Skip to main content
Log in

Enhanced semantic visual secret sharing scheme for the secure image communication

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Sharing multimedia information through the means of internet has increased many folds in this digital world. Information needs to be send across various secure channel as it contains sensitive data such as bank account details, medical reports or any financial documents. Due to the importance of information sharing, security is the most important objective that needs to be addressed while sharing this sensitive information. In order to share the information securely, one such way is visual secret sharing or visual cryptography. In this paper, introduced Enhanced Semantic Visual Secret Sharing (ESVSS) Scheme that transmits a gray-scale secret image to the receiver using two color cover images. At the receiver end, the secret image is reconstructed by digitally stacking the shares together. The result analysis shows that the ESVSS achieves security and improves the quality of the reconstructed image. The quality is measured by Peak Signal to Noise Ratio (PSNR) up to +39 dB and Mean Square Error is reduced to 6. The Universal Image Quality Index (UIQI) results are recorded up to 90% for the reconstructed image with minimal computational complexity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Blesswin AJ, Mary GS (2015) Optimal grayscale visual cryptography using error diffusion to secure image communication. International Journal of Control Theory and Applications 8:1511–1519

    Google Scholar 

  2. Blesswin AJ, Visalakshi P (2014) Multi-secret semantic visual cryptographic protocol (MSVCP) for securing image communications. Asian Journal of Information Technology 13:506–512

    Google Scholar 

  3. Blesswin AJ, Genitha A, Mary GS (2016) A novel QR-code authentication protocol using visual cryptography for secure communications. International Journal of Control Theory and Applications 9:967–974

    Google Scholar 

  4. Blundo C, Santis AD, Naor M (2000) Visual cryptography for grey level images. Inf Process Lett 75:255–259

    Article  MathSciNet  Google Scholar 

  5. Chang CC, Lin CC, Le THN, Le HB (2009) Self-verifying visual secret sharing using error diffusion and interpolation techniques. IEEE Transactions on Information Forensics and Security 4:790–801

    Article  Google Scholar 

  6. Chen TH, Wu CS (2011) Efficient multi-secret image sharing based on Boolean operations. Signal Process 91:90–97

    Article  Google Scholar 

  7. Cheng Y, Fu Z, Yu B (2018) Improved visual secret sharing scheme for QR code applications. In: IEEE Transactions on Information Forensics and Security 13(9):2393–2403. https://doi.org/10.1109/TIFS.2018.2819125

  8. Fu Z, Cheng Y, Yu B (2018) Visual cryptography scheme with meaningful shares based on QR Codes. In: IEEE Access 6:59567–59574. doi: https://doi.org/10.1109/ACCESS.2018.2874527

  9. Gayathri M, Blesswin AJ, Mary GS (2016) An efficient QR-code authentication protocol using visual cryptography for securing ubiquitous multimedia communications. Indian J Sci Technol 9:1–7

    Google Scholar 

  10. Hou YC (2003) Visual cryptography for color images. Pattern Recogn 36:1619–1629

    Article  Google Scholar 

  11. Jia X, Wang D, Nie D, Zhang C (2018) Collaborative visual cryptography schemes. In: IEEE Transactions on Circuits and Systems for Video Technology 28(5):1056–1070. https://doi.org/10.1109/TCSVT.2016.2631404

  12. Kang IK, Arce GR, Lee HK (2011) Color extended visual cryptography using error diffusion. IEEE Trans Image Process 20:132–145

    Article  MathSciNet  Google Scholar 

  13. Kester QA (2013) A cryptographic image encryption technique based on the RGB PIXEL shuffling. International Journal of Advanced Research in Computer Engineering & Technology 2:848–854

    Google Scholar 

  14. Lee JS, Hsieh MH (2013) Preserving user-participation for insecure network communications with CAPTCHA and visual secret sharing technique. IET Networks 2:81–91

    Article  Google Scholar 

  15. Lin CC, Tsai WH (2003) Visual cryptography for gray-level images by dithering techniques. Pattern Recogn Lett 24:349–358

