Zero-Watermarking Algorithm for Medical Image Based on VGG19 Deep Convolution Neural Network.

Yuanyuan Jia,Baoru Han,Lingwei Xu,Huazheng Zhu,Jinglong Du

doi:10.1155/2021/5551520

Abstract

Aiming at the security issues in the storage and transmission of medical images in the medical information system, combined with the special requirements of medical images for the protection of lesion areas, this paper proposes a robust zero-watermarking algorithm for medical images' security based on VGG19. First, the pretrained VGG19 is used to extract deep feature maps of medical images, which are fused into the feature image. Second, the feature image is transformed by Fourier transform, and low-frequency coefficients of the Fourier transform are selected to construct the feature matrix of the medical image. Then, based on the low-frequency part of the feature matrix of the medical image, the mean-perceptual hashing algorithm is used to achieve a set of 64-bit binary perceptual hashing values, which can effectively resist local nonlinear geometric attacks. Finally, the algorithm adopts a watermarking image after scrambling and the 64-bit binary perceptual hashing value to obtain robust zero-watermarking. At the same time, the proposed algorithm utilizes Hermite chaotic neural network to scramble the watermarking image for secondary protection, which enhances the security of the algorithm. Compared with the existing related works, the proposed algorithm is simple to implement and can effectively resist local nonlinear geometric attacks, with good robustness, security, and invisibility.

Highlights

With the construction of hospital normalization, digitization is widely applied in the medical field [1]
Experimental results show that the proposed algorithm can effectively resist local nonlinear geometric attacks and display the superior performance of the proposed algorithm compared with other watermarking algorithms
If the origin of the two-dimensional discrete Fourier transform matrix is set in the upper left corner, the energy of the image will be concentrated in the four corners of the coefficient matrix. is is determined by the nature of the two-dimensional discrete Fourier transform itself

Summary

Introduction

With the construction of hospital normalization, digitization is widely applied in the medical field [1]. Erefore, the ability of the algorithm to resist geometric attacks has become a research hotspot in the field of medical image zero-watermarking [1, 12]. These geometric attacks mainly refer to global geometric transformation (rotation, scaling, translation, etc.), which is a kind of linear transformation. A zero-watermarking algorithm based on VGG19 against local nonlinear geometric attacks is proposed in this paper In this algorithm, VGG19 can extract complex high-level features using a deep structure with powerful representation and learning ability. Experimental results show that the proposed algorithm can effectively resist local nonlinear geometric attacks and display the superior performance of the proposed algorithm compared with other watermarking algorithms

The Fundamental Theory

Zero-Watermarking Embedding and Extraction Algorithm

Experiment and Analysis

Algorithm Comparison

Method

Findings

Conclusions