Adaptive watermark scheme with RBF neural networks

Zhang, Zhiming; Li, Rongyan; Wang, Lei

doi:10.1109/icnnsp.2003.1281164

Cited by 33 publications

(16 citation statements)

References 4 publications

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“…There are many numbers of techniques that are develop in both frequency and spatial domain such as hiding watermark in the least significant bit (LSB) [4], or using the coefficients of discreet cosine transform (DCT) blocks to embedded watermark [5], increasing the strength for watermarking by utilize discrete wavelet transform (DWT) mechanism [6], utilize (radial basis function RBF) neural network to produce watermark with high strength [7], and embedding watermark in the discrete components (DC) of transformed blocks [8].…”

Section: Related Workmentioning

confidence: 99%

Generating Pattern from Image using Genetic Algorithm as Invisible Watermark

Abdul-Jabbar¹,

AbdulGhafor²

2017

djps

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Section: Related Workmentioning

confidence: 99%

Generating Pattern from Image using Genetic Algorithm as Invisible Watermark

Abdul-Jabbar¹,

AbdulGhafor²

2017

djps

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“…It showed good performance, but instead of embedding the watermark in the cover image, it was embedded in the FCNN synapses. Zhi-Ming et.al and Quan et.al [34,52] proposed a Radial Basis Function (RBF) based watermarking scheme to determine the watermarking strength.…”

Section: Related Workmentioning

confidence: 99%

A bi-directional associative memory based multiple image watermarking on cover video

Agilandeeswari

Ganesan

2015

Multimed Tools Appl

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Telemedicine is a rapidly developing application of clinical medicine where medical information is transferred through the internet and other networks for the purpose of consulting, and remote medical procedures or examinations. This paper presents a novel neural network inspired watermarking technique, to enhance the authentication of the transmitted sensitive medical images over telemedicine network. In order to examine the medical images, the multiple scan images of same type or different types can be considered as watermarks and the same are trained using Bidirectional Associative Memory (BAM) neural network. The resultant weight matrix is embedded in the less correlated Principal Component Analysis (PCA) components of the wavelet coefficients of the cover video frames using additive embedding type of watermark. At the receiver end, the same BAM neural network is used with the randomly generated target matrix and the extracted weight matrix as input. As a result of this, the input matrix will be obtained. From the input matrix, the physician can extract their own information or scan images using their private or secret key. The proposed watermarking technique is validated with the existing systems in terms of imperceptibility, robustness and watermark capacity using the metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Normalized Cross Correlation (NCC), Bit Correction Rate (BCR), Detection rate, Receiver Operating Characteristics (ROC) and payload. The performance of the proposed system is evaluated by introducing various notable image processing attacks, geometrical attacks and video processing attacks on watermarked video. The experimental results demonstrate that the proposed technique has good perceptual quality of 50.6292 dB in terms of PSNR value, robustness of about nearly 1.0000 in terms of NCC value and payload of 1000 watermarks.

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“…A large number of techniques have been developed in spatial domain and frequency domain like manipulating the bit plane of Least Significant Bit (LSB) [1], linear addition of watermark to cover image, using mid band coefficients of Discrete Cosine Transform (DCT) transformed blocks to hide watermark [2], maximizing strength of watermark using Discrete Wavelet Transform(DWT) techniques [3], Using radial basis function(RBF)neural network to achieve maximum strength watermark [4]. Deng and wang [5] propose a novel algorithm to Embed a watermark into a still host image in DCT domain.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Fidelity with Adaptive Genetic Watermarking Algorithm Using Roulette-Wheel

Goyal

Gupta

2010

2010 International Conference on Computational Intelligence and Communication Networks

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In Digital Watermarking a low energy signal is imperceptibly embedded in another signal. The low energy signal is called watermark. Earlier techniques based on spatial and frequency domain, had the problems of a poor fidelity especially with higher payloads of watermark image. Unsatisfactory value of Peak Signal to Noise Ratio (PSNR) of watermarked image resulting in image quality degradation was seen in varying degree, in various research works. This paper is an attempt to employ genetic algorithms to find suitable locations for watermark insertion within a cover image, to focus on the issue of optimizing fidelity. The paper uses a roulette-wheel selection strategy in genetic algorithm and investigates the variation of maximum fitness which reflects the higher PSNR of the watermarked image with respect to embedding strength, number of genes, and incremental payloads of watermark consisting of binary matrix. With the proper understanding and analysis of the results of this paper, a successful watermarking scheme can be obtained using Genetic algorithms, which may be useful when optimizing the fidelity aspect of digital watermarking..

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Adaptive watermark scheme with RBF neural networks

Cited by 33 publications

References 4 publications

Generating Pattern from Image using Genetic Algorithm as Invisible Watermark

Generating Pattern from Image using Genetic Algorithm as Invisible Watermark

A bi-directional associative memory based multiple image watermarking on cover video

Optimization of Fidelity with Adaptive Genetic Watermarking Algorithm Using Roulette-Wheel

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