A secure framework for remote diagnosis in health care: A high capacity reversible data hiding technique for medical images. (January 2021)

• Record Type: Journal Article
• Authors: Govind, P.V. Sabeen; Judy, M.V.
• Is Part Of: Computers & electrical engineering. Volume 89(2021)
• Publication Date: 2021-01
• Subjects: Steganalysis -- Remote diagnosis -- Medical image -- Interpolation -- Modular arithmetic -- Visual quality; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106933
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A high capacity data hiding algorithm which is reversible in nature. Utilization of the original pixels along with the interpolated pixels boosts the payload capacity. A novel weighted image interpolation technique that enhances visual quality of the stego image. Abstract: The health care industry involves the processing of large-scale images for various applications. Remote diagnosis is one such significant area where medical images are sent across vulnerable communication media. Hence, a secure and robust framework is necessary to hide and retrieve patient information in medical images. Here, we propose a high capacity reversible data hiding technique that can be used to embed patient data using a new weighted interpolation technique. In this approach, to improve the payload capacity, interpolated pixels are effectively utilized for the data embedding process using modular arithmetic. The original cover pixels are also employed to embed data using the difference expansion method. The framework developed is tested with standard benchmark images and medical images. The experimental results prove that the proposed method proffers a better output in comparison with the other contemporary methods in this domain. Graphical abstract: Image, graphical abstract