Watermarking Techniques used in Medical Images: a Survey
TL;DR: This paper aims to provide a useful survey on watermarking and offer a clear perspective for interested researchers by analyzing the strengths and weaknesses of different existing methods.
Abstract: The ever-growing numbers of medical digital images and the need to share them among specialists and hospitals for better and more accurate diagnosis require that patients’ privacy be protected. As a result of this, there is a need for medical image watermarking (MIW). However, MIW needs to be performed with special care for two reasons. Firstly, the watermarking procedure cannot compromise the quality of the image. Secondly, confidential patient information embedded within the image should be flawlessly retrievable without risk of error after image decompressing. Despite extensive research undertaken in this area, there is still no method available to fulfill all the requirements of MIW. This paper aims to provide a useful survey on watermarking and offer a clear perspective for interested researchers by analyzing the strengths and weaknesses of different existing methods.
Citations
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TL;DR: This survey presents a brief discussion of different aspects of digital image watermarking, including major characteristics of digital watermark, novel and recent applications of watermarked, different kinds of water marking techniques and common watermark embedding and extraction process.
Abstract: This survey presents a brief discussion of different aspects of digital image watermarking. Included in the present discussion are these general concepts: major characteristics of digital watermark, novel and recent applications of watermarking, different kinds of watermarking techniques and common watermark embedding and extraction process. In addition, recent state-of-art watermarking techniques, potential issues and available solutions are discussed in brief. Further, the performance summary of the various state-of-art watermarking techniques is presented in tabular format. This survey contribution will be useful for the researchers to implement efficient watermarking techniques for secure e-governance applications.
114 citations
TL;DR: A survey of medical images watermarking is presented and offers an evident scene for concerned researchers by analysing the robustness and limitations of various existing approaches.
110 citations
Cites background or methods from "Watermarking Techniques used in Med..."
...DCT and DFT give the spectral description of the input image while DWT transforms the input image into predictions onto basis vectors....
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...All other coefficients are titled the AC coefficients [13]....
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...DFT denotes the most popular technique to convert the images from the spatial domain to transform domain [36]....
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...6, respectively [13]: 𝐹(𝑢, 𝑣) = ∑ ∑ 𝑓(𝑥, 𝑦)𝑒−𝑗2𝜋( 𝑢𝑥 𝑁 + 𝑣𝑦 𝑀 ) 𝑀−1 𝑦=0 𝑁−1 𝑥=0 (5) = 𝑅(𝑢, 𝑣) + 𝑗𝐼(𝑢, 𝑣) 𝑓(𝑥, 𝑦) = 1 𝑁𝑀 ∑ ∑ 𝐹(𝑢, 𝑣)𝑒𝑗2𝜋( 𝑢𝑥 𝑁 + 𝑣𝑦 𝑀 ) 𝑀−1 𝑣=0 𝑁−1 𝑢=0 (6) Where: F(u,v) is the DFT coefficient, u=0,1,2,…,M−1, and v=0,1,2,…,N−1, R(u,v) and I(u,v) are the real and imaginary parts of DFT, respectively....
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...DFT decomposes an image in sine and cosine form....
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TL;DR: General concepts of watermarking, major characteristics, recent applications, concepts of embedding and recovery process of watermarks, and the summary of various techniques are highlighted in brief.
Abstract: With the widespread growth of medical images and improved communication and computer technologies in recent years, authenticity of the images has been a serious issue for E-health applications. In order to this, various notable watermarking techniques are developed by potential researchers. However, those techniques are unable to solve many issues that are necessary to be measured in future investigations. This paper surveys various watermarking techniques in medical domain. Along with the survey, general concepts of watermarking, major characteristics, recent applications, concepts of embedding and recovery process of watermark, and the summary of various techniques (in tabular form) are highlighted in brief. Further, major issues associated with medical image watermarking are also discussed to find out research directions for fledgling researchers and developers.
78 citations
TL;DR: Experimental result shows, significant enhancement in both imperceptibility and robustness with the average of 46.9496 db and more than 99% respectively, while image blocking makes the capacity independent from the size of the host image.
