Abstract
To date, the exchange and storage of medical data on electronic format are subject to potential risks. Hence, considerations of security and copyright protection of medical images are necessary and unavoidable. In such a situation, a watermarking scheme is proposed as one of the most promising methods to provide security, reliability, and authenticity of medical information. In this work, we propose a new region based medical image watermarking, which consists of embedding numerical information, called a watermark, into the original image. The main originality of this scheme is the use of the polynomial transform to decompose an image into two parts: the structure and the texture components. This mathematical model is used to extract the most relevant embedding areas, containing less information required for diagnosis. The texture component is selected for embedding the watermark so as to preserve fidelity to the original medical image. Compared with the state-of-the-art schemes, experimental results reveal that the proposed scheme can achieve a good compromise with regard to the invisibility and robustness of the watermark.
Similar content being viewed by others
References
Aherrahrou N, Tairi H (2015) PDE based scheme for multi-modal medical image watermarking. Biomed Eng Online 14. https://doi.org/10.1186/s12938-015-0101-x
Amakdouf H, El Mallahi M, Zouhri A et al (2018) Classification and Recognition of 3D Image of Charlier moments using a Multilayer Perceptron Architecture. Procedia Computer Science 127:226–235. https://doi.org/10.1016/j.procs.2018.01.118
Bennett K, Bennett AJ, Griffiths KM (2010) Security Considerations for E-Mental Health Interventions. J Med Internet Res 12:e61. https://doi.org/10.2196/jmir.1468
Cox IJ (2008) Digital watermarking and steganography, 2nd edn. Morgan Kaufmann Publishers, Boston
Cox IJ, Miller ML, Bloom JA (2000) Watermarking Applications and Their Properties. In: Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC’00). IEEE Computer Society, Washington, DC, pp 6
Da F, Zhang H (2010) Sub-pixel edge detection based on an improved moment. Image Vis Comput 28:1645–1658. https://doi.org/10.1016/j.imavis.2010.05.003
Favorskaya M, Pyataeva A, Popov A (2017) Texture analysis in watermarking paradigms. Procedia Computer Science 112:1460–1469. https://doi.org/10.1016/j.procs.2017.08.019
Flusser J, Suk T (1993) Pattern recognition by affine moment invariants. Pattern Recogn 26:167–174. https://doi.org/10.1016/0031-3203(93)90098-H
Gangadhar Y, Giridhar Akula VS, Reddy PC (2018) An evolutionary programming approach for securing medical images using watermarking scheme in invariant discrete wavelet transformation. Biomedical Signal Processing and Control 43:31–40. https://doi.org/10.1016/j.bspc.2018.02.007
Ghadi M, Laouamer L, Nana L, Pascu A. A Robust Watermarking System Based on Formal Concept Analysis and Texture Analysis. 6
Gomez-Coronel SL, Moya-Albor E, Escalante-Ramírez B, Brieva J (2015) Watermarked cardiac CT image segmentation using deformable models and the Hermite transform. In: Romero E, Lepore N (eds). Cartagena de Indias, Colombia, p 928717
Kekre DHB, Sarode DT, Natu S. Performance Evaluation of Watermarking Technique using Full, Column and Row DCT Wavelet Transform. 3:15
Maalouf A, Larabi M (2009) Low-complexity enhanced lapped transform for image coding in JPEG XR / HD photo. 2009 16th IEEE International Conference on Image Processing (ICIP):5–8
Moubtahij RE, Augereau B, Tairi H, Fernandez-Maloigne C. A spatial image polynomial decomposition with application to video classification. 29
Mousavi SM, Naghsh A, Abu-Bakar SAR (2014) Watermarking Techniques used in Medical Images: a Survey. J Digit Imaging 27:714–729. https://doi.org/10.1007/s10278-014-9700-5
