Skip to main content

Edge Based Steganography on Colored Images

  • Conference paper
Intelligent Computing Theories (ICIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7995))

Included in the following conference series:

Abstract

This paper proposes a novel technique to hide secret messages in the least two significant bits of the edges in the cover image. Edges make a better option to hide secret data than any other region of an image where a small distortion is much more noticeable. Edge detection is adaptive to the amount of data in the message. Smaller is the amount of data, more striking edges are selected. Experimental results have shown that the technique performs better or at par with the existing steganography techniques against visual attacks.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wu, D., Tsai, W.: A Steganographic Method for Images by Pixel Value Differencing. Pattern Recognition Letters 24(9-10), 1613–1626 (2003)

    Article  MATH  Google Scholar 

  2. Zhang, X., Wang: Vulnerability of Pixel-Value Differencing Steganography to Histogram Analysis and Modification for Enhanced Security. Pattern Recognition Letters 25(3), 331–339 (2004)

    Article  Google Scholar 

  3. Yang, C., Weng, C., Wang, S., Sun, H.: Adaptive Data Hiding in Edge Areas of Images with Spatial Lsb Domain Systems. IEEE Transactions on Information Forensics and Security 3(3), 488–497 (2008)

    Article  Google Scholar 

  4. Luo, W., Huang, F., Huang, J.: Edge Adaptive Image Steganography Based on Lsb Matching Revisited. IEEE Transactions on Information Forensics and Security 5(2), 201–214 (2010)

    Article  MathSciNet  Google Scholar 

  5. Hempstalk, K.: Hiding Behind Corners: Using Edges in Images for Better Steganography. In: Proceedings Computing Womens Congress, Hamilton, New Zealand (2006)

    Google Scholar 

  6. Westfeld, A., Pfitzmann, A.: Attacks on Steganographic Systems. In: Pfitzmann, A. (ed.) IH 1999. LNCS, vol. 1768, pp. 61–76. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  7. Fridrich, J., Goljan, M., Du, R.: Detecting Lsb Steganography in Color and Gray-Scale Images. IEEE MultiMedia 8(4), 22–28 (2001)

    Article  Google Scholar 

  8. Dumitrescu, S., Wu, X., Memon, N.: On Steganalysis of Random Lsb Embedding in Continuous-Tone Images. In: International Conference on Image Processing, vol. 3, pp. 641–644 (2002)

    Google Scholar 

  9. Ker, A.D., Böhme, R.: Revisiting Weighted Stego-Image Steganalysis. In: Proceedings SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, San Jose, CA, pp. 681905-1–681905-17 (2008)

    Google Scholar 

  10. Canny, J.: A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)

    Article  Google Scholar 

  11. Nrcs photo gallery (2013), http://photogallery.nrcs.usda.gov/res/sites/photogallery/

  12. Adobe color profiles (2013), http://www.adobe.com/support/downloads/detail.jsp?ftpID=3680

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Modi, M.R., Islam, S., Gupta, P. (2013). Edge Based Steganography on Colored Images. In: Huang, DS., Bevilacqua, V., Figueroa, J.C., Premaratne, P. (eds) Intelligent Computing Theories. ICIC 2013. Lecture Notes in Computer Science, vol 7995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39479-9_69

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39479-9_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39478-2

  • Online ISBN: 978-3-642-39479-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics