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A Novel Texture-Quantization-Based Reversible Multiple Watermarking Scheme Applied to Health Information System

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Abstract

The recent innovations in information and communication technologies have appreciably changed the panorama of health information system (HIS). These advances provide new means to process, handle, and share medical images and also augment the medical image security issues in terms of confidentiality, reliability, and integrity. Digital watermarking has emerged as new era that offers acceptable solutions to the security issues in HIS. Texture is a significant feature to detect the embedding sites in an image, which further leads to substantial improvement in the robustness. However, considering the perspective of digital watermarking, this feature has received meager attention in the reported literature. This paper exploits the texture property of an image and presents a novel hybrid texture-quantization-based approach for reversible multiple watermarking. The watermarked image quality has been accessed by peak signal to noise ratio (PSNR), structural similarity measure (SSIM), and universal image quality index (UIQI), and the obtained results are superior to the state-of-the-art methods. The algorithm has been evaluated on a variety of medical imaging modalities (CT, MRA, MRI, US) and robustness has been verified, considering various image processing attacks including JPEG compression. The proposed scheme offers additional security using repetitive embedding of BCH encoded watermarks and ADM encrypted ECG signal. Experimental results achieved a maximum of 22,616 bits hiding capacity with PSNR of 53.64 dB.

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Authors and Affiliations

  1. Pune Institute of Computer Technology, Sr. No 27, Pune-Satara Road, Behind Bharati Vidyapeeth, Dhankawadi, Pune, Maharashtra, 411043, India

    Mousami Turuk & Ashwin Dhande

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  1. Mousami Turuk
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  2. Ashwin Dhande
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Correspondence to Mousami Turuk.

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Turuk, M., Dhande, A. A Novel Texture-Quantization-Based Reversible Multiple Watermarking Scheme Applied to Health Information System. J Digit Imaging 31, 167–177 (2018). https://doi.org/10.1007/s10278-017-0024-0

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