Soft Computing

, Volume 13, Issue 4, pp 401–416 | Cite as

Spiking neural network and wavelets for hiding iris data in digital images

  • Aboul Ella Hassanien
  • Ajith Abraham
  • Crina Grosan
Focus

Abstract

This paper introduces an efficient approach to protect the ownership by hiding the iris data into a digital image for authentication purposes. The idea is to secretly embed an iris code data into the content of the image, which identifies the owner. Algorithms based on Biologically inspired Spiking Neural Networks, called Pulse Coupled Neural Network (PCNN) are first applied to increase the contrast of the human iris image and adjust the intensity with the median filter. It is followed by the PCNN segmentation algorithm to determine the boundaries of the human iris image by locating the pupillary boundary and limbus boundary of the human iris for further processing. A texture segmentation algorithm for isolating the iris from the human eye in a more accurate and efficient manner is presented. A quad tree wavelet transform is first constructed to extract the texture feature. Then, the Fuzzy c-Means (FCM) algorithm is applied to the quad tree in the coarse-to-fine manner by locating the pupillary boundary (inner) and outer (limbus) boundary for further processing. Then, iris codes (watermark) are extracted that characterizes the underlying texture of the human iris by using wavelet theory. Then, embedding and extracting watermarking methods based on Discrete Wavelet Transform (DWT) to insert and extract the generated iris code are presented. The final process deals with the authentication process. In the authentication process, Hamming distance metric that measure the variation between the recorded iris code and the corresponding extracted one from the watermarked image (Stego image) to test weather the Stego image has been modified or not is presented. Simulation results show the effectiveness and efficiency of the proposed approach.

