Title: A novel convolution kernel-based robust watermarking scheme applied in medical image

Authors: Junhua Zheng; Jingbing Li; Jing Liu; Mengxing Huang; Yen-Wei Chen; Uzair Aslam Bhatti

Addresses: School of Information and Communication Engineering, Hainan University, Haikou, Hainan, China ' School of Information and Communication Engineering, Hainan University, Haikou, Hainan, China ' Research Center for Healthcare Data Science, Zhejiang Lab, Zhejiang Province, Hangzhou, China ' State Key Laboratory of Marine Resource Utilisation in the South China Sea, Hainan University, Haikou, Hainan, China ' Graduate School of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan ' School of Information and Communication Engineering, Hainan University, Haikou, Hainan, China

Abstract: When the existing digital watermarking algorithm is applied to the medical image, the watermark embedded in the Region of Interest (ROI) will change the properties of the original medical image, causing misdiagnosis. To solve these problems, a robust watermarking method for medical images based on feature extraction of convolution kernels is proposed in this paper. First, the embedded watermark is encrypted by logistic mapping to improve the security of the transmission of patients' personal information on the internet. Then, the convolution kernels are used to perform feature extraction on the original medical image to increase the algorithm's ability to resist geometric attacks. Finally, the zero-watermarking technology is used to organically combine the watermark and the medical image to prevent the region of interest of the medical image from being damaged by the watermark. Experimental results show that the algorithm has good performance on security and robustness.

Keywords: digital watermark; medical image; convolution kernel; zero watermarking; feature extraction.

DOI: 10.1504/IJWMC.2022.124820

International Journal of Wireless and Mobile Computing, 2022 Vol.22 No.3/4, pp.290 - 299

Received: 01 Oct 2021
Accepted: 17 Mar 2022

Published online: 09 Aug 2022 *

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