TARU PUBLICATIONS
Journal of Information and Optimization Sciences cover

Journal of Information and Optimization Sciences

(Since 1980)
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

Powered by:Powered by

Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
submissions@tarupublications.com
Taru Online First Current IssueSpecial IssuesBrowse all Issues
Journal of Information and Optimization Sciences
Open Access Research Article

A novel reversible digital image watermarking algorithm to protect medical image and patient record authenticity

* , ,

* Corresponding author · click or hover a name for details

pp. 2223–2244Vol. 47Issue 6June 2026DOI: 10.47974/JIOS-2119XML
Received:
01 Mar 2025
Published Online:
11 Jun 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2119
Pages:
2223–2244

Abstract

Due to the growing quantity of medical images, the patient data recognition is the important one for treatment clinical institutions. So, digital image watermarking has widespread importance at the time of sharing of medical images among treatment clinical institutions. But in watermarking the extraction of the patient data and preserving image quality are the major important factors, after sharing of medical images. In this paper, a novel spatial domain-based reversible digital image watermarking scheme proposed on medical images to ensure authenticity, integrity, and confidentiality. In this scheme, the input ground truth image (or cover image) is divided into 4 X 4 block sizes. The watermark image is embedded with the original ground truth image by performing L-level Quantization. The watermark image is quick response (QR) code of patient information. The compression applied to the remainder part of the cover ground truth image using the mean arithmetic method to make the process most robust. The reversible watermarking scheme applied over watermarked images by performing inverse L-level Quantization and decompression. The proposed scheme is compared with Reza et al. existing scheme: “An Image Watermarking Algorithm for Medical Computerized Tomography Images”. The proposed scheme has better experimental results compared to the existing scheme in terms of Peak Signal-to-noise ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index (SSIM). The PSNR, MSE, and SSIM metrics are used to evaluate the robustness of the proposed scheme for extracting cover images and QR code of patient information (in terms of watermark images) from watermarked images. In addition, the Similarity (SIM) and the correlation coefficient (CRC) are used to evaluate how well the suggested approach for patient data and cover ground truth medical image extraction holds up robustness. The experimental numerical values of metrics achieved in the proposed scheme have better performance for compression and decompression watermarking medical images.

Keywords

Medical imageWatermarkingReversible watermarkingSpatial domainScalar quantizationCompressionDecompressionQR code

