Multimedia Tools and Applications

, Volume 77, Issue 8, pp 10273–10284 | Cite as

Tamper detection of medical images using statistical moments against various attacks

  • T. Vijayanandh
  • A. Shenbagavalli


Medical Imaging has evolved to digital means to make it suitable for transmission and storage purposes. This aids in transfer of medical images for medical transcriptions, tele-medicine and Content Based Image Retrieval (CBIR) applications. Medical images need to be transported with enough security to preserve the contents from intruders, to verify the contents of Hospital Information system for legal purposes and to protect the images from disclosure to unauthorized persons. Data authentication using watermarking preserves the content against modification and also can be used for ready reference anytime. In this work, zernike and Hu moments were used for generation of Hash for the original and distorted images. Hash generated is compared with the Hausdorff distance. It was found that the variance of Hu moments is higher than that of zernike moments and hence the use of Hu moments enhances the security of medical images used for transmission and storage purposes.


Authentication Hu moments Zernike moments Image distortion Hausdorff distance 


  1. 1.
    Al-Haj A et al (2015) Crypto-based algorithms for secured medical image transmission. IET Inf Secur 9(6):365–373CrossRefGoogle Scholar
  2. 2.
    Aznaveh AM, Torkamani-Azar F, Mansouri A, Kurugollu F (2010) Reversible watermarking using statistical information. EURASIP J Adv Signal Processing 2010(1):738972Google Scholar
  3. 3.
    Begum AHR et al (2016) Evolutionary optimized discrete Tchebichef moments for image compression applications. Turk J Electr Eng Comput Sci 24:3321–3334CrossRefGoogle Scholar
  4. 4.
    Cao X et al (2016) High capacity reversible data hiding in encrypted images by patch-level sparse representation. IEEE Trans Cybern 46(5):1132–1143CrossRefGoogle Scholar
  5. 5.
    Chen H et al (2017) High-fidelity reversible data hiding using directionally-enclosed prediction. IEEE Trans Signal Proc Lett 24(5):574–578CrossRefGoogle Scholar
  6. 6.
    Honarvar B, Paramesran R, Lim CL (2014) Image reconstruction from a complete set of geometric and complex moments. J Signal Process 98:224–232CrossRefGoogle Scholar
  7. 7.
    Jie Z (2013) A novel block-DCT and PCA based image perceptual hashing algorithm. IJ Comput Sci Issues 10(1):3Google Scholar
  8. 8.
    Kougianos E et al (2016) Design of a High-Performance system for secure image communication in the internet of things. IEEE Access 4:1222–1242CrossRefGoogle Scholar
  9. 9.
    Li X et al (2017) Hierarchical multilevel authentication system for multiple image based on phase retrieval and basic vector operations. Opt Lasers Eng 89:59–71CrossRefGoogle Scholar
  10. 10.
    Lin PY et al (2017) High payload secret hiding technology for QR codes. EURASIP J Image Video Process 14.
  11. 11.
    Mallahi ME, Mesbah A, Fadili HE, Zenkouar K, Qjidaa H (2015) Image analysis by discrete orthogonal Tchebichef moments for 3D object representation. WSEAS Trans Comput 14:513–525Google Scholar
  12. 12.
    Nafornita C, Isar A (2011) Application of discrete wavelet transform in watermarking. In Discrete Wavelet Transforms-Algorithms and Applications. Computer and Information Science, Numerical Analysis and Scientific Computing.
  13. 13.
    Nagarajan SK, Saravanan S (2012) Content-based medical image annotation and retrieval using perceptual hashing algorithm. IOSR Journal of Engineering 2(4):814–818CrossRefGoogle Scholar
  14. 14.
    Nikolaidis A (2015) Reversible data hiding in JPEG images utilizing zero quantized coefficients. IET Image Process 9(7):560–568CrossRefGoogle Scholar
  15. 15.
    Nyeem H, Boles W, Boyd C (2014) Digital image watermarking: its formal model, fundamental properties and possible attacks. EURASIP J Adv Signal Process 2014:135.
  16. 16.
    Piper A, Safavi-Naini R (2013) Scalable fragile watermarking for image authentication. IET Inf Secur 7(4):300–311Google Scholar
  17. 17.
    Preda RO et al (2015) Watermarking based image authentication robust to JPEG compression. Electron Lett 51(23):1873–1875CrossRefGoogle Scholar
  18. 18.
    Qian Z et al (2016) Reversible data hiding in encrypted images based on progressive recovery. IEEE Trans Signal Proc. Letters 23(11):1672–1676CrossRefGoogle Scholar
  19. 19.
    Rad RM et al (2014) A unified data embedding and scrambling method. IEEE Trans Image Process 23(4):1463–1475MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Ramos CC et al (2011) Watermarking-based image authentication system in the discrete wavelet transform domain. Discrete Wavelet Transform and Applications, Intech Publications.
  21. 21.
    Vellaisamy S, Ramesh V (2014) Inversion attack resilient zero-watermarking scheme for medical image aauthentication. IET Image Process 8(12):718–727Google Scholar
  22. 22.
    Shu HZ, Zhou J, Han GN, Luo LM, Coatrieux JL (2007) Image reconstruction from limited range projection using orthogonal moments. J Pattern Recognit 40:670–680CrossRefzbMATHGoogle Scholar
  23. 23.
    Singh C et al (2014) Image adaptive and high-capacity watermarking system for using accurate Zernike moments. IET Image Process 8(7):373–382CrossRefGoogle Scholar
  24. 24.
    Sun R, Yan X, Zeng W (2011) Geometric invariant robust image hashing via zernike moment. Int J Wirel Microwave Technol (IJWMT) 1(5):9Google Scholar
  25. 25.
    Tabatabaei SAH, Ur-Rehman O, Zivic N, Ruland C (2015) Secure and robust two-phase image authentication. IEEE Trans Multimed 17(7):945–956Google Scholar
  26. 26.
    Tang Z, Dai Y, Zhang X (2012) Perceptual hashing for color images using invariant moments. Int J Appl Math Inf Sci 6(2):643–650Google Scholar
  27. 27.
    Walia E et al (2013) Fragile and blind watermarking technique based on Weber’s law for medical image authentication. IET Comput Vis 7(1):9–19CrossRefGoogle Scholar
  28. 28.
    Wu WC (2017) Quantisation-based image authentication scheme using QR error correction. J Image Video Proc 2017:13.
  29. 29.
    Wu WC, Lin ZW (2016) SVD-based self-embedding image authentication scheme using quick response code features. J Vis Commun Image R 38:18–28CrossRefGoogle Scholar
  30. 30.
    Yu M et al (2015) New fragile watermarking method for stereo image authentication with localization and recovery. Int J Electron Commun 69(1):361–370CrossRefGoogle Scholar
  31. 31.
    Zhao Y, Wang S, Feng G, Tang Z (2010) A robust image hashing method based on zernike moments. J Comput Inf Syst 6(3):717–725Google Scholar
  32. 32.
    Zhao Y et al (2013) Robust hashing for image authentication using zernike moments and local features. IEEE Trans Inf Foren Secur 8(1):55–63CrossRefGoogle Scholar
  33. 33.
    Zheng D, Wang S, Zhao J (2009) RST invariant image watermarking algorithm with mathematical modeling and analysis of the watermarking processes. IEEE Trans Image Process 18(5):1055–1068Google Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringNational Engineering CollegeKovilpattiIndia

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