scholarly journals A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
V. Seenivasagam ◽  
R. Velumani
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Patient Data ◽  
Qr Code ◽  
Patient Records ◽  
Patient Identification ◽  
Geometric Attacks ◽  
Zero Watermarking ◽  
Value Decomposition ◽  
Watermarking Scheme

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu’s invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.

scholarly journals A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

2019 ◽  
Vol 9 (4) ◽  
pp. 700 ◽  
Author(s):  
Jing Liu ◽  
Jingbing Li ◽  
Jixin Ma ◽  
Naveed Sadiq ◽  
Uzair Bhatti ◽  
...  
Keyword(s):  
Medical Image ◽  
Feature Vector ◽  
Medical Images ◽  
Complex Wavelet Transform ◽  
Hénon Map ◽  
Henon Map ◽  
Geometric Attacks ◽  
Watermark Embedding ◽  
Zero Watermarking ◽  
Blind Extraction

To resolve the contradiction between existing watermarking methods—which are not compatible with the watermark’s ability to resist geometric attacks—and robustness, a robust multi-watermarking algorithm suitable for medical images is proposed. First, the visual feature vector of the medical image was obtained by dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) to perform multi-watermark embedding and extraction. Then, the multi-watermark was preprocessed using the henon map chaotic encryption technology to strengthen the security of watermark information, and combined with the concept of zero watermark to make the watermark able to resist both conventional and geometric attacks. Experimental results show that the proposed algorithm can effectively extract watermark information; it implements zero watermarking and blind extraction. Compared with existing watermark technology, it has good performance in terms of its robustness and resistance to geometric attacks and conventional attacks, especially in geometric attacks.

scholarly journals Dual Zero-Watermarking Scheme for Two-Dimensional Vector Map Based on Delaunay Triangle Mesh and Singular Value Decomposition

2019 ◽  
Vol 9 (4) ◽  
pp. 642 ◽  
Author(s):  
Xu Xi ◽  
Xinchang Zhang ◽  
Weidong Liang ◽  
Qinchuan Xin ◽  
Pengcheng Zhang
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Two Dimensional ◽  
Triangle Mesh ◽  
Vector Map ◽  
Vector Maps ◽  
Feature Sequence ◽  
Zero Watermarking ◽  
Value Decomposition ◽  
Watermarking Scheme

Digital watermarking is important for the copyright protection of electronic data, but embedding watermarks into vector maps could easily lead to changes in map precision. Zero-watermarking, a method that does not embed watermarks into maps, could avoid altering vector maps but often lack of robustness. This study proposes a dual zero-watermarking scheme that improves watermark robustness for two-dimensional (2D) vector maps. The proposed scheme first extracts the feature vertices and non-feature vertices of the vector map with the Douglas-Peucker algorithm and subsequently constructs the Delaunay Triangulation Mesh (DTM) to form a topological feature sequence of feature vertices as well as the Singular Value Decomposition (SVD) matrix to form intrinsic feature sequence of non-feature vertices. Next, zero-watermarks are obtained by executing exclusive disjunction (XOR) with the encrypted watermark image under the Arnold scramble algorithm. The experimental results show that the scheme that synthesizes both the feature and non-feature information improves the watermark capacity. Making use of complementary information between feature and non-feature vertices considerably improves the overall robustness of the watermarking scheme. The proposed dual zero-watermarking scheme combines the advantages of individual watermarking schemes and is robust against such attacks as geometric attacks, vertex attacks and object attacks.

scholarly journals A Polar Complex Exponential Transform-Based Zero-Watermarking for Multiple Medical Images with High Discrimination

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wenbing Wang ◽  
Yan Li ◽  
Shengli Liu
Keyword(s):  
Medical Images ◽  
Computation Time ◽  
Image Features ◽  
Computational Time ◽  
Geometric Attacks ◽  
Exponential Transform ◽  
Zero Watermarking ◽  
Polar Complex Exponential Transform ◽  
The Stability ◽  
Complex Exponential

Zero-watermarking is one of the solutions for image copyright protection without tampering with images, and thus it is suitable for medical images, which commonly do not allow any distortion. Moment-based zero-watermarking is robust against both image processing and geometric attacks, but the discrimination of watermarks is often ignored by researchers, resulting in the high possibility that host images and fake host images cannot be distinguished by verifier. To this end, this paper proposes a PCET- (polar complex exponential transform-) based zero-watermarking scheme based on the stability of the relationships between moment magnitudes of the same order and stability of the relationships between moment magnitudes of the same repetition, which can handle multiple medical images simultaneously. The scheme first calculates the PCET moment magnitudes for each image in an image group. Then, the magnitudes of the same order and the magnitudes of the same repetition are compared to obtain the content-related features. All the image features are added together to obtain the features for the image group. Finally, the scheme extracts a robust feature vector with the chaos system and takes the bitwise XOR of the robust feature and a scrambled watermark to generate a zero-watermark. The scheme produces robust features with both resistance to various attacks and low similarity among different images. In addition, the one-to-many mapping between magnitudes and robust feature bits reduces the number of moments involved, which not only reduces the computation time but also further improves the robustness. The experimental results show that the proposed scheme meets the performance requirements of zero-watermarking on the robustness, discrimination, and capacity, and it outperforms the state-of-the-art methods in terms of robustness, discrimination, and computational time under the same payloads.

