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Issue title: Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems
Guest editors: Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri and V. Subramaniyaswamy
Article type: Research Article
Authors: Kamili, Asraa | Fatima, Izata | Hassan, Muzamila | Parah, Shabir A.* | Vijaya Kumar, V.b | Ambati, L. S.c
Affiliations: [a] Department of Electronics and Instrumentation Technology, University of Kashmir, India | [b] School of Computer Engineering, Nobel International University, USA | [c] Department of Business Information Systems, Dakota State University, USA
Correspondence: [*] Corresponding author. Shabir A. Parah, Department of Electronics and Instrumentation Technology, University of Kashmir, India. E-mail: shabireltr@gmail.com.
Abstract: Embedding information in medical images is considered as one of the significant methods for safeguarding the integrity and authenticity of medical images besides providing security to electronic patient records (EPR). The conventional embedding methods deteriorate the perceptual quality of medical images making them unsuitable for proper diagnosis. To preserve the perceptual quality of medical images reversible embedding is used. The reversible embedding schemes, however, have less embedding capacity. In this work, a reversible scheme based on histogram bin shifting and RGB plane concatenation has been proposed which offers high embedding capacity as well. We have exploited the fact that medical images, unlike general images, consist of a large number of peaks and zero points that can be employed for reversibly embedding the data. Reversibility ensures that original image restoration takes place after the extraction of embedded data, which is of great importance in medical images for proper diagnosis and treatment. We have used various subjective and objective image quality metrics for analyzing the scheme. The proposed scheme has been shown to provide a Peak Signal to Noise Ratio (PSNR) value of above 56 dB for an embedding capacity of 0.58 bits per pixel (bpp). The results obtained show that the performance of scheme presented is far better in comparison to the state-of-the-art.
Keywords: Medical images, security, authentication, reversibility, electronic patient record
DOI: 10.3233/JIFS-189157
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8389-8398, 2020
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