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3D DWT-DCT and Logistic MAP Based Robust Watermarking for Medical Volume Data.

Li J, Liu Y, Zhong J - Open Biomed Eng J (2014)

Bottom Line: Applying digital watermarking technique for the security protection of medical information systems is a hotspot of research in recent years.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.

View Article: PubMed Central - PubMed

Affiliation: College of Information Science and Technology, Hainan University, Haikou, China, 570228.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Different attacks: (a) Original volume data; (b) Gaussian noise(3%); (c) JPEG compression(4%); (d) Median filter([3×3]) ;(e)Rotation(20°); (f) Scaling(0.5 times); (g) Translation(10%, down); (h) Cropping(8%, from z direction).
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Figure 4: Different attacks: (a) Original volume data; (b) Gaussian noise(3%); (c) JPEG compression(4%); (d) Median filter([3×3]) ;(e)Rotation(20°); (f) Scaling(0.5 times); (g) Translation(10%, down); (h) Cropping(8%, from z direction).

Mentions: Applying 3D DWT-DCT, the feature vector of the medical volume data can be obtained. Feature vector of the medical volume data is a group of symbol sequence which represents the visual feature of the medical image. Firstly, 3D-DWT is applied to the original medical volume data to obtain the approximated sub-band LLL1. Then, DCT of the whole LLL1 is computed and the DWT-DCT coefficient is obtained. We choose 8 low-frequency 3D DWT-DCT coefficients (F(1,1,1), F(1,2,1),F(1,1,2),… F(1,2,4)) to compose the coefficient sequence of the volume data, the value of the low-frequency coefficients may change under some attacks. However, the signs of the coefficients remain unchanged, as shown in Table 1. The different attacked images are shown in Fig. (4a-4h). If the coefficient is positive or zero value, it is denoted as “1”; otherwise, it is denoted as “0”. Thus, we can obtain the sign sequence of low-frequency coefficients as shown in Table 1. We can see that the sign sequence remains unchanged after common and geometrical attacks.


3D DWT-DCT and Logistic MAP Based Robust Watermarking for Medical Volume Data.

Li J, Liu Y, Zhong J - Open Biomed Eng J (2014)

Different attacks: (a) Original volume data; (b) Gaussian noise(3%); (c) JPEG compression(4%); (d) Median filter([3×3]) ;(e)Rotation(20°); (f) Scaling(0.5 times); (g) Translation(10%, down); (h) Cropping(8%, from z direction).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4382563&req=5

Figure 4: Different attacks: (a) Original volume data; (b) Gaussian noise(3%); (c) JPEG compression(4%); (d) Median filter([3×3]) ;(e)Rotation(20°); (f) Scaling(0.5 times); (g) Translation(10%, down); (h) Cropping(8%, from z direction).
Mentions: Applying 3D DWT-DCT, the feature vector of the medical volume data can be obtained. Feature vector of the medical volume data is a group of symbol sequence which represents the visual feature of the medical image. Firstly, 3D-DWT is applied to the original medical volume data to obtain the approximated sub-band LLL1. Then, DCT of the whole LLL1 is computed and the DWT-DCT coefficient is obtained. We choose 8 low-frequency 3D DWT-DCT coefficients (F(1,1,1), F(1,2,1),F(1,1,2),… F(1,2,4)) to compose the coefficient sequence of the volume data, the value of the low-frequency coefficients may change under some attacks. However, the signs of the coefficients remain unchanged, as shown in Table 1. The different attacked images are shown in Fig. (4a-4h). If the coefficient is positive or zero value, it is denoted as “1”; otherwise, it is denoted as “0”. Thus, we can obtain the sign sequence of low-frequency coefficients as shown in Table 1. We can see that the sign sequence remains unchanged after common and geometrical attacks.

Bottom Line: Applying digital watermarking technique for the security protection of medical information systems is a hotspot of research in recent years.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.

View Article: PubMed Central - PubMed

Affiliation: College of Information Science and Technology, Hainan University, Haikou, China, 570228.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus