Robust watermarking for medical images resistant to geometric attacks

2012 ◽  
Author(s):  
Muhammad Tahir Naseem ◽  
Ijaz Mansoor Qureshi ◽  
Atta-ur-Rahman ◽  
Muhammad Zeeshan Muzaffar
Keyword(s):  
Medical Images ◽  
Robust Watermarking ◽  
Geometric Attacks

A SVD and Modified Firefly Optimization Based Robust Digital Image Watermarking Technique

2017 ◽  
Vol 7 (7) ◽  
pp. 268
Author(s):  
Chauhan Usha ◽  
Singh Rajeev Kumar
Keyword(s):  
Digital Media ◽  
Firefly Algorithm ◽  
Image Watermarking ◽  
Singular Values ◽  
Robust Watermarking ◽  
Scaling Factors ◽  
Geometric Attacks ◽  
Host Image ◽  
Firefly Optimization ◽  
Value Decomposition

Digital Watermarking is a technology, to facilitate the authentication, copyright protection and Security of digital media. The objective of developing a robust watermarking technique is to incorporate the maximum possible robustness without compromising with the transparency. Singular Value Decomposition (SVD) using Firefly Algorithm provides this objective of an optimal robust watermarking technique. Multiple scaling factors are used to embed the watermark image into the host by multiplying these scaling factors with the Singular Values (SV) of the host image. Firefly Algorithm is used to optimize the modified host image to achieve the highest possible robustness and transparency. This approach can significantly increase the quality of watermarked image and provide more robustness to the embedded watermark against various attacks such as noise, geometric attacks, filtering attacks etc.

scholarly journals A Large Capacity Histogram-Based Watermarking Algorithm for Three Consecutive Bins

2018 ◽  
Vol 8 (12) ◽  
pp. 2617 ◽  
Author(s):  
Zhen Yue ◽  
Zichen Li ◽  
Hua Ren ◽  
Yixian Yang
Keyword(s):  
Information Hiding ◽  
Research Topic ◽  
Robust Watermarking ◽  
Large Capacity ◽  
Geometric Attacks ◽  
Watermark Embedding ◽  
Strong Robustness ◽  
Information Number ◽  
First Time ◽  
Cropping Attack

The histogram watermark, which performs watermark embedding by slightly modifying the histogram of the original image, has been a hot research topic in information hiding technology due to the superiority of its pixel modification during the watermark embedding process, which is independent of the pixel position. This property makes the histogram-based watermark strong resistant to geometric attacks, such as cropping attack, crossed attack, rotation attack, etc. In this paper, we propose a large capacity histogram-based robust watermarking algorithm based on three consecutive bins for the first time. In our scheme, we divide the shape of three consecutive bins into eight cases. According to these cases, we embed Information Number 0, 1, 2, 3, 4, 5, 6, or 7, respectively. The embedded information capacity reaches one bit per bin (bpb), and the amount of embedded information is equal to 200% of the previous existing algorithms. Experimental results show that the new algorithm not only has a large capacity of embedding information, but also has strong robustness to geometric attacks, as well as common image processing operations.

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 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.

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