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Journal of Healthcare Engineering
Volume 2017 (2017), Article ID 3538979, 7 pages
Research Article

Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

1UMIT, SNDT University, Mumbai, Maharashtra, India
2AGV Systems Pvt. Ltd. India, Mumbai, Maharashtra, India
3D.J. Sanghvi Engineering College, Mumbai, Maharashtra, India

Correspondence should be addressed to Vishakha Kelkar

Received 17 February 2017; Revised 16 June 2017; Accepted 20 August 2017; Published 26 September 2017

Academic Editor: Syoji Kobashi

Copyright © 2017 Vishakha Kelkar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient’s information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB) obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image.