Zero Watermarking Algorithm for Medical Image Based on Resnet50-DCT

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.