Robust Image Data Hiding Technique for Copyright Protection

2013 ◽  
Vol 7 (2) ◽  
pp. 44-56 ◽  
Author(s):  
Siddharth Singh ◽  
Tanveer J. Siddiqui
Keyword(s):  
Data Hiding ◽  
Copyright Protection ◽  
Spread Spectrum ◽  
Image Data ◽  
Singular Values ◽  
Histogram Equalization ◽  
Chaotic Sequence ◽  
Discrete Wavelet ◽  
Robust Image ◽  
Value Decomposition

A robust image data-hiding scheme for copyright protection is proposed and simulated. The scheme uses a combination of redundant discrete wavelet transform (RDWT), singular value decomposition (SVD) and spread spectrum technique. The embedding is done by spreading the copyright mark into the singular values of middle frequency sub-bands of RDWT coefficients of the cover image. Chaotic sequence is used for spreading. The use of chaotic sequence and RDWT increases security and robustness of the proposed scheme. Simulation results show that the proposed scheme achieves higher security and robustness against filtering, addition of noise, JPEG compression, sharpening, gamma correction, resizing, rotation, and histogram equalization than other existing techniques for copyright protection.

scholarly journals An Approach for Image Copyright Protection by using Walsh Hadamard Method

2017 ◽  
Vol 12 (1) ◽  
pp. 142-168
Author(s):  
Manish Kumar Gupta ◽  
Dibakar Raj Pant
Keyword(s):  
Copyright Protection ◽  
Wavelet Transformation ◽  
Signal To Noise Ratio ◽  
Image Data ◽  
Scaling Factor ◽  
Discrete Wavelet ◽  
Protection Method ◽  
Hadamard Transformation ◽  
Value Decomposition ◽  
Day By Day

Protecting copyrighted image from abuse, misuse and piracy is being critical day by day. Digital image Copyright Protection is considered as a solution to prevent the piracy of original image data. In this article, the authors propose copyright protection method using the well-known Walsh Hadamard transformation along with discrete wavelet transformation and singular value decomposition to achieve robust and imperceptible copyrighted image. The optimum scaling factor which decides the strength of signature image to be embedded is obtained at 0.3. The proposed article ensures imperceptibility of copyrighted image which is determined by Peak signal to noise ratio value greater than 35dB. Normalized Correlation value nearly equals to 0.9999 provides robustness against different attacks such as image cropping, rotations and noise on copyrighted image.  Journal of the Institute of Engineering, 2016, 12(1): 162-168

A Unified Approach towards Multimedia Watermarking

2013 ◽  
pp. 376-399
Author(s):  
Ali Al-Haj ◽  
Ahmad Mohammad ◽  
Samir Abou El-Seoud ◽  
Tuqa Manasrah ◽  
Lama Rajab ◽  
...  
Keyword(s):  
Digital Media ◽  
Digital Watermarking ◽  
Singular Values ◽  
Discrete Wavelet ◽  
Digital Multimedia ◽  
Copyright Violation ◽  
The Media ◽  
Value Decomposition ◽  
Multimedia Watermarking ◽  
Dual Transform

The tremendous advancement of digital technology has increased the ease with which digital multimedia signals (image, video, audio) are stored, transmitted, and reproduced. Consequently, the content providers and owners are faced with problems of protection against copyright violation and other forms of abuse to their digital property. Digital watermarking has been proposed in the last decade as a solution to prevent illegal and malicious copying and distribution of digital media by embedding an unnoticeable information into the media content. This chapter describes three imperceptible and robust watermarking algorithms for different types of multimedia objects (image, video, audio). The three algorithms are based on cascading two powerful mathematical transforms; the Discrete Wavelet Transform (DWT), and the Singular Value Decomposition (SVD). The two transforms are different, and thus provide complementary levels of robustness against the same attack. In the proposed dual-transform algorithms, the watermark bits are not embedded directly on the wavelet coefficients, but rather on the elements of singular values of the DWT sub-bands of the multimedia object. Effectiveness of the proposed algorithms is demonstrated through extensive experimentation.

scholarly journals Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding

2020 ◽  
Vol 10 (12) ◽  
pp. 4338
Author(s):  
Gelar Budiman ◽  
Andriyan Bayu Suksmono ◽  
Donny Danudirdjo
Keyword(s):  
Data Hiding ◽  
Compression Ratio ◽  
Spread Spectrum ◽  
Sampling Technique ◽  
Singular Values ◽  
Compressive Sampling ◽  
Biomedical Signal ◽  
Audio Quality ◽  
Memory Efficiency ◽  
Broadcast Monitoring

We propose a novel data hiding method in an audio host with a compressive sampling technique. An over-complete dictionary represents a group of watermarks. Each row of the dictionary is a Hadamard sequence representing multiple bits of the watermark. Then, the singular values of the segment-based host audio in a diagonal matrix are multiplied by the over-complete dictionary, producing a lower size matrix. At the same time, we embed the watermark into the compressed audio. In the detector, we detect the watermark and reconstruct the audio. This proposed method offers not only hiding the information, but also compressing the audio host. The application of the proposed method is broadcast monitoring and biomedical signal recording. We can mark and secure the signal content by hiding the watermark inside the signal while we compress the signal for memory efficiency. We evaluate the performance in terms of payload, compression ratio, audio quality, and watermark quality. The proposed method can hide the data imperceptibly, in the range of 729–5292 bps, with a compression ratio 1.47–4.84, and a perfectly detected watermark.