Subject Classifications

08A7068P3054H30

References

[1] L. Q. Kuang, Y. Zhang, and X. Han, “A Medical Image Authentication System Based on Reversible Digital Watermarking,” in Proceedings of the 1st International Conference on Information Science and Engineering (ICISE), Nanjing, China, pp. 1047–1050 (2009), doi: 10.1109/ICISE.2009.60.
[2] P. K. Sahoo, M. K. Nanda, and M. Jahangeer, “A Modified Framework for Reversible Digital Image Watermarking,” in Proceedings of the International Conference on Advanced Machine Learning (ICAML), Bhubaneswar, India, pp. 228–234 (2019), doi: 10.1109/ICAML48257.2019.00049. 
[3] G. Bhatnagar and W. U. Jonathan, “Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform,” Future Generation Computer Systems, vol. 29, no. 1, pp. 182–195 (2013), doi: 10.1016/j.future.2012.05.021.
[4] W. Pan, G. Coatrieux, N. C. Boulahia, F. Cuppens, and C. Roux, “Medical image integrity control combining digital signature and lossless watermarking,” in Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance, vol. 5959, Lecture Notes in Computer Science (LNCS), Berlin, Germany: Springer, pp. 153–162, (2010), doi: 10.1007/978-3-642-11207-2_12.
[5] J. M. Zain and M. Clarke, “Reversible region of non-interest (RONI) watermarking for authentication of DICOM images,” Intenational Journal of Computer Science and Network Security, vol. 7, no. 9, pp. 19–28 (2011), doi: 10.48550/arXiv.1101.1603.
[6] N. I. Wu and Hwang, “Data hiding current status and key issues,” International journal of Network Security, vol. 4, no. 1, pp. 1–9 (2007).
[7] K. Heylen and T. Dams, “An image watermarking tutorial tool using MATLAB,” in Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, Proc. SPIE 7075, San Diego, CA, USA, Art. no. 70750D (2008), doi: 10.1117/12.793308.
[8] S. P. Mohanty, K. R. Ramakrishnan, and M. Kankanhalli, “A Dual Watermarking Technique for Images,” in Proceedings of the 7th ACM International Conference on Multimedia, Orlando, FL, USA, pp. 49–5 (1999), doi: 10.1145/319878.319891.
[9] P. K. Sahoo, D. Gountia, R. Dash, and J. Mohammed, “A Technical Analysis of Digital Image and Video Processing,” IETE Technical Review, vol. 41, no. 4, pp. 420-430 (2024), doi: 10.1080/02564602.2023.2262418
[10] A. S. Gaikwad, V. D. Gowda, and P. A. Athavale, “Enhancing IoT security through encrypted image processing for intelligent surveillance system,” Journal of information and Optimization Sciences, vol. 46, no. 7, pp. 2363-2374 (2025), doi: 10.47974/JIOS-2133. 
[11] V. S. Jabade and S. R. Gengaje, “Literature review of wavelet based digital image watermarking techniques,” International Journal of Computer Application, vol. 31, no. 1, pp. 28–35 (2011), doi: 10.5120/3838-5334.
[12] N. A. Memon and S. A. M. Gilani, “Watermarking of chest CT scan medical images for content authentication,” International Journal of Computer Mathematics, vol. 88, no. 22, pp. 265– 280 (2010), doi: 10.1080/00207161003596690.
[13] M. Kaur and R. Kaur, “Reversible watermarking of medical images authentication and recovery-a survey,” Journal of Information and Operations Management, vol. 3, no. 1,pp. 241– 244 (2012).
[14] J. M. Zain and M. Clarke, “Reversible region of non-interest (RONI) watermarking for authentication of DICOM images,” Int. J. Comput. Sci. Netw. Secur., vol. 7, no. 9, pp. 19–28 (2007).
[15] O. M. Al-Qershi and B. E. Khoo, “Authentication and data hiding using a hybrid ROI-based watermarking scheme for DICOM images,” Journal of digital imaging, vol. 24, no. 1, pp. 114-125 (2011), doi: 10.1007/s10278-009-9253-1.
[16] R. A. Movahed, M. R. Rezaeian, and S. Ghasemi, “An Image Watermarking Algorithm for Medical Computerized Tomography Images,” in Proceedings of the 5th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), Shahrood, Iran, pp. 1–5 (2019), doi: 10.1109/ICSPIS48872.2019.9066018.
[17] C. W. Honsinger, P. W. Jones, M. Rabbani, and J. C. Stoffel, “Lossless Recovery of an Original Image Containing Embedded Data,” U.S. Patent 6,278,791, (Aug. 2001).
[18] J. Fridrich and M. Goljan, “Practical Steganalysis of Digital Images,” in Security and Watermarking of Multimedia Contents IV, Proc. SPIE 4675, San Jose, CA, USA, pp. 1–13 (2002), doi: 10.1117/12.465263.
[19] T. Kalker and F. M. J. Willems, “Capacity Bounds and Construction for Reversible Data Hiding,” in Proceedings of the 14th International Conference on Digital Signal Processing (DSP 2002), Santorini, Greece, vol. 1, pp. 71–76 (2002), doi: 10.1109/ICDSP.2002.1027818.
[20] B. Perry, B. MacIntosh, and D. Cushman, “Digimarc MediaBridge—The Birth of a Consumer Product, from Concept to Commercial Application,” Proceedings of Electronic Imaging Security and Watermarking of Multimedia, San Jose, California, United States, vol. 4, pp. 118–123 (2002), doi:10.117/12.465267.
[21] M. U. Celik, G. Sharma, A. M. Tekalp, and E. Saber, “Lossless generalized-LSB data embedding,” IEEE Transactions on Image Processing, vol. 14, no. 2, pp. 253-266 (2005), doi: 10.1109/TIP.2004.840686.
[22] J. Tian, “Wavelet-Based Reversible Watermarking for Authentication,” in Security and Watermarking of Multimedia Contents IV, Proc. SPIE 4675, San Jose, CA, USA, pp. 679–690 (2002), doi: 10.1117/12.465329.
[23] A. L. Wakekar, S. Patil, V. K Bhosale, E. Xudaynazarov, N. Tukhtaeva, and S. Karale, “Algebraic geometry approaches to 3D image reconstruction,” Journal of Interdisciplinary Mathematics, vol. 29, no. 3, pp. 709–717 (2026), doi: 10.47974/JIM-2507.
