Multimedia Tools and Applications

, Volume 72, Issue 1, pp 637–666 | Cite as

Secure multimodal biometric authentication with wavelet quantization based fingerprint watermarking

  • Bin Ma
  • Yunhong Wang
  • Chunlei Li
  • Zhaoxiang ZhangEmail author
  • Di Huang


As malicious attacks greatly threaten the security and reliability of biometric systems, ensuring the authenticity of biometric data is becoming increasingly important. In this paper we propose a watermarking-based two-stage authentication framework to address this problem. During data collection, face features are embedded into a fingerprint image of the same individual as data credibility token and secondary authentication source. At the first stage of authentication, the credibility of input data is established by checking the validness of extracted patterns. Due to the specific characteristics of face watermarks, the face detection based classification strategies are introduced for reliable watermark verification instead of conventional correlation based watermark detection. If authentic, the face patterns can further serve as supplemental identity information to facilitate subsequential biometric authentication. In this framework, one critical issue is to guarantee the robustness and capacity of watermark while preserving the discriminating features of host fingerprints. Hence a wavelet quantization based watermarking approach is proposed to adaptively distribute watermark energy on significant DWT coefficients of fingerprint images. Experimental results which evaluate both watermarking and biometric authentication performance demonstrate the effectiveness of this work.


Biometrics Digital watermarking DWT Dither modulation 



This work is funded by the National Basic Research Program of China (No. 2010CB327902), the National Natural Science Foundation of China (No. 60873158, No. 61005016, No. 61061130560) and the Fundamental Research Funds for the Central Universities.


