Irshad Ahmad Ansari

Robust and false positive free watermarking in IWT domain using SVD and ABC

Watermarking is used to protect the copyrighted materials from being misused and help us to know the lawful ownership. The security of any watermarking scheme is always a prime concern for the developer. In this work, the robustness and security issue of IWT (integer wavelet transform) and SVD (singular value decomposition) based watermarking is explored. Generally, SVD based watermarking techniques suffer with an issue of false positive problem. This leads to even authenticating the wrong owner. We are proposing a novel solution to this false positive problem; that arises in SVD based approach. Firstly, IWT is employed on the host image and then SVD is performed on this transformed host. The properties of IWT and SVD help in achieving high value of robustness. Singular values are used for the watermark embedding. In order to further improve the quality of watermarking, the optimization of scaling factor (mixing ratio) is performed with the help of artificial bee colony (ABC) algorithm. A comparison with other schemes is performed to show the superiority of proposed scheme.

Multipurpose image watermarking in the domain of DWT based on SVD and ABC

A novel multipurpose image watermarking algorithm is proposed in this work.Proposed scheme performs very efficiently in all the three purposes.Option to set user defined imperceptibility level.Auto calculation of optimization strengths to get maximum robustness.Even after multipurpose nature, the scheme can deal with complex attacks too. A multipurpose image watermarking scheme is proposed in the present work in order to provide tamper localization, self-recovery and ownership verification of the host image. For robust watermarking, gray scale watermark is utilized to provide generalization and wide applicability to proposed scheme. The host is first transformed into the wavelet domain using DWT (Discrete Wavelet Transform) and then singular values of transformed host are modified in accordance with the principal components of watermark. This insertion make the scheme free from false positive error as well as it provides a decent capacity too. After the insertion of robust watermark, the last two LSB (Least Significant Bit) of host are modified in such a way that it contains the scrambled and deterministic average representation of host itself along with the SVD (Singular Value Decomposition) based tamper localization information. The LSB insertion is used to locate the tampered region as well as to provide the self-recovery feature to the scheme. The robust insertion is also optimized with the help of ABC (Artificial Bee colony) in such a way that maximum robustness can be assured corresponding to user specific threshold of imperceptibility.

SVD Watermarking: Particle Swarm Optimization of Scaling Factors to Increase the Quality of Watermark

The quality of watermark mainly depends on scaling factor, i.e., the ratio in which we mix the host image and watermark image. This scaling factor should not be too low as it will degrade the quality of extracted watermark (robustness) hugely. Similarly, it should not be too high as it will degrade the quality of watermarked image (Imperceptibility) hugely. So there is a need of optimal selection of scaling factor to get a trade-off between robustness and imperceptibility. In this work, particle swarm optimization (PSO) has been used to choose the optimal values of the scaling factors. Singular value decomposition (SVD) has been used for the watermarking because of its high capacity. Five different attacks have been considered on the watermarked image. The simulation result shows that the SVD + PSO-based watermarking outperforms the watermarking based on SVD alone in all the five attacks.

Analysis of gray scale watermark in RGB host using SVD and PSO

The present study is conducted in two phases. In the first phase we analyze the different aspects of gray image watermarking in a colored host. Robustness and imperceptibility are used as analysis parameters. The approaches explored and compared in this study are - watermark embedding with any one of the three RGB (Red-Green-Blue) components (single channel embedding), multichannel watermark embedding (same watermark with all channels) and multichannel embedding with equally segmented watermark. SVD (Singular Value Decomposition) is used to calculate the singular values of host image and then appropriate scaling factor isused to embed the watermark and the watermarked image is subjected to different attacks. To secure the watermark from an unauthorized access Arnold transform is implemented. From the simulation results it is observed that segmented watermark approach is better than the other two approaches in terms of both robustness and imperceptibility. In the second phase, change of robustness and imperceptibility is studied with the change of scaling factor for which PSO (Particle swarm optimization) is employed to determine the optimal values of scaling factor. The results here indicate that the use of different scaling factors (optimal) for each RGB component provides better result in comparison to a single (optimal) scaling factor in segmented multichannel approach. Overall, the experimental analysis shows that the equal distribution of gray watermark over RGB components with PSO optimized scaling factors provides significant improvement in the quality of watermarked image and the quality of retrieved watermark even from the distorted watermarked image.

