Index Modulation (QIM) with combined technique Discrete Cosine Transform (DCT) – QR – Cartesian Polar Transform (CPT). Each frame of a host audio is transformed by DCT, then DCT output is decomposed using QR method. Next, CPT transform two cartesian coefficients from triangular matrix (R) in position (1,1) and (2,2) to polar coefficients. After that, embedding is executed on polar coefficients by QIM. The simulation result shows that the imperceptibility is good with Signal to Noise Ratio (SNR)>20, Mean Opinion Score (MOS)>4 and it is robust against attacks such as Low Pass Filter (LPF) and Band Pass Filter (BPF) with cut off 25-6k, Resampling, Linear Speed Change and MP3 Compression with rate 64 kbps and above. Keywords: Audio Watermarking, CPT, DCT, QIM, QR

scholarly journals A New Method of Denoising Crop Image Based on Improved SVD in Wavelet Domain

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Rui Wang ◽  
Wanxiong Cai ◽  
Zaitang Wang
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Signal To Noise Ratio ◽  
Wavelet Coefficient ◽  
Real Life ◽  
Low Frequency ◽  
New Method ◽  
Wavelet Domain ◽  
Noise Image ◽  
Noise Ratio

In real life, images are inevitably interfered by various noises during acquisition and transmission, resulting in a significant reduction in image quality. The process of solving this kind of problem is called image denoising. Image denoising is a basic problem in the field of computer vision and image processing, which is essential for subsequent image processing and applications. It can ensure that people can obtain more effective information of images more accurately. This paper mainly studies a new method of crop image denoising with improved SVD in wavelet domain. The algorithm used in this study firstly carried out a 3-layer wavelet transform on the crop noise image, leaving the low-frequency subimage unchanged; then, for the high-frequency subimages distributed in the horizontal, vertical, and diagonal directions, the improved adaptive SVD algorithm was used to filter the noise; finally perform wavelet coefficient reconstruction. To effectively test the performance of the algorithm, field crop images were taken as test images, and the denoising performance of the algorithm, SVD algorithm, and the improved SVD algorithm used in this study were compared, and the peak signal-to--to-noise ratio (PSNR) was introduced. Quantitative evaluation of the denoising results of several types of algorithms. The experimental data in this paper show that when the noise standard deviation is greater than 20, the enhanced experimental results clearly achieve higher PSNR and SSIM values than WNNM. The average peak signal-to-noise ratio (PSNR) is about 0.1 dB higher, and the average SSIM is larger about 0.01. The results show that the algorithm used in this study is superior to the other two algorithms, which provides a more effective method for crop noise image processing.

scholarly journals A NOVEL APPROACH IN IMAGE WATERMARKING WITH DISCRETE WAVELET TRANSFORM

2013 ◽  
pp. 271-274
Author(s):  
G. KOTESWARA RAO ◽  
V. ANURAGH ◽  
T.P. SRINIVASKAUSALYANANDAN ◽  
R.L. PRASHANTH
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Image Data ◽  
Extraction Process ◽  
Discrete Wavelet ◽  
Wavelet Domain ◽  
Still Image ◽  
Image Pyramids ◽  
Novel Approach ◽  
Frequency Domain Methods

In this paper we present a new watermarking scheme for still image data. Most of the recent work in watermarking can be grouped into two categories: spatial domain methods and frequency domain methods. We introduce a novel approach of watermarking which involves embedding the watermark in the discrete wavelet domain. We make use of a multi resolution data fusion approach in which the image and watermark are both transformed into the discrete wavelet domain. The resulting image pyramids are then fused according to a series of combination. After watermark insertion, inverse DWT is applied to the sub-bands with modified coefficients to obtain the watermarked image. For watermark extraction, a threshold-based decoder is designed. Embedding and extraction process are characterized with parameters and genetic algorithm is used for parameter optimization. Optimization is to maximize the values of peak signal-to-noise ratio of the watermarked image and normalized cross correlation of the extracted watermark. The performance of the proposed scheme is compared with the existing schemes and significant improvement is observed.

scholarly journals High-capacity, transparent and robust blind audio watermarking scheme based DWT and TLBO algorithm

2020 ◽  
Author(s):  
Ali Joudaki ◽  
Marjan Abdeyazdan ◽  
Mohammad Mosleh
Keyword(s):  
Digital Media ◽  
High Capacity ◽  
Audio Signal ◽  
Extraction Process ◽  
Audio Watermarking ◽  
Blind Audio Watermarking ◽  
Tlbo Algorithm ◽  
Payload Capacity ◽  
Low Pass ◽  
Specific Frequency

Abstract Digital watermarking is one of the best solutions again the copyright infringement, duplicates, verifies data and illegal distribution of digital media. Recently, the protection of digital audio signals is one of the attracting and interesting topics for scientific and researchers. In this paper we propose a blind audio watermarking mechanism in which it has high capacity, transparency and resistance simultaneously based on digital wavelet transform (DWT) algorithm. The key principle of this work is that in the DWT procedure, using two filters; break down the original audio signal into several sub-bands and transform them on a specific frequency range. It should be noted that the 8 bits of watermarked signal is selected and transform to the original signal. In order to increase the watermarking resistance, framing the high frequency coefficients of the third level of the wavelet and calculate the frames average and place them in the frame memory prime. Moreover, TLBO algorithm used to determination of embedding and extraction coefficients in order to increase the SNR ratio in the embedding process and decrease the bit error rate (BER) in the extraction process. This method increases the embedding payload capacity while the audio SNR and extracted image BER have good qualify. Moreover, experimental results shown that this method has 13kbs hiding rate,ascendency imperceptibility, good payload capacity and intense robustness when resisting against various attacks such as MP3 compression, re-quantization, low-pass filtering, amplitude scaling, re-sampling, echo addition and noise corruption.

Optimally Sensitive and Efficient Compact Loudspeakers for Low Audio Frequencies

2007 ◽  
Vol 38 (7) ◽  
pp. 11-17
Author(s):  
Ronald M. Aarts
Keyword(s):  
Optimality Criterion ◽  
Low Frequency ◽  
Audio Signal ◽  
Design Procedure ◽  
Frequency Range ◽  
Force Factor ◽  
Low Frequencies ◽  
Limited Frequency ◽  
The Cost ◽  
Higher Sensitivity

Conventionally, the ultimate goal in loudspeaker design has been to obtain a flat frequency response over a specified frequency range. This can be achieved by carefully selecting the main loudspeaker parameters such as the enclosure volume, the cone diameter, the moving mass and the very crucial “force factor”. For loudspeakers in small cabinets the results of this design procedure appear to be quite inefficient, especially at low frequencies. This paper describes a new solution to this problem. It consists of the combination of a highly non-linear preprocessing of the audio signal and the use of a so called low-force-factor loudspeaker. This combination yields a strongly increased efficiency, at least over a limited frequency range, at the cost of a somewhat altered sound quality. An analytically tractable optimality criterion has been defined and has been verified by the design of an experimental loudspeaker. This has a much higher efficiency and a higher sensitivity than current low-frequency loudspeakers, while its cabinet can be much smaller.

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