High capacity image steganographic model

High capacity image steganographic model

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IEE Proceedings - Vision, Image and Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Steganography is an ancient art of conveying messages in a secret way that only the receiver knows the existence of a message. So a fundamental requirement for a steganographic method is imperceptibility; this means that the embedded messages should not be discernible to the human eye. There are two other requirements, one is to maximise the embedding capacity, and the other is security. The least-significant bit (LSB) insertion method is the most common and easiest method for embedding messages in an image. However, how to decide on the maximal embedding capacity for each pixel is still an open issue. An image steganographic model is proposed that is based on variable-size LSB insertion to maximise the embedding capacity while maintaining image fidelity. For each pixel of a grey-scale image, at least four bits can be used for message embedding. Three components are provided to achieve the goal. First, according to contrast and luminance characteristics, the capacity evaluation is provided to estimate the maximum embedding capacity of each pixel. Then the minimum-error replacement method is adapted to find a grey scale as close to the original one as possible. Finally, the improved grey-scale compensation, which takes advantage of the peculiarities of human visual system, is used to eliminate the false contouring effect. Two methods, pixelwise and bitwise, are provided to deal with the security issue when using the proposed model. Experimental results show effectiveness and efficiency of the proposed model.


    1. 1)
      • B. Schneier . (1996) , Applied cryptography.
    2. 2)
      • KAHN, D.: `The history of steganography', Proceedings of the first workshop on Information hiding, 30 May–1 June 1996, Cambridge, UK, Springer-Verlag, 1174, p. 1–5, Lect. Notes Comput. Sci..
    3. 3)
      • PFITZMANN, B.: `Information hiding terminology', Proceedings of the first workshop on Information hiding, 30 May–1 June 1996, Cambridge, UK, Springer-Verlag, Lecture Notes Comput. Sci., 1174, p. 347–350.
    4. 4)
      • R.J. ANDERSON , F.A.P. PETITCOLAS . On the limits of steganography. IEEE J. Sel. Areas Commun. , 4 , 474 - 481
    5. 5)
      • M. KUTTER , F. JORDAN , F. BOSSEN . Digital signature of color images using amplitude modulation. J. Electron. Imaging , 2 , 326 - 332
    6. 6)
      • LANGELAAR, G.C., LUBBE, J.C.A., BIEMOND, J.: `Copy protection for multimedia data based on labeling techniques', Presented at the 17th symposium on Information theory in the Benelux, 30–31 May 1996, Enschede, The Netherlands.
    7. 7)
      • V. DARMSTAEDTER , J.-F. DELAIGLE , J.J. QUISQUATER , B. MACQ . Low cost spatial watermarking. Comput. Graphics , 4 , 417 - 424
    8. 8)
      • M. Swanson , M. Kobayashi , A. Tewfik . Multimedia data embedding and watermarking technologies. Proc. IEEE , 6 , 1064 - 1087
    9. 9)
      • I.J. COX , J. KILIAN , T. LEIGHTON , T. SHAMOON . Secure spread spectrum watermaking for multimedia. IEEE Trans. Image Process. , 12 , 1673 - 1687
    10. 10)
      • R.B. WOLFGANG , C.I. PODILCHUK , E.J. DELP . Perceptual water-marks for digital images and video. Proc. SPIE. - Int. Soc. Opt. Eng. , 44 - 51
    11. 11)
      • KOCH, E., ZHAO, J.: `Towards robust and hidden image copyright labeling', Proceedings of IEEE workshop on Nonlinear signal and image processing, 20–22 June 1995, Neos Marmaras, Halkidiki, Greece, p. 452–455.
    12. 12)
      • XIA, X.-G., BONGELET, C.G., ARCE, G.R.: `A multiresolution water-mark for digital images', Proceedings of IEEE international conference on Image Processing, 26–29 Oct 1997, Santa Barbara, CA, Vol. 3, p. 548–551.
    13. 13)
      • LIN, E.T., DELP, E.J.: `A review of data hiding in digital images', Proceedings of the conference on Image processing, image quality, image capture systems PICS '99, 25–28 April 1999, Savannah, Georgia, p. 274–278.
    14. 14)
      • N.F. JOHNSON , S. JAJODIA . Steganography: seeing the unseen. IEEE Comput. , 26 - 34
    15. 15)
      • W. BENDER , D. GRUHL , N. MORIMOTO , A. LU . Techniques for data hiding. IBM syst. J. , 313 - 336
    16. 16)
      • W.K. Pratt . (1978) , Digital image processing.
    17. 17)
      • MINTZER, F.C., GOERTZEL, G., THOMPSON, G.R.: `Display of images with calibrated color on a system featuring monitors with limited color palettes', SID international symposium digest of technical papers, 1992, p. 377–380.
    18. 18)
      • M.M. YEUNG , F.C. MINTZER . Invisible watermarking for image verification. J. Electron. Imaging , 3 , 578 - 591

Related content

This is a required field
Please enter a valid email address