Artificial bee colony optimized robust-reversible image watermarking

The ownership verification of digital images is possible by the help of image watermarking. Watermarking make the image secure towards unlawful use; but at the same time, it causes some information loss too. Medical and defense are few fields, where even a small change in data can be very problematic. So there is need of reliable and lossless watermarking schemes. The present study is focused on the development of lossless watermarking method that can fulfill five basic requirements (robustness, reversibility, invisibility, security and capacity) of ideal lossless watermarking scheme maximally. Arnold transformed watermark is embedded into the host to restrict any unauthorized access of watermark even after extraction. Slantlet transformed coefficients are known to be quite robust towards image processing attacks; so block wise Slantlet transform is employed to resist the maximum attacks and to ensure a decent capacity. Mean values of transformed coefficients are used for embedding to increase the robustness and imperceptibility. The spatial domain overflow/underflow (due to embedding) is taken care by a post processing to satisfy the reversibility requirements. The embedding strength of watermarking is controlled with the help of artificial bee colony (ABC) in order to get an optimal tradeoff between invisibility and robustness. The proposed scheme is applied to a range of images to show its applicability to different domains.

Supplier Selection in Uncertain Environment: A Fuzzy MCDM Approach

This paper addresses a critical issue of selection of supplier occurred in supply chain of a manufacturing company. As there are lot more criteria present for decision making of suitable supplier selection among many, it becomes more challenging task for any company to make as this decision is entangled with company’s profit and time. So, to address this problem, this paper proposes a multi-criteria decision making (MCDM) method using Decision Making Trial and Evaluation Laboratory (DEMATEL) based on Analytic Network Process (ANP), i.e., DANP, with fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) to judiciously select suppliers based on important criteria and to point out interrelationships among dimensions and criteria in SCM by Network Relationship Map (NRM) for this company. Furthermore, the ranking is supported by sensitivity analysis.

PSO Optimized and Secured Watermarking Scheme Based on DWT and SVD

The present study proposed a robust and secure watermarking scheme to authenticate the digital images for ownership claim. The proposed watermarking scheme is making use of 2-level of DWT (Discrete wavelet transform) to provide high capacity of watermark embedding. The SVD (singular value decomposition) is performed on the host and watermark images. Then, principal components are calculated for watermark image. The use of principal components for watermark embedding makes the scheme free from false positive error. PSO (particle swarm optimization) optimized multiple scaling factors along with principal components are utilized for watermark embedding in the singular values of host image. The PSO-optimized scaling factor provides a very good tradeoff between imperceptibility and robustness of watermarking scheme. The scheme is also extended to use for color images. The proposed scheme provides a secured and high data embedding with good robustness toward different signal processing attacks.

BCI: an optimised speller using SSVEP

The proposed work is done in order to develop an optimised Brain-Computer Interface (BCI) system (speller) for people with severe motor impairments using SSVEP (Steady-State Visual Evoked Potentials). To make the system fast yet error-free, the optimisation of speller is divided into three domains: one is the design of smart encoding method for the selection of appeared characters on interface, second one is the optimal frequency choice and the last one is design of optimal feature classification algorithm. Three classification methods: threshold method, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are evaluated. An optimal user window is also carefully selected after many trails in order to maintain a decent communication rate. The optimised BCI system provides an average accuracy of 96% with character per minute (CPM) of 13 ± 2. Speller performs almost similar with new users too because inter-subject variability is tackle by SVM classifier.

PSO Optimized Multipurpose Image Watermarking Using SVD and Chaotic Sequence

This study proposes a novel method for multipurpose image watermarking for both ownership verification and tampered region localization. Two watermarks (robust and fragile) are inserted into the host image. Robust watermark insertion is done by PSO (particle swarm optimization) optimized scaling of the singular values; utilizing the singular value decomposition (SVD). Doing so, leads to reduction in visibility changes (better imperceptibility) of host image as well as enhanced performance of watermarked image towards attacks (better robustness). Fragile watermark insertion is done by making use of SVD and chaotic sequence (block feature’s dependent). The image is first divided into non overlapped blocks and block based Arnold transformed is performed. Then after, block grouping is done of scrambled blocks to breakdown their independence in order to sustain the vector quantization and collage attacks. The proposed scheme is tested against various signal processing attacks and results shows a good performance.