The Experts below are selected from a list of 30684 Experts worldwide ranked by ideXlab platform
F U Weibin - One of the best experts on this subject based on the ideXlab platform.
-
a robust watermarking algorithm of encrypted Medical Volume Data based on 3d dwt and 3d dct
DEStech Transactions on Computer Science and Engineering, 2017Co-Authors: X U Lian, Li Jingbing, F U WeibinAbstract:This work proposed a novel scheme for robust watermarking in the encrypted Medical Volume Data, which protects the original Medical Volume Data from the third party embedders. The original Medical Volume Data is encrypted using a selective partial encryption method based on 3D DCT and Logistic Map. In the watermark embedding phase, the watermark is associated with the feature vector of the encrypted Medical Volume Data, generating a key which will be used in watermark extraction. The feature vector of the encrypted Medical Volume Data is extracted in a way combining 3D DWT and 3D DCT. The watermark extraction is performed on the encrypted domain. The proposed watermarking algorithm realizes zero-watermarking technology in the encrypted domain, which has no effects on the encrypted Medical Volume Data. The experimental results show that the proposed watermarking scheme has good robustness to some normal and geometric attacks. Therefore, it has a good practical value.
X U Lian - One of the best experts on this subject based on the ideXlab platform.
-
a robust watermarking algorithm of encrypted Medical Volume Data based on 3d dwt and 3d dct
DEStech Transactions on Computer Science and Engineering, 2017Co-Authors: X U Lian, Li Jingbing, F U WeibinAbstract:This work proposed a novel scheme for robust watermarking in the encrypted Medical Volume Data, which protects the original Medical Volume Data from the third party embedders. The original Medical Volume Data is encrypted using a selective partial encryption method based on 3D DCT and Logistic Map. In the watermark embedding phase, the watermark is associated with the feature vector of the encrypted Medical Volume Data, generating a key which will be used in watermark extraction. The feature vector of the encrypted Medical Volume Data is extracted in a way combining 3D DWT and 3D DCT. The watermark extraction is performed on the encrypted domain. The proposed watermarking algorithm realizes zero-watermarking technology in the encrypted domain, which has no effects on the encrypted Medical Volume Data. The experimental results show that the proposed watermarking scheme has good robustness to some normal and geometric attacks. Therefore, it has a good practical value.
Li Jingbing - One of the best experts on this subject based on the ideXlab platform.
-
Robust watermarking algorithm for Medical Volume Data in internet of Medical things
'Institute of Electrical and Electronics Engineers (IEEE)', 2020Co-Authors: Liu Jing, Ma Jixin, Li Jingbing, Huang Mengxing, Sadiq Naveed, Ai YangAbstract:The advancement of 5G technology, big Data and cloud storage has promoted the rapid development of the Internet of Medical Things (IoMT). Based on the strict security requirements and high level of accuracy required for disease diagnosis and pathological analysis, 3D Medical Volume Data have been created in large numbers. The IoMT facilitates the rapid transfer of Medical information and also makes the protection of pathological information and privacy information of patients increasingly prominent. To solve the security problem, a robust zero-watermarking algorithm based on 3D hyperchaos and 3D dual-tree complex wavelet transform is proposed according to the selected feature of Medical Volume Data. The feature combines human visual features with improved perceptual hashing techniques. It is a robust and efficient binary sequence. When implementing the proposed algorithm, the watermark is first scrambled with 3D hyperchaos to enhance security. Then, 3D DTCWT-DCT transformation is applied to Medical Volume Data, and the low-frequency coefficients that can represent the features are selected and binarized to generate the secret key to complete the watermark embedding and extraction. Zero embedding and blind extraction ensure that the original Medical Volume Data is not altered in any form, which meets the special requirements for diagnosis. Simulation results show that the algorithm is robust and can effectively resist common attacks and geometric attacks. It used fewer robust features to effectively bound Medical Volume Data and watermark information, saved bandwidth, and satisfied the security of transmission and storage of Medical Volume Data in the Internet of Medical things. In particular, compared with state-of-the-art technology, the proposed algorithm improves the average NC value by 46.67% under geometric attacks
-
a robust watermarking algorithm of encrypted Medical Volume Data based on 3d dwt and 3d dct
DEStech Transactions on Computer Science and Engineering, 2017Co-Authors: X U Lian, Li Jingbing, F U WeibinAbstract:This work proposed a novel scheme for robust watermarking in the encrypted Medical Volume Data, which protects the original Medical Volume Data from the third party embedders. The original Medical Volume Data is encrypted using a selective partial encryption method based on 3D DCT and Logistic Map. In the watermark embedding phase, the watermark is associated with the feature vector of the encrypted Medical Volume Data, generating a key which will be used in watermark extraction. The feature vector of the encrypted Medical Volume Data is extracted in a way combining 3D DWT and 3D DCT. The watermark extraction is performed on the encrypted domain. The proposed watermarking algorithm realizes zero-watermarking technology in the encrypted domain, which has no effects on the encrypted Medical Volume Data. The experimental results show that the proposed watermarking scheme has good robustness to some normal and geometric attacks. Therefore, it has a good practical value.