74 citations
TL;DR: The hybrid method is suitable for avoidance of the patient identity theft/alteration/modification and secure medical document dissemination over the open channel for medical applications and is robust for hidden watermark at acceptable quality of the watermarked image.
Abstract: This paper presents a robust and secure region of interest and non-region of interest based watermarking method for medical images. The proposed method applies the combination of discrete wavelet transform and discrete cosine transforms on the cover medical image for the embedding of image and electronic patient records (EPR) watermark simultaneously. The embedding of multiple watermarks at the same time provides extra level of security and important for the patient identity verification purpose. Further, security of the image and EPR watermarks is enhancing by using message-digest (MD5) hash algorithm and Rivest---Shamir---Adleman respectively before embedding into the medical cover image. In addition, Hamming error correction code is applying on the encrypted EPR watermark to enhance the robustness and reduce the possibility bit error rates which may result into wrong diagnosis in medical environments. The robustness of the method is also extensively examined for known attacks such as salt & pepper, Gaussian, speckle, JPEG compression, filtering, histogram equalization. The method is found to be robust for hidden watermark at acceptable quality of the watermarked image. Therefore, the hybrid method is suitable for avoidance of the patient identity theft/alteration/modification and secure medical document dissemination over the open channel for medical applications.
68 citations
References
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TL;DR: A "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information is pursued and it is shown that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves.
Abstract: The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, such as curvelets, that first develop a transform in the continuous domain and then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Specifically, we construct a discrete-domain multiresolution and multidirection expansion using nonseparable filter banks, in much the same way that wavelets were derived from filter banks. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and, thus, it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise link between the developed filter bank and the associated continuous-domain contourlet expansion via a directional multiresolution analysis framework. We show that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing applications.
3,948 citations
"Watermarking Techniques used in Med..." refers methods in this paper
...The other transform-based scheme is the contourlet transform (CT), introduced by Minh Do and Martin Vetterli [70, 71]....
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TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
Abstract: Reversible data embedding has drawn lots of interest recently Being reversible, the original digital content can be completely restored We present a novel reversible data-embedding method for digital images We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low
2,739 citations
"Watermarking Techniques used in Med..." refers methods in this paper
...The proposed method was based on difference expansion (DE) technique which was proposed by Tian (2003) [94]....
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TL;DR: Several methods for filter design are described for dual-tree CWT that demonstrates with relatively short filters, an effective invertible approximately analytic wavelet transform can indeed be implemented using the dual- tree approach.
Abstract: The paper discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing The authors use the complex number symbol C in CWT to avoid confusion with the often-used acronym CWT for the (different) continuous wavelet transform The four fundamentals, intertwined shortcomings of wavelet transform and some solutions are also discussed Several methods for filter design are described for dual-tree CWT that demonstrates with relatively short filters, an effective invertible approximately analytic wavelet transform can indeed be implemented using the dual-tree approach
2,407 citations
TL;DR: It is proved analytically and shown experimentally that the peak signal-to-noise ratio of the marked image generated by this method versus the original image is guaranteed to be above 48 dB, which is much higher than that of all reversible data hiding techniques reported in the literature.
Abstract: A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.
2,240 citations
11 May 2004
TL;DR: A novel approach to face recognition which considers both shape and texture information to represent face images and the simplicity of the proposed method allows for very fast feature extraction.
Abstract: In this work, we present a novel approach to face recognition which considers both shape and texture information to represent face images. The face area is first divided into small regions from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single, spatially enhanced feature histogram efficiently representing the face image. The recognition is performed using a nearest neighbour classifier in the computed feature space with Chi square as a dissimilarity measure. Extensive experiments clearly show the superiority of the proposed scheme over all considered methods (PCA, Bayesian Intra/extrapersonal Classifier and Elastic Bunch Graph Matching) on FERET tests which include testing the robustness of the method against different facial expressions, lighting and aging of the subjects. In addition to its efficiency, the simplicity of the proposed method allows for very fast feature extraction.
2,191 citations