Improving the performance of DCT-based fragile watermarking using intelligent optimization algorithms
TL;DR: The performance of a fragile watermarking method based on discrete cosine transform (DCT) has been improved in this paper by using intelligent optimization algorithms (IOA), namely genetic algorithm, differential evolution algorithm, clonal selection algorithm and particle swarm optimization algorithm.
About: This article is published in Optics Communications.The article was published on 2009-07-15. It has received 92 citations till now. The article focuses on the topics: Clonal selection algorithm & Genetic algorithm.
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TL;DR: The proposed algorithm for multiple watermarking based on discrete wavelet transforms, discrete cosine transform and singular value decomposition has been proposed for healthcare applications and has been found to be giving excellent performance for robustness, imperceptibility, capacity and security simultaneously.
Abstract: In this paper, an algorithm for multiple watermarking based on discrete wavelet transforms (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) has been proposed for healthcare applications. For identity authentication purpose, the proposed method uses three watermarks in the form of medical Lump image watermark, the doctor signature/identification code and diagnostic information of the patient as the text watermarks. In order to improve the robustness performance of the image watermark, Back Propagation Neural Network (BPNN) is applied to the extracted image watermark to reduce the noise effects on the watermarked image. The security of the image watermark is also enhanced by using Arnold transform before embedding into the cover. Further, the symptom and signature text watermarks are also encoded by lossless arithmetic compression technique and Hamming error correction code respectively. The compressed and encoded text watermark is then embedded into the cover image. Experimental results are obtained by varying the gain factor, different sizes of text watermarks and the different cover image modalities. The results are provided to illustrate that the proposed method is able to withstand a different of signal processing attacks and has been found to be giving excellent performance for robustness, imperceptibility, capacity and security simultaneously. The robustness performance of the method is also compared with other reported techniques. Finally, the visual quality of the watermarked image is evaluated by the subjective method also. This shows that the visual quality of the watermarked images is acceptable for diagnosis at different gain factors. Therefore the proposed method may find potential application in prevention of patient identity theft in healthcare applications.
227 citations
TL;DR: An improved SVD-based watermarking technique considering human visual characteristics is presented and experimental results are provided to demonstrate the proposed approach is able to withstand a variety of image processing attacks.
168 citations
TL;DR: This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in the discrete wavelet transform (DWT) domain that outperformed several previous schemes in terms of imperceptibility and robustness.
Abstract: Digital watermarking has been suggested as a way to achieve digital protection. The aim of digital watermarking is to insert the secret data into the image without significantly affecting the visual quality. This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in the discrete wavelet transform (DWT) domain. The proposed method is considered to be a block-based scheme that utilises the entropy and edge entropy as HVS characteristics for the selection of significant blocks to embed the watermark, which is a binary watermark logo. The blocks of the lowest entropy values and edge entropy values are selected as the best regions to insert the watermark. After the first level of DWT decomposition, the SVD is performed on the low-low sub-band to modify several elements in its U matrix according to predefined conditions. The experimental results of the proposed scheme showed high imperceptibility and high robustness against all image processing attacks and several geometrical attacks using examples of standard and real images. Furthermore, the proposed scheme outperformed several previous schemes in terms of imperceptibility and robustness. The security issue is improved by encrypting a portion of the important information using Advanced Standard Encryption a key size of 192-bits (AES-192).
160 citations
TL;DR: Experimental results indicate that the proposed reversible watermarking method is not only highly competitive, but also outperforms the existing methods.
Abstract: A reversible watermarking method is proposed with wavelet transforms and SVD.Signature and logo data are inserted by recursive dither modulation algorithm.DE is explored to design the quantization steps optimally.Good balance of imperceptibility, robustness and capacity is obtained by DE.Experiments show good performance and outperform the related algorithms. Currently, most medical images are stored and exchanged with little or no security; hence it is important to provide protection for the intellectual property of these images in a secured environment. In this paper, a new and reversible watermarking method is proposed to address this security issue. Specifically, signature information and textual data are inserted into the original medical images based on recursive dither modulation (RDM) algorithm after wavelet transform and singular value decomposition (SVD). In addition, differential evolution (DE) is applied to design the quantization steps (QSs) optimally for controlling the strength of the watermark. Using these specially designed hybrid techniques, the proposed watermarking technique obtains good imperceptibility and high robustness. Experimental results indicate that the proposed method is not only highly competitive, but also outperforms the existing methods.
127 citations
Cites methods from "Improving the performance of DCT-ba..."
