A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

In a telemedicine diagnosis system, the emergence of 3D imaging enables doctors to make clearer judgments, and its accuracy also directly affects doctors' diagnosis of the disease. In order to ensure the safe transmission and storage of medical data, a 3D medical watermarking algorithm based on wavelet transform is proposed in this paper. The proposed algorithm employs the principal component analysis (PCA) transform to reduce the data dimension, which can minimize the error between the extracted components and the original data in the mean square sense. Especially, this algorithm helps to create a bacterial foraging model based on particle swarm optimization (BF-PSO), by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding, thereby achieving the optimal balance between embedding capacity and imperceptibility. A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.

Automated summary

In this paper, a 3D medical watermarking algorithm based on wavelet transform is proposed, which utilizes PCA transform to reduce data dimension and a BF-PSO model to find the optimal embedding parameters, achieving the optimal balance between embedding capacity and imperceptibility. Experimental results based on a standard MRI brain volume dataset in MATLAB software show that the proposed algorithm has strong robustness and minimal deformation of the 3D model after watermark embedding.