    Article  Google Scholar 

  16. Liu F, Wu CK, Lin XJ (2008) Colour visual cryptography schemes. IET Inf Secur 2:151–165

    Article  Google Scholar 

  17. Mhala NC, Jamal R, Pais AR (2018) Randomised visual secret sharing scheme for grey-scale and colour images. In: IET Image Processing, vol. 12, no. 3, pp. 422–431, 3. https://doi.org/10.1049/iet-ipr.2017.0759

  18. Mohamed Shakeel P, El Tobely TE, Al-Feel H, Manogaran G, Baskar S (2019) Neural network based brain tumor detection using wireless infrared imaging sensor. IEEE Access 1

  19. Mrunali G (2014) Image encryption technique based on visual cryptography. International Journal of Research 1:1694–1699

    Google Scholar 

  20. Naor M, Shamir A (1994) Visual cryptography. Proceedings of Advances in Cryptology-Eurprocrypt'94, 950:1–12

  21. Prisco RD, Santis AD (2014) On the relation of random grid and deterministic visual cryptography. IEEE Transactions on Information Forensics and Security 9:653–665

    Article  Google Scholar 

  22. Ren Y, Liu F, Guo T, Feng R, Lin D (2017) Cheating prevention visual cryptography scheme using Latin square. In: IET Information Security, vol. 11, no. 4, pp. 211–219, 7. https://doi.org/10.1049/iet-ifs.2016.0126

  23. Shakeel PM, Baskar S, Dhulipala VS, Jaber MM (2018) Cloud based framework for diagnosis of diabetes mellitus using K-means clustering. Health Information Science and Systems 6(1):16. https://doi.org/10.1007/s13755-018-0054-0

    Article  Google Scholar 

  24. Shyu SJ (2018) XOR-based visual cryptographic schemes with monotonously increasing and flawless reconstruction properties. In: IEEE Transactions on Circuits and Systems for Video Technology, 28(9):2397–2401. https://doi.org/10.1109/TCSVT.2017.2707923

  25. Sridhar KP, Baskar S, Shakeel PM, Dhulipala VS (2018) Developing brain abnormality recognize system using multi-objective pattern producing neural network. J Ambient Intell Humaniz Comput:1–9. https://doi.org/10.1007/s12652-018-1058-y

  26. Thung K, Raveendran P (2009) A survey of image quality measures, 2009 International Conference for Technical Postgraduates (TECHPOS), Kuala Lumpur, p 1–4. https://doi.org/10.1109/TECHPOS.2009.5412098

  27. Weir J, Yan W (2010) Secure masks for visual cryptography. Transactions on Data Hiding and Multimedia Security V 6010:106–128

    Article  Google Scholar 

  28. Wu HC, Chan CC (2005) Sharing visual multi-secrets using circle shares. Computer Standards & Interfaces 28:123–135

    Article  Google Scholar 

  29. Wu X, Sun W (2013) Generalized random grid and its applications in visual cryptography 8:1541–1553

  30. Yan X, Wang S, Niu X, Yang C-N (2015) Halftone visual cryptography with minimum auxiliary black pixels and uniform image quality. Digital Signal Processing 38:53–65, ISSN 1051-2004. https://doi.org/10.1016/j.dsp.2014.12.002

    Article  Google Scholar 

  31. Yan X, Lu Y, Liu L (2018) General meaningful shadow construction in secret image sharing. In: IEEE Access, vol. 6, p 45246–45255. https://doi.org/10.1109/ACCESS.2018.2865421

  32. Yan B, Xiang Y, Hua G (2019) Improving the visual quality of size-invariant visual cryptography for grayscale images: an analysis-by-synthesis (AbS) approach. In: IEEE Transactions on Image Processing, 28(2):896–911. https://doi.org/10.1109/TIP.2018.2874378

  33. Yang CN, Laih CS (2000) New colored visual secret sharing schemes. Des Codes Crypt 20:325–335

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to John Blesswin A.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

John Blesswin A, Raj, C., Sukumaran, R. et al. Enhanced semantic visual secret sharing scheme for the secure image communication. Multimed Tools Appl 79, 17057–17079 (2020). https://doi.org/10.1007/s11042-019-7535-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7535-2

Keywords

Navigation