Color Zero-Watermarking Algorithm for Medical Images Based on BEMD-Schur Decomposition and Color Visual Cryptography

Deyang Wu,Changbo Qu,Haichun Zheng,Sen Hu,Yong Tang,Jiayan Wang,Miaomiao Wang,Jing Zhao,Meiyu Zhong,Jinwei Wang

doi:10.1155/2021/7081194

Abstract

With the widespread use of medical images in telemedicine, personal information may be leaked. The traditional zero-watermarking technology has poor robustness under large-scale attacks. At the same time, most of the zero-watermarking information generated is a binary sequence with a single information structure. In order to effectively solve the poor robustness problem of traditional zero-watermarking under large-scale attacks, a color zero-watermarking algorithm for medical images based on bidimensional empirical mode decomposition (BEMD)-Schur decomposition and color visual cryptography is proposed. Firstly, the color carrier image and the color copyright logo are decomposed into R, G, and B three color components, respectively, and the feature value of each sub-block are extracted by wavelet transform, BEMD decomposition, block operation, and Schur decomposition. Then, the R, G, and B components of the copyright logo are scrambled by Arnold scramble and converted into binary watermark information. Finally, a color visual cryptography scheme is proposed to generate two color shared images based on the carrier characteristics and copyright information. One shared image is used to generate a color zero-watermark, and the other is used for copyright authentication phase. Experimental results show that this algorithm has strong robustness and stability in resisting large-scale noise attacks, filtering attacks, JPEG compression, cropping attacks, and translation attacks at different positions. Compared with similar zero-watermarking algorithms, the robust performance is improved by about 10%, and it can adapt to more complex network environments.

Highlights

With the rapid development of information technology, medical images play an important role in the diagnosis process of telemedicine systems
In response to the above problems, Yang et al [23] proposed a zero-watermark algorithm based on fast quaternion generic polar complex exponential transform (FQGPCET), which fused the low-order coefficients of FGPCET moments and QGPCET moments to improve the calculation efficiency of the moments, and the extracted carrier features are more robust
(3) Existing zero-watermarking algorithms Arnold or chaotic mapping is used alone to encrypt copyright information, and their security is lower is paper proposes a color zero-watermarking algorithm for medical images based on bidimensional empirical mode decomposition (BEMD)-Schur decomposition and color visual cryptography

Summary

Introduction

With the rapid development of information technology, medical images play an important role in the diagnosis process of telemedicine systems. In response to the above problems, Yang et al [23] proposed a zero-watermark algorithm based on fast quaternion generic polar complex exponential transform (FQGPCET), which fused the low-order coefficients of FGPCET moments and QGPCET moments to improve the calculation efficiency of the moments, and the extracted carrier features are more robust. (1) Binary image as watermark information in the existing zero-watermarking schemes, and the generated zero-watermark is binary information, which information structure is relatively simple (2) Most of the existing zero-watermarking algorithms can only resist small-scale attacks, and the normalized correlation coefficients obtained for largescale attacks are relatively low, or the extracted copyright information contains more noise points (3) Existing zero-watermarking algorithms Arnold or chaotic mapping is used alone to encrypt copyright information, and their security is lower is paper proposes a color zero-watermarking algorithm for medical images based on BEMD-Schur decomposition and color visual cryptography.

Preliminaries

Color Zero-Watermarking Algorithm

Experimental Results and Analysis

Robustness Analysis