Wavelet-based oblivious image watermarking scheme using genetic algorithm

Ramanjaneyulu, K.; Rajarajeswari, K.

doi:10.1049/iet-ipr.2010.0347

Cited by 59 publications

(41 citation statements)

References 17 publications

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“…After attacks, correlation is calculated. This comparison shows that performance of the proposed algorithm in terms of correlation is better than the existing algorithms [10].…”

Section: Jpeg2000 Compression Attackmentioning

confidence: 83%

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Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

Kasana¹,

Singh²,

Bhatia³

2015

J Inf Process Syst

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In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.

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“…After attacks, correlation is calculated. This comparison shows that performance of the proposed algorithm in terms of correlation is better than the existing algorithms [10].…”

Section: Jpeg2000 Compression Attackmentioning

confidence: 83%

“…After transformation, secret data is hidden into the transformed coefficients of the image. DWT based methods are discussed into [3][4][5][6][7][8][9][10]. In these methods, wavelet coefficients produced by DWT are used to embed the secret data bits.…”

Section: Introductionmentioning

confidence: 99%

Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

Kasana¹,

Singh²,

Bhatia³

2015

J Inf Process Syst

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“…Therefore, any optimization technique or algorithm can be used to find the minimum value of J . A genetic algorithm (GA) commonly is used to optimize the problem with the objective of achieving maximum robustness without sacrificing the transparency as mentioned in [15][16][17]. We also use a GA with a population of 100 and 200 generations to optimize the same problem in order to train the ANN.…”

Section: Selection Of Optimum Blocksmentioning

confidence: 99%

A new approach for digital image watermarking to predict optimal blocks using artificial neural networks

Movaghar¹,

Bizaki²

2017

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, we propose a novel nonblind digital image watermarking based on discrete wavelet transform and singular value decomposition. This robust scheme takes advantage of artificial neural networks for selecting suitable image blocks in which the watermark signal can be embedded. Local characteristics of the blocks such as luminance and texture sensitivity are the main criteria that the selections are based on. Generally, selection is based on a prediction of the results with the objective of transparency and watermark resilience. In other words, before embedding the water mark signal, it is estimated which blocks would be the best for embedding the signals to achieve the desired robustness and quality. Simulation results confirm the superiority of the proposed scheme in terms of the transparency of the images as well as robustness under various kinds of attacks.

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“…Veysel Aslantaset al [52] has used intelligent optimization algorithms for correcting the rounding errors caused by the transformation process. K. Ramanjaneyulu et al [53] has proposed a novel method for oblivious and robust image watermarking scheme using Multiple Descriptions Coding (MDC) and Quantization Index Modulation (QIM).Proposed scheme is characterized with Blocked Discrete Hadamard Transform (DHT) parameters and Genetic Algorithm (GA) is used for parameter optimization. The performance improvement is achieved over the existing methods in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Cross correlation (NCC).…”

Section: Genetic Algorithmmentioning

confidence: 99%

Computer Science & Information Technology ( CS & IT )

2015

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) were collocated with the ACITY-2015. The conferences attracted many local and international delegates, presenting a balanced mixture of intellect from the East and from the West.The goal of this conference series is to bring together researchers and practitioners from academia and industry to focus on understanding computer science and information technology and to establish new collaborations in these areas. Authors are invited to contribute to the conference by submitting articles that illustrate research results, projects, survey work and industrial experiences describing significant advances in all areas of computer science and information technology.The ACITY-2015, DPPR-2015, VLSI-2015, WiMNET-2015, AIAA-2015, CNDC-2015 Committees rigorously invited submissions for many months from researchers, scientists, engineers, students and practitioners related to the relevant themes and tracks of the workshop. This effort guaranteed submissions from an unparalleled number of internationally recognized top-level researchers. All the submissions underwent a strenuous peer review process which comprised expert reviewers. These reviewers were selected from a talented pool of Technical Committee members and external reviewers on the basis of their expertise. The papers were then reviewed based on their contributions, technical content, originality and clarity. The entire process, which includes the submission, review and acceptance processes, was done electronically. All these efforts undertaken by the Organizing and Technical Committees led to an exciting, rich and a high quality technical conference program, which featured high-impact presentations for all attendees to enjoy, appreciate and expand their expertise in the latest developments in computer network and communications research.In closing, ACITY-2015, DPPR-2015, VLSI-2015, WiMNET-2015, AIAA-2015, CNDC-2015 brought together researchers, scientists, engineers, students and practitioners to exchange and share their experiences, new ideas and research results in all aspects of the main workshop themes and tracks, and to discuss the practical challenges encountered and the solutions adopted. The book is organized as a collection of papers from the ACITY-2015, DPPR-2015, VLSI-2015, WiMNET-2015, AIAA-2015, CNDC-2015 We would like to thank the General and Program Chairs, organization staff, the members of the Technical Program Committees and external reviewers for their excellent and tireless work. We sincerely wish that all attendees benefited scientifically from the conference and wish them every success in their research. It is the humble wish of the conference organizers that the professional dialogue among the researchers, scientists, engineers, students and educators continues beyond the event and that the friendships and collaborations forged will linger and prosper for many years to come.

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Wavelet-based oblivious image watermarking scheme using genetic algorithm

Cited by 59 publications

References 17 publications

Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform

A new approach for digital image watermarking to predict optimal blocks using artificial neural networks

Computer Science & Information Technology ( CS & IT )

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