Medical volume data are always concerned with the breach of confidentiality. A robust watermarking technique, resisting conventional attack, is proposed in this paper. The watermarking technique is a zero-watermarking. Firstly, the original watermarking image scrambling opts to use a novel Chebyshev chaotic neural network. Secondly, the medical volume data are split into 64 non-overlapping sub-volume data, each of which is done by sub-block three-dimensional (3D) discrete cosine transform so as to obtain the direct-current components. Thirdly, the 64 direct-current components are subjected to standardized processing. Finally, the 64-bit feature vector is generated by the perceptual hashing, which is used for producing zero-watermarking.Therefore, the watermarking technique has a good robustness resisting conventional attacks. The results show that the watermarking technique used in medical volume data is effective. So the watermarking technique is suitable for medical volume data concerned with privacy protection, safety and management.
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