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References

  1. Aslantas V (2008) A singular-value decomposition-based image watermarking using genetic algorithm. Int J Electron Commun 62: 386–394CrossRefGoogle Scholar
  2. Brassil JT, Low S, Maxemchuk NF (1999) Copyright protection for the electronic distribution of text. Proc IEEE 87(7): 1181–1196CrossRefGoogle Scholar
  3. Celik MU, Sharma G, Saber E, Tekalp AM (2006) Lossless watermarking for image authentication: a new framework and an implementation. IEEE Trans Image Process 15: 1042–1049CrossRefGoogle Scholar
  4. Celik MU, Sharma G, Saber E, Tekalp AM (2002) Hierarchical watermarking for secure image authentication with localization. IEEE Trans Image Process 11: 585–595CrossRefGoogle Scholar
  5. Chang CC, Hwang KF, Hwang MS (2002) Robust authentication scheme for protecting copyrights of images and graphics. IEE Proc Vis Image Signal Process 149: 43–50CrossRefGoogle Scholar
  6. Chen P-Y, Lin H-J (2006) A DWT based approach for image steganography. Int J Appl Sci Eng 4(3): 275–290Google Scholar
  7. Coifman R, Meyer Y, Quake S, Wickerhauser V (1990) Signal processing and compression with wave packets Numerical Algorithms Research Group. Yale University, New Haven, CTGoogle Scholar
  8. Cox IJ, Miller ML (2002) The first 50 years of electronic watermarking. EURASIP JASP 2: 126–132Google Scholar
  9. Cox IJ, Kilian J, Leighton T, Shamoon TG (1997) Secure spread spectrum watermarking for multimedia. IEEE Trans Image Process 6(12): 1673–1687CrossRefGoogle Scholar
  10. Cox IJ, Miller ML, Bloom JA (2001) Digital watermarking. Morgan Kaufmann, Menlo ParkGoogle Scholar
  11. Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, Reitboeck HJ (1988) Coherent oscillations: a mechanism of feature linking in the visual cortex. Biol Cybern 60: 121–130CrossRefGoogle Scholar
  12. Eckhorn R, Reitboeck HJ, Arndt M (1990) Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex. Neural Comp 2: 293–307CrossRefGoogle Scholar
  13. Eckhorn R (1999) Neural mechanisms from visual cortex suggest basic circuits for linking field models. IEEE Trans Neural Netw 10: 464–479CrossRefGoogle Scholar
  14. El-dahshan E, Redi A, Hassanien AE, Xiao K (2007) Accurate detection of prostate boundary in ultrasound images using biologically inspired spiking neural network. In: International Symposium on Intelligent Siganl Processing and Communication Systems Proceeding, Nov. 28–Dec. 1, 2007. Xiamen, China, pp 333–336Google Scholar
  15. Hartung F, Kutter M (1999) Multimedia watermarking techniques. Proc IEEE 87: 1079–1107CrossRefGoogle Scholar
  16. Hassanien AE, Jafar MA (2003) An iris recognition system to enhance E-security environment based on wavelet theory. Adv Model Optim J 5(2): 93–104MATHGoogle Scholar
  17. Hassanien AE (2005) Watermarking algorithm for copyright protection using discrete wavelet transform. In: Proceedings of the 8th International Conference on Pattern Recognition and Information Processing (PRIP’05), May, 18–20, Minsk, BelarusGoogle Scholar
  18. Hassanien AE (2006) Pulse coupled neural network for detection of masses in digital mammogram. Neural Netw World J 2/06: 129–141Google Scholar
  19. Hassanien AE (2007) Fuzzy-rough hybrid scheme for breast cancer detection. Image Comput Vision J 25(2): 172–183CrossRefGoogle Scholar
  20. Helal MA, HassanienAE Taha E-A, Nahla E-H (2004) An efficient texture segmentation algorithm for isolating Iris pattern based on wavelet theory. Int J Pattern Recognit Image Anal 14(1): 97–103Google Scholar
  21. Hsu C-T, Wu J-L (1999) Hidden digital watermarks in images. IEEE Trans Image Process 8(1): 58–68CrossRefGoogle Scholar
  22. Hubbard BB (1995) The world according to wavelets. A K Peters Wellesley, MassachusettsMATHGoogle Scholar
  23. Jain AK, Uludag U (2003) Hiding biometric data. IEEE Trans Pattern Anal Mach Intell 25(11): 1494–1498CrossRefGoogle Scholar
  24. Kagan FG, Leblebici Y, Mlynek D (1998) A compact high-speed hamming distance comparator for pattern matching applications. http://turquoise.wpi.edu
  25. Kerckhoffs A (1883) La Cryptographie Militaire (Military Cryptography). J Sci Militaires (J. Military Science, in French), Feb. 1883Google Scholar
  26. Lee SJ, Jung SH (2001) A survey of watermarking techniques applied to multimedia. In: Proceedings of IEEE international symposium on industrial electronics, Pusan, Korea, pp 272–277Google Scholar
  27. Leea C-C, Wub H-C, Tsaic C-S, Chud Y-P (2008) Adaptive lossless steganographic scheme with centralized difference expansion. Pattern Recognit 41: 2097–2106CrossRefGoogle Scholar
  28. Mallat SG (1989) A theory for multi-resolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell II(7): 674–693CrossRefGoogle Scholar
  29. McEliece R, Posner C, Rodemich R, Santosh R (1987) The capacity of the Hopfield associative memory. IEEE Trans Inform Theory 33(4): 461–482MATHCrossRefMathSciNetGoogle Scholar
  30. Meyer Y (1993) Wavelets: algorithms & applications. SIAM, PhiladelphiaMATHGoogle Scholar
  31. Neil FJ, Zoran Dc, Sushil J (2000) Information hiding: steganography and watermarking—attacks and countermeasures. Kluwer, DordrechtGoogle Scholar
  32. Nikolaidis N, Pitas I (1996) Copyright protection of images using robust digital signatures. In: Proceedings of ICASSP’96, Atlanta, Georgia, May, pp 2168–2171Google Scholar
  33. Petitcolas FAP, Anderson RJ, Kuhn MG (1995) Information hiding: a survey. Proc IEEE, special issue on protection of multimedia content 87(7): 1062–1078Google Scholar
  34. Petitcolas FAP (2000) Watermarking schemes evaluation. IEEE Signal Process 17(5): 58–64CrossRefGoogle Scholar
  35. Podilchuk CI, Delp EJ (2001) Digital watermarking: algorithms and applications. IEEE Signal Process Mag, pp 33–46Google Scholar
  36. Potdar VM, Han S, Chang E (2005) A survey of digital image watermarking techniques. In: Proceedings of IEEE third international conference on industrial informatics, INDIN05, pp 709–16Google Scholar
  37. Provos N, Honeyman P (2003) Hide and seek: an introduction to steganography. IEEE Secur Priv 1(3): 32–44CrossRefGoogle Scholar
  38. Ross A, Jain A (2003) Information fusion in biometrics. Pattern Recognit Lett 24: 2115–2125CrossRefGoogle Scholar
  39. Sarukkai SR, Zhang DD (2002) Biometric solutions for authentication in an E-World. Springer, BerlinGoogle Scholar
  40. Shen J (2003) A note on wavelets and diffusions. J Comp Anal Appl 5: 147–159MATHGoogle Scholar
  41. Wang Y, Doherty JF, Van Dyck RE (2002) A Wavelet-based watermarking algorithm for ownership verification of digital images. IEEE Trans Image Process 11(2): 77–88CrossRefGoogle Scholar
  42. Wolfgang RB, Delp EJ (1996) A watermark for digital images. Proc ICIP’ 96(3): 219–222Google Scholar
  43. Wong PW, Memon N (2001) Secret and public key image watermarking schemes for image authentication and ownership verification. IEEE Trans Image Process 10(10): 1593–1601MATHCrossRefGoogle Scholar
  44. Wong PW (1998) A public key watermark for image verification and authentication. IEEE Int Conf Image Process 1: 455–459Google Scholar
  45. Yang M, Trifas M, Bourbakis, Cushing C (2007) A Robust Information Hiding Methodology in Wavelet Domain. Signal and Image Processing, SIP 2007. Honolulu, USA ProceedingGoogle Scholar
  46. Yang C-H (2008) Inverted pattern approach to improve image quality of information hiding by LSB substitution. Pattern Recognit. http://www.sciencedirect.co. Accessed 9 Feb 2008
  47. Zhang X, Wang S (2005) Steganography using multiple-base notational system and human vision sensitivity. IEEE Signal Process Lett 12: 67–70CrossRefGoogle Scholar
  48. Zhang F, Pan Z, Cao K, Zheng F, Wu F (2008) The upper and lower bounds of the information-hiding capacity of digital images. Inform Sci. doi:10.1016/j.ins.2008.03.011

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Aboul Ella Hassanien
    • 1
    • 2
  • Ajith Abraham
    • 3
  • Crina Grosan
    • 4
  1. 1.Department of Quantitative Methods and Information Systems, College of Business AdministrationKuwait UniversitySafatKuwait
  2. 2.Information Technology Department, FCICairo UniversityOrman, GizaEgypt
  3. 3.Center for Quantifiable Quality of Service in Communication SystemsNorwegian University of Science and TechnologyTrondheimNorway
  4. 4.Department of Computer Science, Faculty of Mathematics and Computer ScienceBabeş Bolyai UniversityCluj-NapocaRomania

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