  1. 1.
    Araque J, Baena M, Chalela B, Navarro D, Vizcaya P (2002) Synthesis of fingerprint images. In: Proceedings of IEEE international conference on pattern recognition, 2002, vol 2, pp 422–425Google Scholar
  2. 2.
    Asif S, Romberg J (2010) Dynamic updating for ℓ1 minimization. IEEE J Sel Top Signal Process 4(2):421–434CrossRefGoogle Scholar
  3. 3.
    Bradley J, Brislawn C (1994) The wavelet scalar quantization compression standard for digital fingerprint images. In: IEEE International Symposium on Circuits and Systems, 1994 (ISCAS’94), vol 3, pp 205–208Google Scholar
  4. 4.
    Byun H, Lee S (2002) Applications of support vector machines for pattern recognition: a survey. In: Pattern recognition with support vector machines, pp 571–591Google Scholar
  5. 5.
    Candes E, Tao T (2005) Decoding by linear programming. IEEE Trans Inf Theory 51(12):4203–4215CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    Cox I, Kilian J, Leighton F, Shamoon T (1997) Secure spread spectrum watermarking for multimedia. IEEE Trans Image Process 6(12):1673–1687CrossRefGoogle Scholar
  7. 7.
    Feng J, Jain A (2011) Fingerprint reconstruction: from minutiae to phase. IEEE Trans Pattern Anal Mach Intell 33(2):209–223CrossRefGoogle Scholar
  8. 8.
    Gunsel B, Uludag U, Murat Tekalp A (2002) Robust watermarking of fingerprint images. Pattern Recogn 35(12):2739–2747CrossRefzbMATHGoogle Scholar
  9. 9.
    Guo H, Georganas N (2005) Jointly verifying ownership of an image using digital watermarking. Multimedia Tools Appl 27(3):323–349CrossRefGoogle Scholar
  10. 10.
    Hämmerle-Uhl J, Raab K, Uhl A (2011) Watermarking as a means to enhance biometric systems: a critical survey. In: Information hiding. Springer, pp 238–254Google Scholar
  11. 11.
    He H, Zhang J, Tai H (2011) A neighborhood characteristic based detection model for statistical fragile watermarking with localization. Multimedia Tools Appl 52(2):307–324CrossRefGoogle Scholar
  12. 12.
    Jain A, Ross A, Uludag U (2005) Biometric template security: challenges and solutions. In: Proceedings of European Signal Processing Conference (EUSIPCO), pp 469–472Google Scholar
  13. 13.
    Jain AK, Nandakumar K, Nagar A (2008) Biometric template security. EURASIP J Adv Signal ProcessGoogle Scholar
  14. 14.
    Jain AK, Uludag U (2003) Hiding biometric data. IEEE Trans Pattern Anal Mach Intell 25(11):1494–1498CrossRefGoogle Scholar
  15. 15.
    Kim W, Lee H (2009) Multimodal biometric image watermarking using two-stage integrity verification. Signal Process 89(12):2385–2399CrossRefzbMATHGoogle Scholar
  16. 16.
    Klare B, Jain A (2010) On a taxonomy of facial features. In: IEEE international conference on Biometrics: Theory Applications and Systems (BTAS), pp 1–8Google Scholar
  17. 17.
    Li C, Wang Y, Ma B, Zhang Z (2012) Multi-block dependency based fragile watermarking scheme for fingerprint images protection. Multimedia Tools Appl 1–20Google Scholar
  18. 18.
    Lin W, Horng S, Kao T, Fan P, Lee C, Pan Y (2008) An efficient watermarking method based on significant difference of wavelet coefficient quantization. IEEE Trans Multimedia 10(5):746–757CrossRefGoogle Scholar
  19. 19.
    Ma B, Li C, Wang Y, Zhang Z, Huang D (2012) Enhancing biometric security with wavelet quantization watermarking based two-stage multimodal authentication. In: Proceedings of international conference on pattern recognitionGoogle Scholar
  20. 20.
    Ma B, Li C, Wang Y, Zhang Z, Wang Y (2010) Block pyramid based adaptive quantization watermarking for multimodal biometric authentication. In: International conference on pattern recognition, 2010, pp 1277–1280Google Scholar
  21. 21.
    Maio D, Maltoni D, Cappelli R, Wayman J, Jain A (2002) FVC2002: second fingerprint verification competition. In: Proceedings of international conference on pattern recognition, vol 3, pp 811–814Google Scholar
  22. 22.
    Maiorana E, Campisi P, Neri A (2007) Multi-level signature based biometric authentication using watermarking. Proc SPIE 6579:65790JGoogle Scholar
  23. 23.
    Meerwald P, Koidl C, Uhl A (2009) Attack on watermarking method based on significant difference of wavelet coefficient quantization. IEEE Trans Multimedia 11(5):1037–1041CrossRefGoogle Scholar
  24. 24.
    Neurotechnology (2010) Verifinger software.
  25. 25.
    Noore A, Singh R, Vatsa M, Houck M (2007) Enhancing security of fingerprints through contextual biometric watermarking. Forensic Sci Int 169(2–3):188–194CrossRefGoogle Scholar
  26. 26.
    Phillips P, Flynn P, Scruggs T, Bowyer K, Chang J, Hoffman K, Marques J, Min J, Worek W (2005) Overview of the face recognition grand challenge. In: Proceedings of IEEE international conference on computer vision and pattern recognition, 2005, vol 1, pp 947–954Google Scholar
  27. 27.
    Phillips P, Moon H, Rizvi S, Rauss P (2000) The feret evaluation methodology for face-recognition algorithms. IEEE Trans Pattern Anal Mach Intell 22(10):1090–1104CrossRefGoogle Scholar
  28. 28.
    Ratha N, Connell J, Bolle R (2001) Enhancing security and privacy in biometrics-based authentication systems. IBM Syst J 40(3):614–634CrossRefGoogle Scholar
  29. 29.
    Sae-Bae N, Ahmed K, Isbister K, Memon N (2012) Biometric-rich gestures: a novel approach to authentication on multi-touch devices. In: Proceedings of the 2012 ACM annual conference on human factors in computing systems, pp 977–986Google Scholar
  30. 30.
    Schneier B (1999) The uses and abuses of biometrics. Commun ACM 42(8):136CrossRefGoogle Scholar
  31. 31.
    Schouten B, Tistarelli M, Garcia-Mateo C, Deravi F, Meints M (2008) Nineteen urgent research topics in biometrics and identity management. In: Proceedings of biometrics and identity management, pp 228–235Google Scholar
  32. 32.
    Swaminathan A, Mao Y, Wu M (2006) Robust and secure image hashing. IEEE Trans Inf Forensics Secur 1(2):215–230CrossRefGoogle Scholar
  33. 33.
    Vatavu R (2012) Small gestures go a long way: how many bits per gesture do recognizers actually need? In: Proceedings of the designing interactive systems conference. ACM, pp 328–337Google Scholar
  34. 34.
    Vatsa M, Singh R, Noore A (2005) Improving biometric recognition accuracy and robustness using dwt and svm watermarking. IEICE Electron Express 2(12):362–367CrossRefGoogle Scholar
  35. 35.
    Vatsa M, Singh R, Noore A (2009) Feature based rdwt watermarking for multimodal biometric system. Image Vis Comput 27(3):293–304CrossRefGoogle Scholar
  36. 36.
    Vatsa M, Singh R, Noore A, Houck M, Morris K (2006) Robust biometric image watermarking for fingerprint and face template protection. IEICE Electron Express 3(2):23–28CrossRefGoogle Scholar
  37. 37.
    Wang Z, Bovik A, Sheikh H, Simoncelli E (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612CrossRefGoogle Scholar
  38. 38.
    Weng L, Preneel B (2007) Attacking some perceptual image hash algorithms. In: IEEE international conference on multimedia and expo, 2007, pp 879–882Google Scholar
  39. 39.
    Wong P, Memon N (2001) Secret and public key image watermarking schemes for image authentication and ownership verification. IEEE Trans Image Process 10(10):1593–1601CrossRefzbMATHGoogle Scholar
  40. 40.
    Wright J, Yang AY, Ganesh A, Sastry SS, Ma Y (2009) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210–227CrossRefGoogle Scholar
  41. 41.
    Zhang J, Tian L, Tai H (2004) A new watermarking method based on chaotic maps. In: IEEE internationa conference on multimedia and expo, 2004, vol 2, pp 939–942Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Bin Ma
    • 1
  • Yunhong Wang
    • 1
  • Chunlei Li
    • 2
  • Zhaoxiang Zhang
    • 1
    Email author
  • Di Huang
    • 1
  1. 1.Intelligent Recognition and Image Processing Lab. (IRIP), Beijing Key Laboratory of Digital Media, School of Computer Science and EngineeringBeihang UniversityBeijingChina
  2. 2.School of Electronic and Information EngineeringZhongyuan University of TechnologyZhengzhouChina

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