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 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.

DAUBECHIES COMPLEX WAVELET TRANSFORM BASED TECHNIQUE FOR DENOISING OF MEDICAL IMAGES

2007 ◽  
Vol 07 (04) ◽  
pp. 663-687 ◽  
Author(s):  
ASHISH KHARE ◽  
UMA SHANKER TIWARY
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Medical Image ◽  
Medical Images ◽  
Universal Method ◽  
Complex Wavelet Transform ◽  
Shrinkage Function ◽  
Daubechies Complex Wavelet Transform ◽  
Complex Wavelet

Wavelet based denoising is an effective way to improve the quality of images. Various methods have been proposed for denoising using real-valued wavelet transform. Complex valued wavelets exist but are rarely used. The complex wavelet transform provides phase information and it is shift invariant in nature. In medical image denoising, both removal of phase incoherency as well as maintaining the phase coherency are needed. This paper is an attempt to explore and apply the complex Daubechies wavelet transform for medical image denoising. We have proposed a method to compute a complex threshold, which does not depend on any assumed model of noise. In this sense this is a "universal" method. The proposed complex-domain shrinkage function depends on mean, variance and median of wavelet coefficients. To test the effectiveness of the proposed method, we have computed the input and output SNR and PSNR of various types of medical images. The method gives an improvement for Gaussian additive, Speckle and Salt-&-Pepper noise as well as for the mixture of these noise types for a range of noisy images with 15 db to 30 db noise levels and outperforms other real-valued wavelet transform based methods. The application of the proposed method to Ultrasound, X-ray and MRI images is demonstrated in the experiments.

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.

Multiple Watermarks Algorithm for Medical Image Based on Arnold Scrambling and DFT

2013 ◽  
Vol 380-384 ◽  
pp. 4116-4119
Author(s):  
Miao Sui ◽  
Jing Bing Li ◽  
Yu Cong Duan
Keyword(s):  
Medical Image ◽  
Feature Vector ◽  
Region Of Interest ◽  
Third Party ◽  
Geometric Attacks ◽  
Arnold Scrambling ◽  
Network Transmission ◽  
Multiple Watermarks ◽  
Medical Accident ◽  
Accident Case

In the process of network transmission, when an exception occurs (such as forgery, tampering, information confusion), digital medical image, as a diagnostic basis, can not serve as the evidence of medical accident case. And the ROI of medical image is unable to tolerate significant changes. In order to deal these problems, we have proposed a multiple watermarks algorithm that uses Arnold scrambling to preprocess the original multiple watermarks, improving the security of watermarking, and combining the visual feature vector of image with the encryption technology and the concept of third-party. Moreover, the sophisticated process is needless to find the Region of Interest (ROI) of medical images. So compared with the existing medical watermarking techniques, it can embed much more data, with less complexity. The experimental results show that the scheme has strong robustness against common attacks and geometric attacks.

scholarly journals Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Yong Yang ◽  
Song Tong ◽  
Shuying Huang ◽  
Pan Lin
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
High Frequency ◽  
Medical Image ◽  
Medical Images ◽  
Discrete Wavelet ◽  
Fusion Method ◽  
Complex Wavelet Transform ◽  
Medical Image Fusion ◽  
Log Gabor

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.

scholarly journals Robust Zero Watermarking Algorithm for Medical Images Based on Zernike-DCT

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chengshan Yang ◽  
Jingbing Li ◽  
Uzair Aslam Bhatti ◽  
Jing Liu ◽  
Jixin Ma ◽  
...  
Keyword(s):  
Edge Detection ◽  
Medical Information ◽  
Medical Images ◽  
Detection Algorithm ◽  
Zernike Moment ◽  
Processing Efficiency ◽  
Edge Detection Algorithm ◽  
Geometric Attacks ◽  
Edge Points ◽  
Zero Watermarking

