Optimized Copyright Protection of Scale-Adaptive Saliency-Driven ROI of Medical Records with MSER-Based authentication
Article Information
Abstract
The medical information is always vulnerable to security violations. After the COVID-19 pandemic, the volume of medical information has exponentially increased and the major information is in the form of images. So, the security of this image information is crucial during the transfer using modern information and communication technologies from one place to another. Image watermarking is one of the methods to protect the copyright and integrity of medical records. The medical images consist of some area that has vital information regarding the disease and this area will be considered as the region of interest (ROI). Therefore, the protection of the copyright of this vital area is crucial for the effective diagnosis. The proposed technique utilizes a scale-adaptive anatomical saliency and a statistical information-guided ROI detection technique. The redundant wavelet transform (RDWT) and diagonalized Hessenberg decomposition (Diag-HD), along with the discrete cosine transform (DCT), are used for watermark embedding and extraction procedures. To get the optimized scaling weight, nature-inspired Salp Swarm Optimization (SSO) is used. Maximally stable extremal regions (MSER) are used for feature-based authentication. The simulation results analysis demonstrates the effectiveness in terms of visual similarity and robustness of the proposed technique. The experimental results obtained also highlight the superiority of the proposed technique over other existing methods in terms of imperceptibility and robustness.
Graphical Abstract
Keywords
Data Availability Statement
Funding
Conflicts of Interest
AI Use Statement
Ethical Approval and Consent to Participate
References
- Tiwari, A., Awasthi, D., & Srivastava, V. K. (2025). RFPPFMark: robust and false positive problem free image watermarking scheme with its performance comparison by PSO and MRFO in Schur domain. Signal, Image and Video Processing, 19(3), 199.
[CrossRef] [Google Scholar] - Singh, H. K., Baranwal, N., Singh, K. N., & Singh, A. K. (2024). Using multimodal biometric fusion for watermarking of multiple images. IEEE Transactions on Consumer Electronics, 70(1), 3487-3494.
[CrossRef] [Google Scholar] - Singh, H. K., Singh, K. N., & Singh, A. K. (2025). Split ways: Using GAN watermarking for digital image protection with privacy-preserving split model training. Future Generation Computer Systems, 163, 107523.
[CrossRef] [Google Scholar] - Castelli, M., Manzoni, L., Mariot, L., Nobile, M. S., & Tangherloni, A. (2022). Salp swarm optimization: a critical review. Expert Systems with Applications, 189, 116029.
[CrossRef] [Google Scholar] - Abualigah, L., Shehab, M., Alshinwan, M., & Alabool, H. (2020). Salp swarm algorithm: A comprehensive survey. Neural Computing and Applications, 32(15), 11195-11215.
[CrossRef] [Google Scholar] - Kimmel, R., Zhang, C., Bronstein, A., & Bronstein, M. (2011). Are MSER features really interesting?. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(11), 2316-2320.
[CrossRef] [Google Scholar] - Eswaraiah, R., & Sreenivasa Reddy, E. (2014). Medical image watermarking technique for accurate tamper detection in ROI and exact recovery of ROI. International Journal of Telemedicine and Applications, 2014(1), 984646.
[CrossRef] [Google Scholar] - Ravichandran, D., Praveenkumar, P., Rajagopalan, S., Rayappan, J. B. B., & Amirtharajan, R. (2021). ROI-based medical image watermarking for accurate tamper detection, localisation and recovery. Medical & Biological Engineering & Computing, 59(6), 1355-1372.
[CrossRef] [Google Scholar] - Das, S., & Kundu, M. K. (2013). Effective management of medical information through ROI-lossless fragile image watermarking technique. Computer Methods and Programs in Biomedicine, 111(3), 662-675.
[CrossRef] [Google Scholar] - Eswaraiah, R., & Sreenivasa Reddy, E. (2015). Robust medical image watermarking technique for accurate detection of tampers inside region of interest and recovering original region of interest. IET Image Processing, 9(8), 615-625.