scholarly journals Medical Image Authentication using Stationary Wavelet Transformation and Singular Value Decomposition

2019 ◽  
Vol 8 (3) ◽  
pp. 953-958
Keyword(s):  
Singular Value Decomposition ◽  
Medical Image ◽  
Wavelet Transformation ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Image Authentication ◽  
Transformation Method ◽  
Singular Value ◽  
Invariance Property ◽  
Value Decomposition

he proposed paper work is implemented using Stationary Wavelet Transformation (SWT) with Singular Value Decomposition (SVD).Even though, there are many other transformations, the Stationary Wavelet Transformation method is chosen for its shift invariance property. The designed method has three steps; the first step is the decomposing of the Medical image into sub-bands using SWT to find the value of sub band and as a second step is to apply SVD, third step will combine both the images with scaling factor. The experiments were conducted over gray scale of MRI and CT Medical images. The statistics of proposed method indicates that imperceptibility of Watermarked Medical images have a Peak Signal to Noise Ratio (PSNR) value of 50 DB for medical images. The robustness is ensured by having Correlation Coefficient (CC) of 1 for the retrieved watermark images. Security for the watermark is extended by encrypting the watermark with chaotic sequence.

A High-Capacity Reversible Watermarking Scheme Based on Shape Decomposition for Medical Images

2018 ◽  
Vol 33 (01) ◽  
pp. 1950001 ◽  
Author(s):  
Xin Zhong ◽  
Frank Y. Shih
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Saliency Detection ◽  
High Capacity ◽  
Detection Algorithm ◽  
Cross Sectional ◽  
Shape Decomposition ◽  
Image Fidelity ◽  
Embedded Image ◽  
Watermarking Scheme

We present a high-capacity reversible, fragile, and blind watermarking scheme for medical images in this paper. A bottom-up saliency detection algorithm is applied to automatically locate the multiple arbitrarily-shaped regions of interest (ROIs). The iterative square-production algorithm is developed to generate different sizes of squares for shape decomposition on the regions of noninterest (RONIs). This scheme of combining the frequency-domain watermarking and arbitrarily-shaped ROI methods can significantly increase the watermarking capacity, whereas the embedded image fidelity is preserved. Extensive experiments were carried out on the OASIS medical image dataset, which consists of a cross-sectional collection of 416 subjects, aged from 18 to 96 years old. The results show that the proposed scheme outperforms six existing state-of-the-art schemes in terms of watermarking capacity and embedded image fidelity.

A FRT - SVD Based Blind Medical Watermarking Technique for Telemedicine Applications

2021 ◽  
pp. 632-653
Author(s):  
Surekah Borra ◽  
Rohit Thanki
Keyword(s):  
Singular Value Decomposition ◽  
Medical Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Region Of Interest ◽  
Singular Value ◽  
Ridgelet Transform ◽  
Simulation Results ◽  
The Individual ◽  
Value Decomposition

In this article, a blind and robust medical image watermarking technique based on Finite Ridgelet Transform (FRT) and Singular Value Decomposition (SVD) is proposed. A host medical image is first transformed into 16 × 16 non-overlapping blocks and then ridgelet transform is applied on the individual blocks to obtain sets of ridgelet coefficients. SVD is then applied on these sets, to obtain the corresponding U, S and V matrix. The watermark information is embedded into the host medical image by modification of the value of the significant elements of U matrix. This proposed technique is tested on various types of medical images such as X-ray and CT scan. The simulation results revealed that this technique provides better imperceptibility, with an average PSNR being 42.95 dB for all test medical images. This technique also overcomes the limitation of the existing technique which is applicable on only the Region of Interest (ROI) of the medical image.

An Immune Secret QR-Code Sharing based on a Twofold Zero-Watermarking Scheme

2015 ◽  
Vol 10 (4) ◽  
pp. 399-412 ◽  
Author(s):  
Jumana Waleed ◽  
Huang Dong Jun ◽  
Sarah Saadoon ◽  
Saad Hameed ◽  
Hiyam Hatem
Keyword(s):  
Qr Code ◽  
Code Sharing ◽  
Zero Watermarking ◽  
Watermarking Scheme
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