A Robust Watermarking Scheme Based on ROI and IWT for Remote Consultation of COVID-19

Abstract

In the current dire situation of the corona virus COVID-19, remote consultations were proposed to avoid cross-infection and regional differences in medical resources. However, the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry. To ensure the integrity and security of medical images, this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest (ROI) and integer wavelet transform (IWT). First, the medical image is divided into two different parts, regions of interest and non-interest regions. Then the integrity of ROI is verified using the hash algorithm, and the recovery data of the ROI region is calculated at the same time. Also, binary images with the basic information of patients are processed by logistic chaotic map encryption, and then the synthetic watermark is embedded in the medical carrier image using IWT transform. The performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the lungs. Experimental results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image reliability. The maximum peak signal to noise ratio (PSNR) value of 51.24 has been achieved, which proves that the watermark is invisible and has strong robustness against noise, compression, and filtering attacks.

Tong Xu

Master student of Computer Science

My research interests include distributed robotics, mobile computing and programmable matter.