Robust and Imperceptible Watermarking on Medical Images using Coefficient Pair Modification

Ledya Novamizanti; Andriyan Bayu Suksmono; Donny Danudirdjo; Gelar Budiman

doi:10.31436/iiumej.v24i1.2597

Authors

Ledya Novamizanti Telkom University https://orcid.org/0000-0001-6060-8243
Andriyan Bayu Suksmono Institut Teknologi Bandung https://orcid.org/0000-0002-4785-4156
Donny Danudirdjo Institut Teknologi Bandung
Gelar Budiman Institut Teknologi Bandung https://orcid.org/0000-0002-2948-4219

DOI:

https://doi.org/10.31436/iiumej.v24i1.2597

Keywords:

medical image, robust, watermarking, DCT, imperceptible

Abstract

Sensitive data including medical images and electronic patient records (EPR) have potential value in the era of big data and telemedicine applications. Distribution of medical images and EPR over public networks requires a high level of privacy and security. Robust and imperceptible watermarking techniques are needed to provide copyright preservation for medical images and protect patient information security. This paper improves the technique of Coltuc et al. by modifying the discrete cosine transform (DCT) coefficient pairs in the watermark embedding formula. Our proposed formula ensures that the difference between the two coefficients is at least ????. If the difference between the two coefficients is less than ????, then the new pixels are modified so that the difference is equal to ????. The proposed method was evaluated on a variety of medical images, including X-ray, CT, US, MRI, and Colonoscopy, and compared to numerous robust watermarking techniques of the recent time. The experimental results demonstrate that the suggested method outperforms contemporary robust watermarking techniques in terms of imperceptibility, robustness, and security. The peak signal noise ratio (PSNR) for all modalities of watermarked medical images exceeds 54 dB, and the average PSNR is approximately 56 dB. The proposed method is outstanding compared to Coltuc's method due to a 93% and 14% increase in bit error rate (BER) and normalized correlation (NC), respectively. Our work is superior to various state-of-the-art robust watermarking techniques, allowing it to be employed effectively in medical applications.

ABSTRAK: Data sensitif termasuk imej perubatan dan rekod pesakit elektronik (EPR) mempunyai potensi nilai dalam era aplikasi data besar dan teleperubatan. Pengedaran imej perubatan dan EPR melalui rangkaian awam memerlukan tahap privasi dan keselamatan yang tinggi. Teknik penanda air yang mantap dan tidak dapat dilihat diperlukan untuk menyediakan pemeliharaan hak cipta untuk imej perubatan dan melindungi keselamatan maklumat pesakit. Kertas kerja ini menambah baik teknik Coltuc et al. dengan mengubah suai pasangan pekali transformasi kosinus diskret (DCT) dalam formula pembenaman tera air. Formula yang dicadangkan kami memastikan bahawa perbezaan antara dua pekali adalah sekurang-kurangnya ????. Jika perbezaan antara dua pekali kurang daripada ????, maka piksel baharu diubah suai supaya perbezaannya sama dengan ????. Kaedah yang dicadangkan telah dinilai pada pelbagai imej perubatan, termasuk X-ray, CT, US, MRI, dan Kolonoskopi, dan dibandingkan dengan banyak teknik penanda air yang mantap pada masa terkini. Keputusan eksperimen menunjukkan bahawa kaedah yang dicadangkan mengatasi teknik penanda air teguh kontemporari dari segi ketidakjelasan, keteguhan dan keselamatan. Nilai PSNR untuk semua modalitas imej perubatan bertanda air melebihi 54 dB, dan nilai purata PSNR adalah lebih kurang 56 dB. Kaedah yang dicadangkan adalah cemerlang daripada kaedah Coltuc kerana masing-masing peningkatan 93% dan 14% dalam BER dan NC. Kerja kami lebih unggul daripada pelbagai teknik penanda air teguh terkini, membolehkan ia digunakan dengan berkesan dalam aplikasi perubatan.

