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An Optimized Halftone Visual Cryptography Scheme Using Error Diffusion

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Abstract

Halftone Visual Cryptography (HVC) is an encryption technique that encodes the secret image into halftone images in order to produce secure meaningful shares. Many methods have been proposed for developing HVC to protect the security of the images. Yet, these methods still have some problems such as poor visual quality of shares, large pixel expansion, interference of secret image on shared images, and interference shared images on retrieved image. To solve such problems, an optimized HVC scheme (OHVCS) using Error Diffusion (ED) is proposed in this paper. The proposed scheme eliminates the explicit requirement of codebook and reduces the random patterns of the shared images, as it encodes only the black pixels of the secret image, taking into account that the pixel expansion is the smallest size to be used. Moreover, it performs the basic concept of Visual Cryptography (VC); therefore, the security of the construction scheme is assured. The experimental results, performance evaluation through statistical analysis, and comparison with some existing schemes in various aspects of HVC show the effectiveness of the proposed scheme.

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References

  1. Alex NS, Anbarasi LJ (2011) Enhanced image secret sharing via error diffusion in halftone visual cryptography. 2011 3rd International Conference on Electronics Computer Technology, Kanyakumari: 393–397. https://doi.org/10.1109/ICECTECH.2011.5941725

  2. Askari N, Heys HM, Moloney CR (2013) An extended visual cryptography scheme without pixel expansion for halftone images. 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Regina, SK: 1–6. https://doi.org/10.1109/CCECE.2013.6567726

  3. Hodeish ME, Humbe VT (2014) State-of-the-Art visual cryptography schemes. International Journal of Electronics Communication and Computer Engineering 5:412–420

    Google Scholar 

  4. Hodeish ME, Bukauskas L, Humbe VT (2016) An Optimal (k, n) Visual Secret Sharing Scheme for Information Security. Procedia Computer Science 93:760–767

    Article  Google Scholar 

  5. Hou Y-C, Wei S-C, Lin C-Y (2014) Random-Grid-Based Visual Cryptography Schemes. Circuits and Systems for Video Technology, IEEE Transactions 24(5):733–744. https://doi.org/10.1109/TCSVT.2013.2280097

    Article  Google Scholar 

  6. Jarvis JF, Judice CN, Ninke WH (1976) A survey of techniques for the display of continuous tone pictures on bilevel displays. Computer Graphics and Image Processing 5(1):13–40

    Article  Google Scholar 

  7. Kumar P, Agarwal S, Shivani S (2014) Halftone Visual Cryptography with Pixel Expansion through Error Diffusion. International Journal of Information & Computation Technology 4:1419–1427

    Google Scholar 

  8. Lee KH, Chiu PL (2012) An extended visual cryptography algorithm for general access structures. IEEE transactions on information forensics and security 7(1):219–229. https://doi.org/10.1109/TIFS.2011.2167611

    Article  Google Scholar 

  9. Lin W, Kuo CCJ (2011) Perceptual visual quality metrics: A survey. J Vis Commun Image Represent 22(4):297–312

    Article  Google Scholar 

  10. Liu F, Wu C (2011) Embedded Extended Visual Cryptography Schemes. IEEE Transactions on Information Forensics and Security 6(2):307–322. https://doi.org/10.1109/TIFS.2011.2116782

    Article  Google Scholar 

  11. Mishra SK and Biswaranjan K (2015) Extended visual cryptography for general access structures using random grids," 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Kochi: 1924–1929. https://doi.org/10.1109/ICACCI.2015.7275899

  12. Nagaveena DD, Kumar SCP (2013) Vessels Segmentation in Diabetic Retinopathy by Adaptive Median Thresholding. The International Journal of Science & Technoledge 1(1):17–22

    Google Scholar 

  13. Naor M, Shamir A (1994) Visual cryptography. In: Workshop on the Theory and Application of Cryptographic Techniques. Springer, Berlin, pp 1–12

    Google Scholar 

  14. Nouri R, Mansouri A (2017) Digital image steganalysis based on the reciprocal singular value curve. Multimedia Tools and Applications 76(6):8745–8756. https://doi.org/10.1007/s11042-016-3507-y

    Article  Google Scholar 

  15. Ouni S, Chambah M, Herbin M, Zagrouba E (2008) Are existing procedures enough? Image and video quality assessment: review of subjective and objective metrics. Image Quality and System Performance V (Vol. 6808, p. 68080Q). International Society for Optics and Photonics

  16. Sangeetha Devi E (2010) Enhanced visual secret sharing scheme via halftoning technique. 2010 International Conference on Communication Control And Computing Technologies, Ramanathapuram: 769–776. https://doi.org/10.1109/ICCCCT.2010.5670739

  17. Satir E, Isik H (2014) A Huffman compression based text steganography method. Multimedia tools and applications 70(3):2085–2110. https://doi.org/10.1007/s11042-012-1223-9

    Article  Google Scholar 

  18. Shivani S, Agarwal S (2016) VPVC: verifiable progressive visual cryptography. Pattern Anal Applic: 1–28. https://doi.org/10.1007/s10044-016-0571-x

  19. Ulichney RA (1988) Dithering with blue noise. In: Proceedings of the IEEE. 76(1):56–79. https://doi.org/10.1109/5.3288

  20. Wang Z, Bovik AC (2002) A universal image quality index, IEEE Signal Process. Lett 9(3):81–84. https://doi.org/10.1109/97.995823

    Google Scholar 

  21. Wang Z, Sheikh HR, Bovik AC (2003) Objective video quality assessment. The handbook of video databases: design and applications 41:1041–1078

    Google Scholar 

  22. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612. https://doi.org/10.1109/TIP.2003.819861

    Article  Google Scholar 

  23. Wang Z, Arce GR, Di Crescenzo G (2009) Halftone Visual Cryptography Via Error Diffusion. IEEE Transactions on Information Forensics and Security 4(3):383–396. https://doi.org/10.1109/TIFS.2009.2024721009

    Article  MATH  Google Scholar 

  24. Xia Z, Wang X, Sun X, Liu Q, Xiong N (2016) Steganalysis of LSB matching using differences between nonadjacent pixels. Multimedia Tools and Applications 75(4):1947–1962. https://doi.org/10.1007/s11042-014-2381-8

    Article  Google Scholar 

  25. Yan X, Wang S, Niu X, Yang CN (2015) Halftone visual cryptography with minimum auxiliary black pixels and uniform image quality. Digital Signal Processing 38:53–65

    Article  Google Scholar 

  26. Zhi Z, Arce GR, Di Crescenzo G (2006) Halftone visual cryptography. IEEE Trans Image Process 15(8):2441–2453. https://doi.org/10.1109/TIP.2006.875249

    Article  Google Scholar 

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Correspondence to Mahmoud E. Hodeish.

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Hodeish, M.E., Humbe, V.T. An Optimized Halftone Visual Cryptography Scheme Using Error Diffusion. Multimed Tools Appl 77, 24937–24953 (2018). https://doi.org/10.1007/s11042-018-5724-z

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  • DOI: https://doi.org/10.1007/s11042-018-5724-z

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