The Robust Digital Image Watermarking Scheme with Back Propagation Neural Network in DWT Domain

Ramamurthy, Nallagarla; Varadarajan, S.

doi:10.1016/j.proeng.2012.06.432

Cited by 19 publications

(14 citation statements)

References 8 publications

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“…In addition, a binary image with half the size of the video frames is considered as the watermark shown in Figure.4. The perceptual quality of watermarked frames is studied with PSNR, which is given by Eq.11 [24]. While the capability of tamper detection is investigated by CER, which is used as a general measure of the similarity between the original and extracted watermarks, and is defined by Eq.13 [25].…”

Section: Resultsmentioning

confidence: 99%

A Fragile Video Watermarking Algorithm for Content Authentication based on Block Mean and Modulation Factor

Gamal¹,

Mosa²,

Said³

2013

IJCA

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Most watermarking algorithms are either robust watermarking for copyright protection or fragile watermarking for tamper detection. This paper proposes a fragile video watermarking algorithm that has the ability to detect tamper in spatial domains. The original video frame is converted from RGB color space into YCbCr color space, then the chrominance component Cb is partitioned into non-overlapping blocks of pixels according to the number of bits of the original watermark. The watermark bits are embedded using a mathematical rule for each block separately. A detailed study for the applicability of this algorithm to content authentication is conducted. Experimental results reveal that the proposed algorithm achieves a low computation cost and high detection rate against a wide range of tampering attacks such as Filtering, Non-Geometric Transformation and Geometric Transformation.

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Section: Resultsmentioning

confidence: 99%

A Fragile Video Watermarking Algorithm for Content Authentication based on Block Mean and Modulation Factor

Gamal¹,

Mosa²,

Said³

2013

IJCA

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“…While frequency domain schemes transform the representation of spatial domain into the frequency domain and then modify its frequency coefficients to embed the watermark. There are many transform domain watermarking schemes such as discrete cosine transforms (DCT) [4,9,57,39,37,38,113], singular value decomposition (SVD) [8,14,22,27,28,34,48,52,63,74,77,84,85,90,91,113], discrete Fourier transforms (DFT) [18,64,67,70,94], and discrete wavelet transforms (DWT) [7,28,51,83,90,102,117]. These methods typically provide higher imperceptibility and are much more robust to distortion attacks, but the computational cost is higher than spatial-domain watermarking methods.…”

Section: Digital Watermarkingmentioning

confidence: 99%

“…It is expected that intelligent data hiding schemes have better results in terms of robustness, transparency or tradeoff between them. In the last two decades, artificial intelligence (AI) techniques such as evolutionary algorithms (EAs), support vector machine, fuzzy logic and neural networks have played an important role in data hiding [25,71,72,83,95,94,99,105,116,121] for improving the performance. Under the category of evolutionary algorithms, genetic algorithm (GA) [7,23,25,47,71,72,81], particle swarm optimization (PSO) [53,85,94,99,108], differential evolution (DE) [4,6,2,8,52], Firefly algorithm [76], and artificial bee colony (ABC) [5] have made numerous valuable contributions to the field of data hiding.…”

Section: Application Of Artificial Intelligence In Data Hidingmentioning

confidence: 99%

“…The neural networks have shown a good potency in dealing with the data hiding problems [44,83,119]. The neural structure of the human eye is considered in human visual system (HVS).…”

Section: Application Of Artificial Intelligence In Data Hidingmentioning

confidence: 99%

“…The blocks, which produce the least amount of perceivable changes are selected by this method. A blind robust digital image watermarking approach based on back propagation neural network in DWT domain is presented in [83]. The back propagation neural network is implemented during both the process; embedding and extraction.…”

Section: Application Of Artificial Intelligence In Data Hidingmentioning

confidence: 99%

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Data Hiding Schemes: A Survey

Ali¹,

Ahn²,

Pant³

2016

Gate to Computer Science and Research

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Data hiding is the process of hiding an amount of data, called secret message or watermark, into a cover media that may be audio, video, or image signal, in an imperceptible way for different purposes. Due to the advances in generation, storage, and communication technology of digital media, the necessity and importance of data hiding has drawn the attention of many researchers all over the world resulting in a lot of variants of data hiding scheme. This chapter provides a detailed review of the basic concepts of data hiding and a survey of its major variants developed so far. The chapter classifies the data hiding schemes based on several aspects of data hiding comprising artificial intelligence. Furthermore, the chapter also provides the recommendations to the interested users for further research. This review may be a useful insight and a good source for the users who are interested in the application of artificial intelligence in data hiding.

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Enhanced Image Security Through Hybrid Approach

Arora¹,

Kadian²

2022

Wireless Communication Security

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The Robust Digital Image Watermarking Scheme with Back Propagation Neural Network in DWT Domain

Cited by 19 publications

References 8 publications

A Fragile Video Watermarking Algorithm for Content Authentication based on Block Mean and Modulation Factor

A Fragile Video Watermarking Algorithm for Content Authentication based on Block Mean and Modulation Factor

Data Hiding Schemes: A Survey

Enhanced Image Security Through Hybrid Approach

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