@Article{cmes.2022.020255,
AUTHOR = {Saima Kanwal, Feng Tao, Ahmad Almogren, Ateeq Ur Rehman, Rizwan Taj, Ayman Radwan},
TITLE = {A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {134},
YEAR = {2023},
NUMBER = {1},
PAGES = {201--219},
URL = {http://www.techscience.com/CMES/v134n1/49435},
ISSN = {1526-1506},
ABSTRACT = {The authenticity and integrity of healthcare is the primary objective. Numerous reversible watermarking schemes
have been developed to improve the primary objective but increasing the quantity of embedding data leads to
covering image distortion and visual quality resulting in data security detection. A trade-off between robustness,
imperceptibility, and embedded capacity is difficult to achieve with current algorithms due to limitations in their
ability. Keeping this purpose insight, an improved reversibility watermarking methodology is proposed to maximize
data embedding capacity and imperceptibility while maintaining data security as a primary concern. A key is
generated by a random path with minimum bit flipping is selected in the 4 × 4 block to gain access to the data
embedding patterns. The random path’s complex structure ensures data security. Data of various sizes (8 KB,
16 KB, 32 KB) are used to analyze image imperceptibility and evaluate quality factors. The proposed reversible
watermarking methodology performance is tested under standard structures PSNR, SSIM, and MSE. The results
revealed that the MRI watermarked images are imperceptible, like the cover image when LSB is 3 bits plane. Our
proposed reversible watermarking methodology outperforms other related techniques in terms of average PSNR
(49.29). Experiment results show that the suggested reversible watermarking method improves data embedding
capacity and imperceptibility compared to existing state-of-the-art approaches.},
DOI = {10.32604/cmes.2022.020255}
}