-
Zero-watermarking Algorithm for Medical Volume Data Based on Difference Hashing
'Agora University of Oradea', 2015Co-Authors: Han Baoru, Li Jingbing, Li YujiaAbstract:In order to protect the copyright of Medical Volume Data, a new zerowatermarking algorithm for Medical Volume Data is presented based on Legendre chaotic neural network and difference hashing in three-dimensional discrete cosine transform domain. It organically combines the Legendre chaotic neural network, three-dimensional discrete cosine transform and difference hashing, and becomes a kind of robust zero-watermarking algorithm. Firstly, a new kind of Legendre chaotic neural network is used to generate chaotic sequences, which causes the original watermarking image scrambling. Secondly, it uses three-dimensional discrete cosine transform to the original Medical Volume Data, and the perception of the low frequency coefficient invariance in the three-dimensional discrete cosine transform domain is utilized to extract the first 4*5*4 coefficient in order to form characteristic matrix (16*5). Then, the difference hashing algorithm is used to extract a robust perceptual hashing value which is a binary sequence, with the length being 64-bit. Finally, the hashing value serves as the image features to construct the robust zero-watermarking. The results show that the algorithm can resist the attack, with good robustness and high security
S Tanaka - One of the best experts on this subject based on the ideXlab platform.
-
improving depth perception using multiple iso surfaces for transparent stereoscopic visualization of Medical Volume Data
2020Co-Authors: Kyoko Hasegawa, Liang Li, Yuichi Sakano, S TanakaAbstract:The development of imaging technologies such as computed tomography and magnetic resonance imaging has made it easier to obtain three-dimensional Data of the internal human body. Visualizing these Data helps us to understand the complicated internal structure of the human body. Transparent stereoscopic visualization using depth information is a good way to visualize internal body structure. However, the position and depth information often become unclear when three-dimensional Data are rendered transparently. In this study, we aimed to understand the structural understanding and correct depth perception in transparent stereoscopic visualization, and examined how depth perception changes by overlaying multiple iso-surfaces on transparently rendered image. The experimental results showed that multiple iso-surfaces improved the accuracy of perceived depth. It was effective when the opacity of the inner iso-surface was high and the distance between the inner iso-surface and the outer iso-surface was large.
-
contour lines to assist position recognition of slices in transparent stereoscopic visualization of Medical Volume Data
2019Co-Authors: Ikuya Morimoto, Kyoko Hasegawa, Liang Li, Yuichi Sakano, S TanakaAbstract:Visualizing multiple slices of a human body is useful in 3D image diagnosis. It provides a useful tool for the patients and trainees and enables a more comprehensive understanding of the inner structure. Computer graphics (CG) is commonly used for Medical Data visualization. The stereoscopic effect of the CG Data can be perceived using a stereoscopic display. However, for complex shape Data, it is difficult to perceive and handle the spatial information correctly. In this study, we carried out experiments to investigate how to correctly arrange and visualize transparent slices in transparent Volume Data using a multi-view autostereoscopic display. We expect that correct position of the slices can be correctly perceived by visualizing contour lines of the slices which were arranged at regular intervals along the line of sight. As a result, we found that the depth-contrast effect occurs by drawing contour lines.
-
particle based transparent fused visualization applied to Medical Volume Data
International Journal of Modeling Simulation and Scientific Computing, 2013Co-Authors: Kyoko Hasegawa, Saori Ojima, Yoshiyuki Shimokubo, Susumu Nakata, Kozaburo Hachimura, S TanakaAbstract:This paper proposes a method to create 3D fusion images, such as Volume–Volume, Volume–surface, and surface–surface fusion. Our method is based on the particle-based rendering, which uses tiny particles as rendering primitives. The method can create natural and comprehensible 3D fusion images simply by merging particles prepared for each element to be fused. Moreover, the method does not require particle sorting along the line of sight to realize right depth feel. We apply our method to realize comprehensible visualization of Medical Volume Data.
Jiling Zhong - One of the best experts on this subject based on the ideXlab platform.
-
retraction notice 3d dwt dct and logistic map based robust watermarking for Medical Volume Data
The Open Biomedical Engineering Journal, 2016Co-Authors: Yaoli Liu, Jiling ZhongAbstract:Applying digital watermarking technique for the security protection of Medical information systems is a hotspot of research in recent years. In this paper, we present a robust watermarking algorithm for Medical Volume Data using 3D DWT-DCT and Logistic Map. After applying Logistic Map to enhance the security of watermarking, the visual feature vector of Medical Volume Data is obtained using 3D DWT-DCT. Combining the feature vector, the third party concept and Hash function, a zero-watermarking scheme can be achieved. The proposed algorithm can mitigate the illogicality between robustness and invisibility. The experiment results show that the proposed algorithm is robust to common and geometrical attacks.
-
3d dwt dct and logistic map based robust watermarking for Medical Volume Data
The Open Biomedical Engineering Journal, 2014Co-Authors: Yaoli Liu, Jiling ZhongAbstract:Applying digital watermarking technique for the security protection of Medical information systems is a hotspot of research in recent years. In this paper, we present a robust watermarking algorithm for Medical Volume Data using 3D DWT-DCT and Logistic Map. After applying Logistic Map to enhance the security of watermarking, the visual feature vector of Medical Volume Data is obtained using 3D DWT-DCT. Combining the feature vector, the third party concept and Hash function, a zero-watermarking scheme can be achieved. The proposed algorithm can mitigate the illogicality between robustness and invisibility. The experiment results show that the proposed algorithm is robust to common and geometrical attacks.