[CrossRef] [Google Scholar] - Keshavarzian, R., & Aghagolzadeh, A. (2016). ROI based robust and secure image watermarking using DWT and Arnold map. AEU-International Journal of Electronics and Communications, 70(3), 278-288.
[CrossRef] [Google Scholar] - Bhalerao, S., Ansari, I. A., & Kumar, A. (2023). A reversible medical image watermarking for ROI tamper detection and recovery. Circuits, Systems, and Signal Processing, 42(11), 6701-6725.
[CrossRef] [Google Scholar] - Awasthi, D., & Srivastava, V. K. (2025). ROI-based optimized image watermarking with real-time authentication. Cluster Computing, 28(7), 463.
[CrossRef] [Google Scholar] - Qasim, A. F., Aspin, R., Meziane, F., & Hogg, P. (2019). ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images. Multimedia Tools and Applications, 78(12), 16433-16463.
[CrossRef] [Google Scholar] - Alshanbari, H. S. (2021). Medical image watermarking for ownership & tamper detection. Multimedia Tools and Applications, 80(11), 16549-16564.
[CrossRef] [Google Scholar] - Awasthi, D., Khare, P., Srivastava, V. K., Singh, A. K., & Gupta, B. B. (2025). DeepNet: Protection of deepfake images with aid of deep learning networks. Image and Vision Computing, 158, 105540.
[CrossRef] [Google Scholar] - Awasthi, D., Khare, P., & Srivastava, V. K. (2025). ANFISmark: ANFIS-based secure watermarking approach for telemedicine applications. Neural Computing and Applications, 37(14), 8677-8698.
[CrossRef] [Google Scholar] - Dwivedi, R., Awasthi, D., & Srivastava, V. K. (2025). WSOMedMark: Robust and optimized dual image watermarking using RDWT and its authentication using BRISK and MSER features for smart healthcare system. Multimedia Tools and Applications, 84(14), 13653-13690.
[CrossRef] [Google Scholar] - Singh, H., Deshmukh, M., & Awasthi, L. K. (2025). Secure healthcare data management using multimodal image fusion and dual watermarking. Scientific Reports, 15(1), 9047.
[CrossRef] [Google Scholar] - Saïd, B. A., Ali, W., Amine, K., Redouane, K. M., & Sahu, A. K. (2025). Robust medical image watermarking based on Ridgelet transform and Ant Colony Optimization for telemedicine security. Systems and Soft Computing, 200390.
[CrossRef] [Google Scholar] - Gupta, A. K., Chakraborty, C., & Gupta, B. (2025). Bio-inspired optimization based secure model for watermarking of medical data. Multimedia Tools and Applications, 1-31.
[CrossRef] [Google Scholar] - Zhang, G. D., Zhang, Z. X., Li, J. Y., Guo, Y., Ding, H., Xi, X. T., ... & Han, Y. C. (2025). Robust Image Watermarking in Wavelet Domain using RDWT-HD-SVD and Whale Optimization Algorithm. Circuits, Systems, and Signal Processing, 44(4), 2681-2705.
[CrossRef] [Google Scholar] - Tiwari, A., & Srivastava, V. K. (2025). MIWHSmark: Multiple Image Watermarking Based on Hybrid Technique in Schur Domain for Smart Healthcare System. Circuits, Systems, and Signal Processing, 1-38.
[CrossRef] [Google Scholar] - Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017). Salp swarm algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software, 114, 163-191.
[CrossRef] [Google Scholar] - Anand, A., & Singh, A. K. (2022). Hybrid nature-inspired optimization and encryption-based watermarking for e-healthcare. IEEE Transactions on Computational Social Systems, 10(4), 2033-2040.
[CrossRef] [Google Scholar] - Anand, A., & Singh, A. K. (2022). Dual watermarking for security of COVID-19 patient record. IEEE Transactions on Dependable and Secure Computing, 20(1), 859-866.
[CrossRef] [Google Scholar] - Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., ... & Tarbox, L. (2013). The Cancer Imaging Archive (TCIA): Maintaining and operating a public information repository. Journal of Digital Imaging, 26(6), 1045-1057.