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References

Memon, NA. Alzahrani A. (2020) Prediction-based reversible watermarking of CT scan images for content authentication and copyright protection. IEEE Access, 8: 75448-75462.

doi: 10.1109/ACCESS.2020.2989175. DOI: https://doi.org/10.1109/ACCESS.2020.2989175

Sajedi H, Rahbar S. (2020) Information hiding methods for E –Healthcare. Smart Health, 15: 100104. doi: 10.1016/j.smhl.2019.100104. DOI: https://doi.org/10.1016/j.smhl.2019.100104

Ahmad GI, Singla J, Giri KJ. (2021). Security and Privacy of E-health Data. In Multimedia Security, Springer Singapore, pp. 199-214. DOI: https://doi.org/10.1007/978-981-15-8711-5_10

Lanxiang C, Wutong BAI, Zhiqiang YAO. (2020) A Secure and Privacy-Preserving Watermark Based Medical Image Sharing Method. Chinese J. Electron., 29(5): 819-825.

doi: 10.1049/cje.2020.07.003. DOI: https://doi.org/10.1049/cje.2020.07.003

Magdy M, Hosny KM. (2022) Security of medical images for telemedicine?: a systematic review. Multimed. Tools Appl., 81: 25101-25145. doi: 10.1007/s11042-022-11956-7 DOI: https://doi.org/10.1007/s11042-022-11956-7

Alzahrani A, Memon NA. (2021) Blind and Robust Watermarking Scheme in Hybrid Domain for Copyright Protection of Medical Images. IEEE Access, 9: 113714-113734.

doi: 10.1109/ACCESS.2021.3104985. DOI: https://doi.org/10.1109/ACCESS.2021.3104985

Thakur S, Singh AK, Ghrera SP, Mohan A. (2020) Chaotic based secure watermarking approach for medical images. Multimed. Tools Appl., 79: 4263-4276. doi: 10.1007/s11042-018-6691-0 DOI: https://doi.org/10.1007/s11042-018-6691-0

Hassan B, Ahmed R, Li BO, Hassan O. (2019) An Imperceptible Medical Image Watermarking Framework for Automated Diagnosis of Retinal Pathologies in an eHealth Arrangement. IEEE Access, 7: 69758-69775. doi: 10.1109/ACCESS.2019.2919381. DOI: https://doi.org/10.1109/ACCESS.2019.2919381

Anand A, Singh AK. (2021) Watermarking techniques for medical data authentication?: a survey. Multimed. Tools Appl., 80: 30165-30197. doi: 10.1007/s11042-020-08801-0 DOI: https://doi.org/10.1007/s11042-020-08801-0

Evsutin O, Dzhanashia K. (2022) Watermarking schemes for digital images?: Robustness overview. Signal Process. Image Commun., 100: 116523. doi: 10.1016/j.image.2021.116523. DOI: https://doi.org/10.1016/j.image.2021.116523

Saini D, Ali M. (2020) A robust medical image watermarking framework based on SVD and DE In Integer DCT domain (Workshop Paper), pp. 373-378.

doi: 10.1109/BigMM50055.2020.00064. DOI: https://doi.org/10.1109/BigMM50055.2020.00064

Coltuc D, Chassery JM. (2007) Distortion-free robust watermarking: a case study. Secur. Steganography, Watermarking Multimed. Contents IX, 6505: 65051N, doi: 10.1117/12.702445. DOI: https://doi.org/10.1117/12.702445

Coltuc D. (2007) Towards distortion-free robust image authentication. J. Phys. Conf. Ser., 77: 012005. doi: 10.1088/1742-6596/77/1/012005. DOI: https://doi.org/10.1088/1742-6596/77/1/012005

Thanki R, Borra S, Dwivedi V, Borisagar K. (2017) An efficient medical image watermarking scheme based on FDCuT–DCT. Eng. Sci. Technol. an Int. J., 20(4): 1366-1379.

doi: 10.1016/j.jestch.2017.06.001. DOI: https://doi.org/10.1016/j.jestch.2017.06.001

Novamizanti L, Wahidah I, Wardana NPDP. (2020) A Robust Medical Images Watermarking Using FDCuT-DCT-SVD. Int. J. Intell. Eng. Syst., 13(6): 266-278.

doi: 10.22266/ijies2020.1231.24 DOI: https://doi.org/10.22266/ijies2020.1231.24

Lei M, Liu X, Wang M, Yang Y, Qu Z. (2018) Robust image watermarking based on quantization index modulation in the DCT domain. J. Internet Technol., 19(2): 507-514.

doi: 10.3966/160792642018031902019.

