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- W4372081817 abstract "The amount of 3D data stored and transmitted in the Internet of Medical Things (IoMT) is increasing, making protecting these medical data increasingly prominent. However, there are relatively few researches on 3D data watermarking. Moreover, due to the particularity of medical data, strict data quality should be considered while protecting data security. To solve the problem, in the field of medical volume data, we proposed a robust watermarking algorithm based on Polar Cosine Transform and 3D-Discrete Cosine Transform (PCT and 3D-DCT). Each slice of the volume data was transformed by PCT to obtain feature row vector, and then the reshaped three-dimensional feature matrix was transformed by 3D-DCT. Based on the contour information of the volume data and the detail information of the inner slice, the visual feature vector was obtained by applying the perceptual hash. In addition, the watermark was encrypted by a multi-sensitive initial value Sine and Piecewise linear chaotic Mapping (SPM) system, and embedded as a zero watermark. The key was stored in a third party. Under the same experimental conditions, when the volume data is rotated by 80 degrees, cut 25% along the Z axis, and the JPEG compression quality is 1%, the Normalized Correlation Coefficient (NC) of the extracted watermark is 0.80, 0.89, and 1.00 respectively, which are significantly higher than the comparison algorithm." @default.
- W4372081817 created "2023-05-07" @default.
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- W4372081817 date "2023-01-01" @default.
- W4372081817 modified "2023-09-27" @default.
- W4372081817 title "Robust Watermarking Algorithm for Medical Volume Data Based on Polar Cosine Transform and 3D-DCT" @default.
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- W4372081817 doi "https://doi.org/10.32604/cmc.2023.036462" @default.
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