[CrossRef] [Google Scholar] - Anand, A., Singh, A. K., Lv, Z., & Bhatnagar, G. (2020). Compression-then-encryption-based secure watermarking technique for smart healthcare system. IEEE MultiMedia, 27(4), 133-143.
[CrossRef] [Google Scholar]
Cite This Article
TY - JOUR AU - Awasthi, Divyanshu AU - Srivastava, Vinay Kumar PY - 2026 DA - 2026/02/10 TI - Optimized Copyright Protection of Scale-Adaptive Saliency-Driven ROI of Medical Records with MSER-Based authentication JO - ICCK Transactions on Information Security and Cryptography T2 - ICCK Transactions on Information Security and Cryptography JF - ICCK Transactions on Information Security and Cryptography VL - 2 IS - 1 SP - 43 EP - 54 DO - 10.62762/TISC.2025.898154 UR - https://www.icck.org/article/abs/TISC.2025.898154 KW - region of interest KW - watermarking KW - optimization KW - authentication AB - The medical information is always vulnerable to security violations. After the COVID-19 pandemic, the volume of medical information has exponentially increased and the major information is in the form of images. So, the security of this image information is crucial during the transfer using modern information and communication technologies from one place to another. Image watermarking is one of the methods to protect the copyright and integrity of medical records. The medical images consist of some area that has vital information regarding the disease and this area will be considered as the region of interest (ROI). Therefore, the protection of the copyright of this vital area is crucial for the effective diagnosis. The proposed technique utilizes a scale-adaptive anatomical saliency and a statistical information-guided ROI detection technique. The redundant wavelet transform (RDWT) and diagonalized Hessenberg decomposition (Diag-HD), along with the discrete cosine transform (DCT), are used for watermark embedding and extraction procedures. To get the optimized scaling weight, nature-inspired Salp Swarm Optimization (SSO) is used. Maximally stable extremal regions (MSER) are used for feature-based authentication. The simulation results analysis demonstrates the effectiveness in terms of visual similarity and robustness of the proposed technique. The experimental results obtained also highlight the superiority of the proposed technique over other existing methods in terms of imperceptibility and robustness. SN - 3070-2429 PB - Institute of Central Computation and Knowledge LA - English ER -
@article{Awasthi2026Optimized,
author = {Divyanshu Awasthi and Vinay Kumar Srivastava},
title = {Optimized Copyright Protection of Scale-Adaptive Saliency-Driven ROI of Medical Records with MSER-Based authentication},
journal = {ICCK Transactions on Information Security and Cryptography},
year = {2026},
volume = {2},
number = {1},
pages = {43-54},
doi = {10.62762/TISC.2025.898154},
url = {https://www.icck.org/article/abs/TISC.2025.898154},
abstract = {The medical information is always vulnerable to security violations. After the COVID-19 pandemic, the volume of medical information has exponentially increased and the major information is in the form of images. So, the security of this image information is crucial during the transfer using modern information and communication technologies from one place to another. Image watermarking is one of the methods to protect the copyright and integrity of medical records. The medical images consist of some area that has vital information regarding the disease and this area will be considered as the region of interest (ROI). Therefore, the protection of the copyright of this vital area is crucial for the effective diagnosis. The proposed technique utilizes a scale-adaptive anatomical saliency and a statistical information-guided ROI detection technique. The redundant wavelet transform (RDWT) and diagonalized Hessenberg decomposition (Diag-HD), along with the discrete cosine transform (DCT), are used for watermark embedding and extraction procedures. To get the optimized scaling weight, nature-inspired Salp Swarm Optimization (SSO) is used. Maximally stable extremal regions (MSER) are used for feature-based authentication. The simulation results analysis demonstrates the effectiveness in terms of visual similarity and robustness of the proposed technique. The experimental results obtained also highlight the superiority of the proposed technique over other existing methods in terms of imperceptibility and robustness.},
keywords = {region of interest, watermarking, optimization, authentication},
issn = {3070-2429},
publisher = {Institute of Central Computation and Knowledge}
}
Publisher's Note
ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and Permissions
Portico