Zhu Z, Zheng N, Qiao T, Xu M. (2019) Robust steganography by modifying sign of DCT coefficients. IEEE Access, 7: 168613-168628. doi: 10.1109/ACCESS.2019.2953504. DOI: https://doi.org/10.1109/ACCESS.2019.2953504

Rachmawanto EH, Setiadi DRIM, Sari CA, Rijati N. (2019) Imperceptible and secure image watermarking using DCT and random spread technique. Telkomnika (Telecommunication Comput. Electron. Control., 17(4): 1750-1757. doi: 10.12928/TELKOMNIKA.v17i4.9227. DOI: https://doi.org/10.12928/telkomnika.v17i4.9227

Byun SW, Son HS, Lee SP. (2019) Fast and Robust Watermarking Method Based on DCT Specific Location. IEEE Access, 7: 100706-100718. doi: 10.1109/ACCESS.2019.2931039. DOI: https://doi.org/10.1109/ACCESS.2019.2931039

Ko HJ, Huang CT, Horng G, WANG SJ. (2020) Robust and blind image watermarking in DCT domain using inter-block coefficient correlation. Inf. Sci. (NY)., 517: 128-147.

doi: 10.1016/j.ins.2019.11.005. DOI: https://doi.org/10.1016/j.ins.2019.11.005

Nawaz SA, Li J, Bhatti UA, Mehmood A, Shoukat MU, Bhatti MA (2020) Advance hybrid medical watermarking algorithm using speeded up robust features and discrete cosine transform. PLoS One, 15(6): 1-21. doi: 10.1371/journal.pone.0232902. DOI: https://doi.org/10.1371/journal.pone.0232902

Kumar S, Jha RK. (2019) FD-based detector for medical image watermarking. IET Image Processing, 13(10): 1773-1782 2019. doi: 10.1049/iet-ipr.2018.5485. DOI: https://doi.org/10.1049/iet-ipr.2018.5485

Fares K, Khaldi A, Redouane K, Salah E. (2021) DCT & DWT based watermarking scheme for medical information security. Biomed. Signal Process. Control, 66: 102403.

doi: 10.1016/j.bspc.2020.102403. DOI: https://doi.org/10.1016/j.bspc.2020.102403

Khayam SA. (2003) The Discrete Cosine Transform (DCT): Theory and Application. In Information Theory and Coding, Michigan State University, pp. 1-13.

Hamidi M, Haziti ME, Cherifi H, Hassouni ME. (2018) Hybrid blind robust image watermarking technique based on DFT-DCT and Arnold transform. Multimed. Tools Appl., 77(20): 27181-27214. doi: 10.1007/s11042-018-5913-9. DOI: https://doi.org/10.1007/s11042-018-5913-9

Hernandez JR, Amado M, Perez-Gonzalez F. (2000) DCT-domain watermarking techniques for still images: detector performance analysis and a new structure. IEEE Trans. Image Process.,9(1): 55-68. doi: 10.1109/83.817598. DOI: https://doi.org/10.1109/83.817598

Wang X, Li X, Pei Q. (2020) Independent Embedding Domain Based Two-Stage Robust Reversible Watermarking. IEEE Trans. Circuits Syst. Video Technol., 30(8): 2406-2417.

doi: 10.1109/TCSVT.2019.2915116. DOI: https://doi.org/10.1109/TCSVT.2019.2915116

Rahim T, Novamizanti L, Ramatryana INA, Shin SY. (2021) Compressed medical imaging based on average sparsity model and reweighted analysis of multiple basis pursuit. Comput. Med. Imaging Graph., 90: 101927. doi: 10.1016/j.compmedimag.2021.101927. DOI: https://doi.org/10.1016/j.compmedimag.2021.101927

Guo Y, Li BZ., Goel N (2017) Optimised blind image watermarking method based on firefly algorithm in DWT-QR transform domain. IET Image Process, 11(6): 406-415.

doi: 10.1049/iet-ipr.2016.0515 DOI: https://doi.org/10.1049/iet-ipr.2016.0515

Budiman G, Suksmono AB, Danudirdjo D. (2020) Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding. Appl. Sci., 10(12): 1-21. doi: 10.3390/app10124338. DOI: https://doi.org/10.3390/app10124338

Novamizanti L, Suksmono AB, Danudirdjo D, Budiman G. (2022) Robust Reversible Watermarking using Stationary Wavelet Transform and Multibit Spread Spectrum in Medical Images. Int. J. Intell. Eng. Syst., 15(3): 343-354. doi: 10.22266/ijies2022.0630.29.