High Capacity Image Steganography Based on Genetic Algorithm and Wavelet Transform

  • Elham Ghasemi
  • Jamshid Shanbehzadeh
  • Nima Fassihi
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 110)


This paper presents the application of wavelet transform and genetic algorithm (GA) in a novel steganography scheme. We employ a GA based mapping function to embed data in discrete wavelet transform coefficients in 4 ×4 blocks on the cover image. The optimal pixel adjustment process (OPAP) is applied after embedding the message. We utilize the frequency domain to improve the robustness of steganography and, we implement GA and OPAP to obtain an optimal mapping function to reduce the difference error between the cover and the stego-image, therefore improving the hiding capacity with low distortions. Our simulation results reveal that the novel scheme outperforms adaptive steganography technique based on wavelet transform in terms of peak signal to noise ratio and capacity, 39.94 dB and 50% respectively.


Steganography Discrete wavelet transform Genetic algorithm Optimal pixel adjustment process Image processing 


  1. 1.
    Inoue H, Miyazaki A, Katsura T (2002) An image watermarking method based on the wavelet transform. In: International Conference on Image Processing, IEEE ICIP, Kobe, vol 1, pp 296–300Google Scholar
  2. 2.
    Provos N, Honeyman P (2003) Hide and seek: an introduction to steganography. In: IEEE Journal Computer Society, ISSN: 1540-7993, 11 June 2003, pp 32–44Google Scholar
  3. 3.
    Provos N (2001) Defending against statistical steganalysis. In: SSYM’01 Proceedings of the 10th conference on USENIX Security Symposium, USENIX Association Berkeley, CA, USA, vol 10, pp 323–335Google Scholar
  4. 4.
    Wu N, Hwang M (2007) Data hiding: current status and key issues. Int J Network Security 4(1):1–9Google Scholar
  5. 5.
    Chen W (2003) A comparative study of information hiding schemes using amplitude, frequency and phase embedding, PhD thesis, National Cheng Kung University, TaiwanGoogle Scholar
  6. 6.
    Chi-kwong C, Cheng LM (2002) Improved hiding data in images by optimal moderately significant-bit replacement. IEE Electron 37:1017–1018Google Scholar
  7. 7.
    Chan CK, Chang LM (2004) Hiding data in images by simple LSB substitution. Pattern Recogn 37:469–474CrossRefMATHGoogle Scholar
  8. 8.
    Chang K-C, Chang C-P, Huang PS, Te-Ming T (2008) A novel image steganographic method using tri-way pixel-value differencing. J Multimedia 3(2):37–44Google Scholar
  9. 9.
    Lee YK, Chen LH (2000) High capacity image steganographic model. IEE Proc Image Signal Process 147:288–294CrossRefGoogle Scholar
  10. 10.
    Lai B, Chang L (2006) Adaptive data hiding for images based on haar discrete wavelet transform. In: Lecture Notes in Computer Science, Springer-verlag Berlin Heidelberg, vol 4319, pp 1085–1093Google Scholar
  11. 11.
    Provos N (2001) Defending against statistical steganalysis. In: Proceedings of 10th usenix security symposium, Usenix Assoc, pp 323–335Google Scholar
  12. 12.
    El Safy RO, Zayed HH, El Dessouki A (2009) An adaptive steganography technique based on integer wavelet transform. In: ICNM international conference on networking and media convergence, Cairo 24–25 March, pp 111–117Google Scholar
  13. 13.
    Raja KB, Kiran KK, Satish KN, Lashmi MS, Preeti H, Venugopal KR, Patnaik LM (2007) Genetic algorithm based steganography using wavelets. In: International conference on information system security, ICISS, Springer-Verlag Berlin Heidelberg, vol 4812, pp 51–63Google Scholar
  14. 14.
    Fard AM, Akbarzadeh MR, Varasteh AF (2006) A new genetic algorithm approach for secure JPEG steganography. International conference on engineering of intelligence systems, ICEIS Islamabad, 18 September, pp 1–6Google Scholar
  15. 15.
    ElShafie DR, Kharma N, Ward R (2008) Parameter optimization of an embedded watermark using a genetic algorithm. In: International symposium on communications, control and signal processing, ISCCSP, St Julians12–14 March, pp 1263–1267Google Scholar
  16. 16.
    Chen P, Lin H (2006) A DWT based approach for image steganography. Int J Appl Sci Eng 4(3):275–290Google Scholar
  17. 17.
    Ghasemi E, Shanbehzadeh J, Fassihi N High capacity image steganography using wavelet transform and genetic algorithm. In: Lecture notes in engineering and computer science: proceedings of the international multiconference of engineers and computer scientists 2011, IMECS 2011, Hong Kong, 16–18 March 2011, pp 495–498Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Elham Ghasemi
    • 1
  • Jamshid Shanbehzadeh
    • 2
  • Nima Fassihi
    • 1
  1. 1.Department of Computer Engineering at Science and Research branchIslamic Azad UniversityTehranIran
  2. 2.Department of Computer EngineeringTarbiat Moallem University TehranTehranIran

Personalised recommendations