Medical Image Watermark and Tamper Detection Using Constant Correlation Spread Spectrum Watermarking

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant correlation, medical image, spread spectrum, tamper detection, watermarking.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1316540

References:

[1] J. H. K Wu et al. “Tamper Detection and Recovery for Medical Images Using Near-lossless Information Hiding Technique” Journal of Digital Imaging, vol. 21, No. 1, March, 2008: pp 59-76.
[2] G. Ulutas et al. “Medical Image Tamper Detection Based on Passive Image Authentication” Journal of Digital Imaging, Springer, DOI: 10.1007/s10278-017-9961-x, May 08, 2017.
[3] Guo and T.G Zhuang. “A lossless watermarking scheme for enhancing security of Medical data in PACS” In Proceedings of SPIE Medical Imaging. SPIE 2003. Pp 350 – 359
[4] V. Dhore and P. M Arfat. “Secure Spread Spectrum Data Embedding and Extraction” International Journal of Science and Research, ISSN:2319-7064. vol 4, no.1, pp 743-747, 2015.
[5] C. Saini et al. “Digital Image Forgery Detection using Correlation Coefficients” International Journal of Computer Applications (0975-8887), vol.129, no. 14, pp 17-23, Nov, 2015.
[6] T. T Nguyen and H. D Tuan. “A Modified Spatial Spread Spectrum Method for Digital Image Watermarking” In IEEE 2nd International Conference Communication and Electronics, ICCE, Hoi an Vitenam, pp. 282-287, 4-6 June, 2008.
[7] P. Singh and S.S Goel. “Correlation-based Image Tampering Detection” In International Journal of Computer Science and Information Technologies, vol. 7, no. 2, pp 990-995, 2016.
[8] Y. Gan and J. Zhong. “Image copy-move Tamper blind detection algorithm based on integrated feature vectors” Journal of Chemical and Pharmaceutical Research, vol 6, no. 6, pp 1580-1589, 2014.
[9] A. Kashyap et al. “An Evaluation of Digital Image Forgery Detection Approaches” In Press: https://arxiv.org/abs/1703.09968, 30th March 2017.
[10] Wakatani, A., “Digital watermarking for ROI medical images by using compressed signature image” In Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS) , pp. 2043–2048, 7-10 Jan.2002.
[11] R. V Hogg and A. T Craig. Introduction to Mathematical Statistics (4th ed.). Macmillian Publishing Company, Newyork, USA, 1978.
[12] Q. Huynh-Thu and M. Ghanbari, “Scope of validity of PSNR in image/video quality assessment” Electronics letters, vol. 44, no. 13, pp.800–801, 2008.
[13] Z. Wang, A.C. Bovik, H.R. Sheikh, and E. P. Simoncelli. “Image Quality Assessment: From Error Visibility to Structural Similarity” In IEEE Transactions On Image Processing, vol. 13, no. 4, pp 1-14, April, 2004.
[14] M. Fakhredanesh, R. Safabakhsh and M. Rahmati. “A Model-Based Image Steganography Method Using Watson’s Visual Model” ETRI Journal, vol.36, no.3 pp. 479 – 489, June 2014.
[15] X. Zhang, Z.J Wang and X. Wang. “Correlation-and-bit-aware additive spread spectrum data hiding for Laplacian distributed host image signal” In Signal Processing: Image Communication vol. 29, pp. 1171 – 1180, 2014.
[16] R. Eswaraiah and E. S Reddy. “Robust medical image watermarking technique for accurate detection of tampers inside region of interest and recovering original region of interest” In IET image Process, vol. 9, no. 8, pp. 615 – 625, Doi:10.1049/iet-ipr.2014.0986, 2015.
[17] F. Rahimi and H. Rabbani. “A dual adaptive watermarking scheme in contourlet domain for DICOM images” In Biomedical Engineering, Doi: 10.1186/1475-925X-10-53, vol. 10, no.53, 2011.
[18] H. K Maity and S.P Maity. “Joint Robust and Reversible Watermarking for Medical Images” In 2nd International Conference on Communication, Computing and Security, Procdia Technology vol.6, pp 275 – 282, 2012.
[19] B. Kumar, H. V. Singh, S. P Singh and A. Mohan, “Secure Spread-Spectrum Watermarking for Telemedicine Applications” Journal of Information Security Vol 2, pp. 91-98, 2011.