...…Lee, Yoo, & Kalker, 2007), lifting wavelet transform (LWT) (Lei, Soon, Zhou, Li, & Lei, 2012b; Lei et al., 2013b), discrete cosine transform (DCT) (Aslantas et al., 2009; Lei, Soon, & Li, 2011), and singular value decomposition (SVD) (Run et al., 2012) rather than in spatial domain (Liu & Tan,…...
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...Consequently, many intelligent techniques such as differential evolution (DE) (Ali & Ahn, 2014; Aslantas, 2009; Lei, Soon, & Tan, 2013b), constrained clonal selection algorithm (Aslantas et al., 2009), particle swarm optimization (PSO) (Lei, Song, & Rahman, 2012a; Lei, Song, & Rahman, 2013a; Run et al....
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...It is very common that intelligent algorithms (Aslantas, 2009; Aslantas et al., 2009; Kumsawat et al., 2005; Liu & Tan, 2002; Run et al., 2012) are utilized to obtain desirable performance by optimizing one or two parameters....
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...Most existing watermarking methods use intelligent approach to obtain a good tradeoff between imperceptibly and capacity (An et al., 2012; Arsalan et al., 2012; Aslantas et al., 2009; Kumsawat et al., 2005; Shih & Wu, 2005; Wang, Lin, & Yang, 2011)....
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...…techniques such as differential evolution (DE) (Ali & Ahn, 2014; Aslantas, 2009; Lei, Soon, & Tan, 2013b), constrained clonal selection algorithm (Aslantas et al., 2009), particle swarm optimization (PSO) (Lei, Song, & Rahman, 2012a; Lei, Song, & Rahman, 2013a; Run et al., 2012), and genetic…...
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TL;DR: A new scheme based on a combination of DWT, DCT, and SVD domains is presented, and an inventional synchronization technique to recover geometrically attacked image via detection of desired image corners is proposed.
123 citations
Cites background from "Improving the performance of DCT-ba..."
...The most important properties of an effiient watermarking algorithm are [5,6]: (1) imperceptibility (i....
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References
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06 Aug 2002
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Abstract: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.
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TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Abstract: Name of founding work in the area. Adaptation is key to survival and evolution. Evolution implicitly optimizes organisims. AI wants to mimic biological optimization { Survival of the ttest { Exploration and exploitation { Niche nding { Robust across changing environments (Mammals v. Dinos) { Self-regulation,-repair and-reproduction 2 Artiicial Inteligence Some deenitions { "Making computers do what they do in the movies" { "Making computers do what humans (currently) do best" { "Giving computers common sense; letting them make simple deci-sions" (do as I want, not what I say) { "Anything too new to be pidgeonholed" Adaptation and modiication is root of intelligence Some (Non-GA) branches of AI: { Expert Systems (Rule based deduction)
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01 May 1992
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
Abstract: From the Publisher:
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications.
In its most familiar form, adaptation is a biological process, whereby organisms evolve by rearranging genetic material to survive in environments confronting them. In this now classic work, Holland presents a mathematical model that allows for the nonlinearity of such complex interactions. He demonstrates the model's universality by applying it to economics, physiological psychology, game theory, and artificial intelligence and then outlines the way in which this approach modifies the traditional views of mathematical genetics.
Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways. Along the way he accounts for major effects of coadaptation and coevolution: the emergence of building blocks, or schemata, that are recombined and passed on to succeeding generations to provide, innovations and improvements.
John H. Holland is Professor of Psychology and Professor of Electrical Engineering and Computer Science at the University of Michigan. He is also Maxwell Professor at the Santa Fe Institute and isDirector of the University of Michigan/Santa Fe Institute Advanced Research Program.
12,584 citations
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01 Jan 1959
TL;DR: The clonal selection theory of acquired immunity is studied as a theory of selection for immunity in the context of infectious disease.
Abstract: The clonal selection theory of acquired immunity , The clonal selection theory of acquired immunity , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
2,208 citations
TL;DR: This paper compares two evolutionary computation paradigms: genetic algorithms and particle swarm optimization, and suggests ways in which performance might be improved by incorporating features from one paradigm into the other.
Abstract: This paper compares two evolutionary computation paradigms: genetic algorithms and particle swarm optimization. The operators of each paradigm are reviewed, focusing on how each affects search behavior in the problem space. The goals of the paper are to provide additional insights into how each paradigm works, and to suggest ways in which performance might be improved by incorporating features from one paradigm into the other.
1,661 citations