Mousavi SM, Naghsh A, Abu-Bakar SAR (2015) A Heuristic Automatic and Robust ROI Detection Method for Medical Image Warermarking. J Digit Imaging 28:417–427. https://doi.org/10.1007/s10278-015-9770-z
Mukundan R, Ramakrishnan RK (1998) Moment Functions In Image Analysis - Theory And Applications. World Scientific Publishing Company, Singapore
Murali P, Sankaradass V (2018) An efficient ROI based copyright protection scheme for digital images with SVD and orthogonal polynomials transformation. Optik 170:242–264. https://doi.org/10.1016/j.ijleo.2018.04.050
Pan W, Bouslimi D, Karasad M et al (2018) Imperceptible reversible watermarking of radiographic images based on quantum noise masking. Comput Methods Prog Biomed 160:119–128. https://doi.org/10.1016/j.cmpb.2018.03.011
Parah SA, Ahad F, Sheikh JA, Bhat GM (2017) Hiding clinical information in medical images: A new high capacity and reversible data hiding technique. J Biomed Inform 66:214–230. https://doi.org/10.1016/j.jbi.2017.01.006
Parah SA, Ahad F, Sheikh JA et al (2017) A New Reversible and high capacity data hiding technique for E-healthcare applications. Multimed Tools Appl 76:3943–3975. https://doi.org/10.1007/s11042-016-4196-2
Prasad R, Dhavale SV. Scaling and Translation Resistant Tchebichef Moments in Image Watermarking. 7
Sabbane F, Aherrahrou N, Tairi H (2019) A new region based watermarking scheme for medical images. In: Proceedings of the New Challenges in Data Sciences: Acts of the Second Conference of the Moroccan Classification Society on ZZZ - SMC ‘19. ACM Press, Kenitra, pp 1–6
Selvam P, Balachandran S, Pitchai Iyer S, Jayabal R (2017) Hybrid transform based reversible watermarking technique for medical images in telemedicine applications. Optik 145:655–671. https://doi.org/10.1016/j.ijleo.2017.07.060
Shih FY, Zhong X (2016) High-capacity multiple regions of interest watermarking for medical images. Inf Sci 367–368:648–659. https://doi.org/10.1016/j.ins.2016.07.015
Singh A, Dutta MK (2017) Imperceptible watermarking for security of fundus images in tele-ophthalmology applications and computer-aided diagnosis of retina diseases. Int J Med Inform 108:110–124. https://doi.org/10.1016/j.ijmedinf.2017.10.010
Singh A, Kumar B, Singh G, Mohan A (2017) Medical Image Watermarking: techniques and Applications. Springer Science+Business Media, New York
Sun Y, Wen G, Wang J (2015) Weighted spectral features based on local Hu moments for speech emotion recognition. Biomedical Signal Processing and Control 18:80–90. https://doi.org/10.1016/j.bspc.2014.10.008
Thanki R, Borra S, Dwivedi V, Borisagar K (2017) An efficient medical image watermarking scheme based on FDCuT–DCT. Engineering Science and Technology, an International Journal 20:1366–1379. https://doi.org/10.1016/j.jestch.2017.06.001
Turuk M, Dhande A (2018) A Novel Texture-Quantization-Based Reversible Multiple Watermarking Scheme Applied to Health Information System. J Digit Imaging 31:167–177. https://doi.org/10.1007/s10278-017-0024-0
Vellaisamy S, Ramesh V (2014) Inversion attack resilient zero-watermarking scheme for medical image authentication. IET Image Process 8:718–727. https://doi.org/10.1049/iet-ipr.2013.0558
Wu H, Yan S (2016) Computing invariants of Tchebichef moments for shape based image retrieval. Neurocomputing 215:110–117. https://doi.org/10.1016/j.neucom.2015.05.147
Xiao B, Li L, Li Y et al (2017) Image Analysis by Fractional-order Orthogonal Moments. Inf Sci 382:135–149. https://doi.org/10.1016/j.ins.2016.12.011
Zhang H, Wang C, Zhou X (2017) A Robust Image Watermarking Scheme Based on SVD in the Spatial Domain. Future Internet 9. https://doi.org/10.3390/fi9030045
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Sabbane, F., Tairi, H. Medical image watermarking technique based on polynomial decomposition. Multimed Tools Appl 78, 34129–34155 (2019). https://doi.org/10.1007/s11042-019-08134-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-08134-7