Open Access

ARTICLE

Zero Watermarking Algorithm for Medical Image Based on Resnet50-DCT

by Mingshuai Sheng¹, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2,3, Jing Liu⁴, Mengxing Huang^1,5, Yen-Wei Chen⁶

1 School of Information and Communication Engineering, Hainan University, Haikou, 570228, China
2 State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, Haikou, 570228, China
3 School of Computer Science and Technology, Hainan University, Haikou, 570228, China
4 Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, 311121, China
5 State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, Haikou, 570228, China
6 Graduate School of Information Science and Engineering, Ritsumeikan University, Kyoto, 5258577, Japan

* Corresponding Author: Jingbing Li. Email:

Computers, Materials & Continua 2023, 75(1), 293-309. https://doi.org/10.32604/cmc.2023.036438

Received 30 September 2022; Accepted 15 November 2022; Issue published 06 February 2023

Abstract

Medical images are used as a diagnostic tool, so protecting their confidentiality has long been a topic of study. From this, we propose a Resnet50-DCT-based zero watermarking algorithm for use with medical images. To begin, we use Resnet50, a pre-training network, to draw out the deep features of medical images. Then the deep features are transformed by DCT transform and the perceptual hash function is used to generate the feature vector. The original watermark is chaotic scrambled to get the encrypted watermark, and the watermark information is embedded into the original medical image by XOR operation, and the logical key vector is obtained and saved at the same time. Similarly, the same feature extraction method is used to extract the deep features of the medical image to be tested and generate the feature vector. Later, the XOR operation is carried out between the feature vector and the logical key vector, and the encrypted watermark is extracted and decrypted to get the restored watermark; the normalized correlation coefficient (NC) of the original watermark and the restored watermark is calculated to determine the ownership and watermark information of the medical image to be tested. After calculation, most of the NC values are greater than 0.50. The experimental results demonstrate the algorithm’s robustness, invisibility, and security, as well as its ability to accurately extract watermark information. The algorithm also shows good resistance to conventional attacks and geometric attacks.

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Keywords

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