ROBUST REFERENCE-WATERMARKING SCHEME USING WAVELET PACKET TRANSFORM AND BIDIAGONAL-SINGULAR VALUE DECOMPOSITION

2009 ◽  
Vol 09 (03) ◽  
pp. 449-477 ◽  
Author(s):  
GAURAV BHATNAGAR ◽  
BALASUBRAMANIAN RAMAN
Keyword(s):  
Singular Value Decomposition ◽  
Gaussian Noise ◽  
Copyright Protection ◽  
Wavelet Packet ◽  
Singular Values ◽  
Wavelet Packet Transform ◽  
Singular Value ◽  
Noise Type ◽  
Value Decomposition ◽  
Watermarking Scheme

This paper presents a new robust reference watermarking scheme based on wavelet packet transform (WPT) and bidiagonal singular value decomposition (bSVD) for copyright protection and authenticity. A small gray scale logo is used as watermark instead of randomly generated Gaussian noise type watermark. A reference watermark is generated by original watermark and the process of embedding is done in wavelet packet domain by modifying the bidiagonal singular values. For the robustness and imperceptibly, watermark is embedded in the selected sub-bands, which are selected by taking into account the variance of the sub-bands, which serves as a measure of the watermark magnitude that could be imperceptibly embedded in each block. For this purpose, the variance is calculated in a small moving square window of size Sp× Sp(typically 3 × 3 or 5 × 5 window) centered at the pixel. A reliable watermark extraction is developed, in which the watermark bidiagonal singular values are extracted by considering the distortion caused by the attacks in neighboring bidiagonal singular values. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks and the superiority of the proposed method is carried out by the comparison which is made by us with the existing methods.

A New Robust Color Image Watermarking Based on DWT and DRT

2013 ◽  
Vol 278-280 ◽  
pp. 1366-1373 ◽  
Author(s):  
Zi Teng ◽  
Xiu Feng Qiu ◽  
Jian Wei Liu
Keyword(s):  
Digital Watermarking ◽  
Copyright Protection ◽  
Color Image ◽  
Image Watermarking ◽  
Discrete Wavelet ◽  
Color Image Watermarking ◽  
Ridgelet Transform ◽  
Color Image Watermark ◽  
Robust Image ◽  
Watermarking Scheme

The copyright protection of multimedia information is more and more important in the digital age, digital watermarking is a solution to address the topic. This paper proposes a new robust image watermarking scheme based on discrete ridgelet transform (DRT) and discrete wavelet transform (DWT). The scheme respectively embeds a copy of color image watermark into DWT domain and DRT domain, and uses a conception of semi-watermark. Experiment results demonstrate that the watermark can resist various attacks such as adding Gaussian or Union Distribution Noise, JPEG compression, brightness adjustment, contrast adjustment, altering color balance, lens blur, zooming in or out, cropping and some combined attacks etc.

Robust Image Data Hiding Using Geometric Mean Quantization

2009 ◽  
Author(s):  
Mohammad Ali Akhaee ◽  
Shahrokh Ghaemmaghami ◽  
Amir Nikooienejad ◽  
Farokh Marvasti
Keyword(s):  
Data Hiding ◽  
Geometric Mean ◽  
Image Data ◽  
Robust Image

scholarly journals A new DWT-SVD based robust watermarking scheme for real property rights

2014 ◽  
Vol 3 (2) ◽  
pp. 69-78
Author(s):  
Sedigeh Razavi babakalak ◽  
Mohammad Ali Balafar ◽  
Ali Farzan
Keyword(s):  
Property Rights ◽  
Image Watermarking ◽  
Singular Values ◽  
Discrete Wavelet ◽  
Digital Image Watermarking ◽  
Robust Watermarking ◽  
Real Property ◽  
Noise Type ◽  
Value Decomposition ◽  
Watermarking Scheme

In this paper, a new robust digital image watermarking algorithm which was based on singular value decomposition (SVD) and discrete wavelet transform (DWT) was proposed and simulated for protecting real property rights. A gray scale logo image, rather than a randomly generated Gaussian noise type watermark, was used as a watermark. Its embedding algorithm hid a watermark LL sub-band blocks in the low–low (LL) and high-high (HH) sub-bands of a target non-overlapping block of the host image by modifying singular values on SVD version of these blocks. A semi-blind watermark extraction was designed to estimate the original coefficients. Experimental results showed that the proposed scheme made significant improvements in terms of both transparency and robustness and was superior to the existing methods which were considered in this paper.

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