In this work, a novel and adaptive visible/invisible watermarking scheme for embedding and extracting a digital watermark into/from an image is proposed. The proposed method uses an adaptive procedure for calculating scaling factor or scaling strength using sigmoid function in Hadamard transform domain. The value of scaling factor is governed by a control parameter. The control parameter can be adjusted to make the watermarking scheme as either visible or invisible. The proposed methodology facilitates in preserving ownership rights and prevents the piracy of digital data which are considered to be the basic needs of digital watermarking. As proposed watermarking process is carried out in Hadamard transform domain, it is more robust to image/signal processing attacks. The experimental results and performance analysis confirm the efficiency of the proposed scheme. © 2013 Elsevier Ltd. All rights reserved.

Santhi V

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

Arulmozhivarman P

Department of Instrumentation

School of Electrical Engineering

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Journal of Information Security and Applications

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. © 2015, Springer Science+Business Media New York.

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Journal	Data powered by TypesetJournal of Information Security and Applications
Publisher	Data powered by TypesetElsevier BV
ISSN	2214-2126
Open Access	0