[24] J. Tian, “High Capacity Reversible Data Embedding and Content Authentication,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), Hong Kong, China, vol. 3, pp. III-517–III-520 (2003), doi: 10.1109/ICASSP.2003.1199525.
[25] A. M. Alattar, “Reversible Watermark Using the Difference Expansion of a Generalized Integer Transform,” IEEE Transactions on Image Processing, vol. 13, no. 8, pp. 1147–1156 (2004), doi: 10.1109/TIP.2004.828418.
[26] S. G. Mallat, “Multifrequency Channel Decomposition of Images and Wavelet Models,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, no. 12, pp. 2091–2110 (1989), doi: 10.1109/29.45554.
[27] J. Tian, “Reversible data embedding using a difference expansion,” IEEE Transactions on Circuits and System for Video Technology, vol. 13, no. 8, pp. 890–896 (2003), doi: 10.1109/TCSVT.2003.815962.
[28] A. M. Alattar, “Reversible Watermark Using Difference Expansion of Quads,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’04), Montreal, QC, Canada, pp. 377–380 (2004), doi: 10.1109/ICASSP.2004.1326560.
[29] D.-C. Lou, M.-C. Hu, and J.-L. Liu, “Multiple layer data hiding scheme for medical images,” Computer Standards & Interfaces, vol. 31, no. 2, pp. 329–335 (Feb. 2009), doi: 10.1016/j.csi.2008.05.009.
[30] M. Fallahpour, D. Megías, and M. Ghanbari, “Reversible and High-Capacity Data Hiding in Medical Images,” IET Image Processing, vol. 5, no. 1, pp. 190–197 (2011), doi: 10.1049/iet-ipr.2009.0226.
[31] W.-L. Tai, C.-M. Yeh, and C.-C. Chang, “Reversible Data Hiding Based on Histogram Modification of Pixel Differences,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 6, pp. 906–910 (2009), doi: 10.1109/TCSVT.2009.2017409. 
[32] W. Puech, M. Chaumont, and O. Strauss, “A Reversible Data Hiding Method for Encrypted Images,” in Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, Proc. SPIE 6819, San Jose, CA, USA, 68191E, (2008), doi: 10.1117/12.766754.
[33] M. S. Rani and S. Lakshmanan, “A Novel Method of Data Hiding and Image Compression for Medical Images,” International Journal of Advanced Information Technology, vol. 6, no. 1, pp. 43–51 (Feb. 2016), doi: 10.5121/ijait.2016.6104.
[34] T. Aydogan and C. Bayilmis, “A new efficient block matching data hiding method based on scanning order selection in medical images,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 25, no. 1, pp. 461-473 (2017), doi: 10.3906/elk-1506-189.
[35] J. Wu, R. Chang, C. Chen, C. Wang, T. Kuo, W. N. Moo, and D. Chen, “Tamper detection and recovery for medical images using nearlossless information hiding technique,” Journal of Digital Imaging, vol. 21, no. 1, pp. 59-76 (2007), doi: 10.1007/s10278-007-9011-1.
[36] M. M. Rani and S. Lakshmanan, “An Integrated Method of Data Hiding and Compression of Medical Images,” International Journal of Advanced Information Technology, vol. 6, no. 1, pp. 43-51 (2016), doi: 10.5281/zenodo.5771904.
[37] H. Chao, C. Hsu, and S. Miaou, “A data-hiding technique with authentication, integration, and confidentiality for electronic patient records,” IEEE Transactions on Information Technology in Biomedical, vol. 6, no. 1, pp. 46-53 (2002), doi: 10.1109/4233.992161.
[38] J. Chang, Y. Lu, and H. Wu, “A separable reversible data hiding scheme for encrypted JPEG bitstreams,” signal processing vol. 133, no. 3, pp. 135-14 (2017), doi: 10.1016/j.sigpro.2016.11.003.
[39] W. A. W. Adnam, S. Hitarn, S. A. –Karim, and M. R. TamJis, “A review of image watermarking,” Proceedings Student Conference, Putrajaya, Malaysia, pp. 381–384, doi: 10.1109/SCORED.2003.1459727.
[40] P. K. Sahoo and M. K. Nanda, “A modified partitioning algorithm for classification of e-waste,” Journal of Statistics and Management Systems, vol. 26, no. 1, pp. 53-65 (2023), doi: 10.47974/JSMS-947.
[41] P. K. Sahoo, D. Gountia, R. Dash, S. Behera, and M. K. Nanda, “An Extension Application of 1D Wavelet Denoising Method for Image Denoising,” In: Lanka, S., Sarasa-Cabezuelo, A., Tugui, A. (eds) Trends in Sustainable Computing and Machine Intelligence., ictsm 2023, Algorithms for Intelligent Systems. Springer, Singapore, vol. 1, no. 1, pp. 87-105 (2024), doi: 10.1007/978-981-99-9436-6_7.
[42] P. K. Sahoo, D. Gountia, and R. K. Dash, “Combine Application of Reversible Watermarking Technique and RSA Algorithm to Verify Ownership of Digital Images: A Hybrid Image Restoration Approach,” Journal of Dalian University of Technology, vol. 33, no. 3, pp. 286-302 (2026), doi: 10.5281/zenodo.18999399.
[43] S. Batra, B. Narwal, and A. K. Mohapatra, “ JLSAIoMT : Justifiable lightweight and secure mutual authentication scheme for Internet of Medical Things,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 29, no. 3, pp. 1151–1180 (2026), doi: 10.47974/JDMSC-2189.
[44] A. Noruzi, N. Nazeri, S. J. Baghiabadi, R. Farshid, A. S. A. Mirkabad, and A. Asnafi, “Analysis of scientific productions regarding knowledge management with the open innovation approach,” COLLNET Journal of Scientometrics and Information Management, vol. 19, no. 2, pp. 229–253 (2025), doi: 10.47974/CJSIM-2025-03005.
[45] B. Zouilekh and S. Bouroubi, “Optimizing minimum dominating set using an enhanced binary whale algorithm,” Journal of Information and Optimization Sciences, vol. 47, no. 3, pp. 887–905 (2026), doi: 10.47974/JIOS-1583.

Views: 84Downloads: 80Citations: 0