Text-image watermarking based on integer wavelet transform (IWT) and discrete cosine transform (DCT)

Alotaibi, Reem Ahmed; Elrefaei, Lamiaa A.

doi:10.1016/j.aci.2018.06.003

Cited by 38 publications

(23 citation statements)

References 18 publications

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“…The stego file is directly built. For example, authors of LSB methods [3,8,9] extract the quantized samples in binary and replace the least significant bits of each sample by a secret bit. These works, including our previous papers [2,7], are well-known in terms of the simplicity of extracting the secret message.…”

Section: Audio Data Hiding Based On Time Domainmentioning

confidence: 99%

“…The audio file is transformed into the frequency domain. This transformation happens by applying one of the most commonly used transformation algorithms such as Fast Fourier Transforms (FFT), Discrete Wavelet Transform (DWT), DCT [9,10]. For instance, the authors in [1] proposed a method that uses Singular Value Decomposition (SVD) and DCT.…”

Section: Audio Steganography Based On Frequency Domainmentioning

confidence: 99%

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Reversible Data Hiding in Audio Based on Discrete Cosine Transform and Location Maps

Al-Hooti¹,

Ahmad²

2019

IJIES

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Transmitting information via public networks is prone to illegal attacks. Thus, data hiding is a suitable aspect that is useful to assure information security. Nowadays, multimedia tempering becomes the most variety problem that occurs on public networks. Audio steganography methods aim to hide secret data in an audio file called cover. Many methods in the time domain can hide large data (payload) with relatively low robustness. On the other hand, transformed based frequency algorithms can be more robust but the recovery of the cover audio is not guaranteed. In this paper, we investigate the time and frequency domains and tend to bridge gaps in the area of data hiding with the frequency transformation methods. In addition, we propose a new reversible audio data hiding based on Discrete Cosine Transform (DCT) and location maps. This kind of map helps to fully recover both the secret message and the cover file from the stego where the frequency sample values are increased or decreased by 10 in correspondence with the intended bit to be embedded. The experimental results prove that this method is able to hide high payload, and it is also robust since it guarantees 100% the reversibility of both the secret message and the cover audio file. The quality measured by Signal-to-noise ratio (SNR) is approximately 75 dB, Normalized Correlation (NC) value is 1.000, and Bit Error Rate (BER) is around 0.006. Additionally, this method is able to maintain the quality and invisibility, which may not be achieved by some previous research.

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Section: Audio Data Hiding Based On Time Domainmentioning

confidence: 99%

Section: Audio Steganography Based On Frequency Domainmentioning

confidence: 99%

Reversible Data Hiding in Audio Based on Discrete Cosine Transform and Location Maps

Al-Hooti¹,

Ahmad²

2019

IJIES

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“…Another robust algorithm to protect gray scale images of Arabic text is employed by Alotaibi et al [11]. This one combines both IWT and DCT to hide the gray scale watermark.…”

Section: Literature Reviewmentioning

confidence: 99%

A Dwt and Scrambling Based Blind Watermarking Algorithm for Digital Images Authentication

Eid,

Emran,

Morsy

2019

IJEAT

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Like the other multimedia that is spread on the Internet, images are also vulnerable to theft and attacks. Protecting the image is therefore an urgent necessity because it represents a large proportion of the digital content. Authentication and ownership protection are the basic demands of image security and these are achieved by applying watermarking techniques. For the Muslim world, the Holy Quran has its sanctity, which does not accept any controversy or doubt. As part of keeping pace with modern technology, digital copies of the Holy Qur’an are available, which are widely distributed all over the world. Therefore, it is necessary to ensure that these copies maintain their integrity and ensure that there are no malicious manipulations. In this paper, we propose an image watermarking scheme to authenticate the images of digital version of Holy Quran using discrete wavelet transform DWT. Here a fragile watermark is used to clarify whether there is any modification occurred to the intended images. Initially the cover image is decomposed by DWT where 2nd and 4th level coefficients are exploited for watermark embedding. The intended watermark is obtained by scrambling the original cover image. Then the scrambled image is inserted into the DWT coefficients by several trials using different embedding gains. To evaluate our system and see how effective it is to detect any error or manipulation, PSNR, SSIM and MSE are employed beside that they are acting as an imperceptibility measure. Results proved that our method has achieved a good level of imperceptibility and can detect any slight tamper. It is necessary to bear in mind that this method is valid for application to normal color images as well and gives an excellent level of efficiency

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“…The most commonly used frequency domain in image watermarking research is DCT and DWT [11][12][13][14]. In the image watermarking method, the combination of DCT and DWT have proved that the method can generate better results than the use of one transformation only [15][16][17][18]. This is caused by each transformation has its own advantages.…”

Section: Introductionmentioning

confidence: 99%

Image watermarking using discrete wavelet-tchebichef transform

Setyono

Setiadi

2019

IJEECS

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<span>Image watermarking is one of the most popular techniques for authenticating copyright on the digital image. Many research on image watermarking has proved that the joint of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) combinations can improve both imperceptibility and robustness when compared to DCT or DWT only. Discrete Tchebichef Transform (DTT) denotes an alternative transformation that has a similarity property with DCT. DTT has an advantage in reducing memory requirements during computing, so the calculation speed is much faster than DCT. This study tested the performance of DTT and DCT on non-blind image watermarking method, where DTT and DCT are performed after DWT. Based on the experimental results, this research proved that the DTT was combined successfully with DWT and very potential for further investigation because it has a computing performance much better than DCT. While the image watermarking quality, both the imperceptibility and robustness aspects were completely identical with the combination of DCT and DWT transformation.</span>

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Text-image watermarking based on integer wavelet transform (IWT) and discrete cosine transform (DCT)

Cited by 38 publications

References 18 publications

Reversible Data Hiding in Audio Based on Discrete Cosine Transform and Location Maps

Reversible Data Hiding in Audio Based on Discrete Cosine Transform and Location Maps

A Dwt and Scrambling Based Blind Watermarking Algorithm for Digital Images Authentication

Image watermarking using discrete wavelet-tchebichef transform

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