Medical Image Authentication Method Based on the Wavelet Packet and Energy Entropy

Entropy (Basel). 2022 Jun 8;24(6):798. doi: 10.3390/e24060798.

Abstract

The transmission of digital medical information is affected by data compression, noise, scaling, labeling, and other factors. At the same time, medical data may be illegally copied and maliciously tampered with without authorization. Therefore, the copyright protection and integrity authentication of medical information are worthy of attention. In this paper, based on the wavelet packet and energy entropy, a new method of medical image authentication is designed. The proposed method uses the sliding window to measure the energy of the detail information. In the time-frequency data distribution, the local details of the data are mined. The complexity of energy is quantitatively described to highlight the valuable information. Based on the energy weight, the local energy entropy is constructed and normalized. The adjusted entropy value is used as the feature vector of the authentication information. A series of experiments show that the authentication method has good robustness against shearing attacks, median filtering, contrast enhancement, brightness enhancement, salt-and-pepper noise, Gaussian noise, multiplicative noise, image rotation, scaling attacks, sharpening, JPEG compression, and other attacks.

Keywords: authentication; energy entropy; robustness; wavelet packet decomposition.

Grants and funding

This research was funded by the National Natural Science Foundation of China (no.: 61672124), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (no.: MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (no.: XLYC1802013), Key R&D Projects of Liaoning Province (no.: 2019020105-JH2/103), the Youth Foundation of Xuzhou Institute of Technology (No:XKY2017223), Xuzhou Science and Technology Plan Project (KC19197, KC17078, KC18011), Major Project of Natural Science Research of the Jiangsu Higher Education Institutions of China (18KJA520012), and Qinglan Project of Jiangsu Province under grant 2018.