Information hiding in medical images: a robust medical image watermarking system for E-healthcare

• Published in: Multimedia tools and applications Vol. 76; no. 8; pp. 10599 - 10633
• Main Authors: Parah, Shabir A., Sheikh, Javaid A., Ahad, Farhana, Loan, Nazir A., Bhat, G. M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2017; Springer Nature B.V
• Subjects: Algorithms; Computer Communication Networks; Computer Science; Cybersecurity; Data Structures and Information Theory; Digital imaging; Digital watermarking; Digital watermarks; Discrete cosine transform; Embedding; Health care; Image transmission; Medical electronics; Medical imaging; Multimedia Information Systems; Special Purpose and Application-Based Systems; Robustness; Region of interest; Region of non interest; Discrete cosine transform
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-015-3127-y

Electronic transmission of the medical images is one of the primary requirements in a typical Electronic-Healthcare (E-Healthcare) system. However this transmission could be liable to hackers who may modify the whole medical image or only a part of it during transit. To guarantee the integrity of a medical image, digital watermarking is being used. This paper presents two different watermarking algorithms for medical images in transform domain. In first technique, a digital watermark and Electronic Patients Record (EPR) have been embedded in both regions; Region of Interest (ROI) and Region of Non-Interest (RONI). In second technique, Region of Interest (ROI) is kept untouched for tele-diagnosis purpose and Region of Non-Interest (RONI) is used to hide the digital watermark and EPR. In either algorithm 8 × 8 block based Discrete Cosine Transform (DCT) has been used. In each 8 × 8 block two DCT coefficients are selected and their magnitudes are compared for embedding the watermark/EPR. The selected coefficients are modified by using a threshold for embedding bit a ‘0’ or bit ‘1’ of the watermark/EPR. The proposed techniques have been found robust not only to singular attacks but also to hybrid attacks. Comparison results viz-a - viz payload and robustness show that the proposed techniques perform better than some existing state of art techniques. As such the proposed algorithms could be useful for e-healthcare systems.