Digital medical system not only facilitates the storage and transmission of medical information but also brings information security problems. Aiming at the security of medical images, a robust zero watermarking algorithm for medical images based on Zernike-DCT is proposed. The algorithm first uses a chaotic logic sequence to preprocess and encrypt the watermark, then performs edge detection and Zernike moment processing on the original medical image to get the accurate edge points, and then performs discrete cosine transform (DCT) on them to get the feature vector. Finally, it combines perceptual Hash and zero watermark technology to generate the key to complete the watermark embedding and extraction. The algorithm has good robustness to conventional and geometric attacks, strong antinoise ability, high positioning accuracy, and processing efficiency and is superior to the classical edge detection algorithm in extraction effect. It is a stable and reliable image edge detection algorithm.

Zero-Watermark Resistant to MP3 Compression

2010 ◽  
Vol 121-122 ◽  
pp. 254-259 ◽  
Author(s):  
Jing Long Zuo ◽  
De Long Cui
Keyword(s):  
Feature Vector ◽  
Coefficient Matrix ◽  
Content Authentication ◽  
Copyright Information ◽  
Watermark Embedding ◽  
Base Matrix ◽  
Zero Watermarking ◽  
Watermarking Scheme ◽  
Non Negative Matrix Factorization ◽  
Mp3 Compression

Most watermarking schemes in literatures are usually implemented by embedding a mark in a host media itself for intended purposes. The existing techniques for watermarking are confronted with the problems of perceptible quality degradation and the inherent conflict between imperceptibility and robustness, which introduced by the watermark embedding. In this paper, we propose a novel audio zero-watermarking scheme for content authentication. First the audio is divided to frame by fixed length and then low-frequent and high-frequent components are obtained by three-level lifting-based wavelet transformation in every frame. Secondly the audio frame is approximately represented as a product of a base matrix and a coefficient matrix using non-negative matrix factorization (NMF). Finally the sum of each column in the coefficient matrix is calculated which is quantized to produce a feature vector, and then the copyright information is obtained by calculating the watermark and feature vector. Experiment results show that the proposed scheme is robust against Mp3 compression and secure.

scholarly journals A New Method for Medical Image Denoising using DTCWT and Bilateral Filter

2019 ◽  
Vol 8 (12) ◽  
pp. 2925-2930
Keyword(s):  
Image Denoising ◽  
Medical Image ◽  
Medical Images ◽  
Imaging Techniques ◽  
Ultrasound Image ◽  
Similarity Index ◽  
New Method ◽  
Wavelet Thresholding ◽  
Complex Wavelet Transform

The quality of digital medical images plays vital role in Non-invasive imaging techniques, which are suitable for medical diagnosis and treatment. Removal of noise from a noisy image without losing the diagnostic details in medical image is still a challenging task even though several denoising methods have been proposed since past years. The wavelet thresholding approach has been reported to be a highly successful method for image denoising. However, the main problem experienced in wavelet thresholding is smoothening of edges. In order to retain original texture while denoising medical images, several methods have been reported in literature. In this paper, we proposed, a new method based on combination of dual-tree complex wavelet transform (DTCWT) and bilateral filters for denoising of medical images. The proposed models are experimented on standard medical images, like MRI image of knee contaminated with Rician noise, CT Scan image of brain contaminated with Gaussian noise, Ultrasound image of liver contaminated with Speckle noise. The results have shown that denoised images using the proposed approach have better performance in terms of smoothness and accuracy compared with existing methods. To assess quality of denoised images the quality metrics, the standard Signal to Noise Ratio (SNR), Universal Image Quality Index (UQI) Mean square error (MSR), and Structural Similarity Index (SSIM) are employed.

Image zero-watermarking algorithm against geometric attacks based on Tchebichef moments

2013 ◽  
Vol 33 (2) ◽  
pp. 434-437 ◽  
Author(s):  
Xinghong CHENG ◽  
Yuqing HOU ◽  
Jingxing CHENG ◽  
Xin PU
Keyword(s):  
Geometric Attacks ◽  
Tchebichef Moments ◽  
Zero Watermarking
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