Skip to main content

Advertisement

Log in

Multimodal biometric cryptosystem for human authentication using fingerprint and ear

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

The multimodal biometrics is mainly used for the purpose of person certification and proof. Lot of biometrics is used for human authentication. In which ear and fingerprint are efficient one. There are three vital phases involved in the biometric detection which include the Preprocessing, Feature extraction and the classification. Initially, preprocessing is done with the help of median filter which lends a helping hand to the task of cropping the image for choosing the position. Then, from the preprocessed Finger print and ear image texture and shape features are extracted. In the long run, the extracted features are integrated. The integrated features, in turn, are proficiently classified by means of the optimal neural network (ONN). Here, the NN weights are optimally, selected with the help of firefly algorithm (FF). The biometric image is classified into fingerprint and ear if the identical person images are amassed in one group and the uneven images are stored in a different group. The performance of the proposed approach is analyzed in terms of evaluation metrics.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Ahmad M1, Woo WL, Dlay SS (2010) Multimodal biometric fusion at feature level: face and palm print. In: Proc. of the 7th international symposium on communication systems networks and digital signal processing (CSNDSP), pp 801–805

  2. Basha AJ, Palanisamy V, Purusothaman T (2010) Fast multimodal biometric approach using dynamic fingerprint authentication and enhanced Iris features. In: Proc. of the IEEE international conference on computational intelligence and computing research (ICCIC), 2010, pp 1–6

  3. Chan T-S, Kumar A (2012) Reliable ear identification using 2-D quadrature filters. Pattern Recogn Lett 33(14):1870–1881

    Article  Google Scholar 

  4. Chin YJ, Ong TS, Teoh ABJ, Goh MKO (2011) Multimodal biometrics based bit extraction method for template security. In: Proc. 6th IEEE conference on industrial electronics and applications (ICIEA), pp 1971–1976

  5. Choi H, Shin M (2009) Learning radial basis function model with matching score quality for person authentication in multimodal biometrics. In: Proc. of first Asian IEEE conference on intelligent information and database systems, pp 346–350

  6. Dahel SK, Xiao Q (2003) Accuracy performance analysis of multimodal biometrics. In: Proc. of the IEEE workshop on information assurance, pp 170–173

  7. Hanmandlu M, Grover J, Gureja A, Gupta HM (2011) Score level fusion of multimodal biometrics using triangular norms. Pattern Recogn Lett 32(14):1843–1850

    Article  Google Scholar 

  8. He M, Horng S-J, Fan P, Run R-S, Chen R-J, Lai J-L, Khan MK, Sentosa KO (2010) Performance evaluation of score level fusion in multimodal biometric systems. Pattern Recogn 43(5):1789–1800

    Article  Google Scholar 

  9. Huang H, Liu J, Feng H, He T (2011) Ear recognition based on uncorrelated local fisher discriminant analysis. Neuro Computing 74(17):3103–3113

    Google Scholar 

  10. Huang Z, Liu Y, Li C, Yang M, Chen L (2013) A robust face and ear based multimodal biometric system using sparse representation. Pattern Recogn 46(8):2156–2168

    Article  Google Scholar 

  11. Ichino M, Sakano H, Komatsu N (2006) Multimodal biometrics of lip movements and voice using kernel fisher discriminant analysis. In: Proc. of the 9th international conference on control, automation, robotics and vision (ICARCV '06), pp 1–6

  12. Islam SMS, Davies R, Bennamoun M, Owens RA, Mian AS (2013) Multibiometric human recognition using 3D ear and face features. Pattern Recogn 46(3):613–627

    Article  Google Scholar 

  13. Khan MK, Zhang J (2008) Multimodal face and fingerprint biometrics authentication on space-limited tokens. Neuro Computing 17(12):3026–3031

    Google Scholar 

  14. Kumar A, Chan T-ST (2013) Robust ear identification using sparse representation of local texture descriptors. Pattern Recogn 46(1):73–85

    Article  Google Scholar 

  15. Madhavi, Jain AK, Flynn P, Ross AA (2007) Handbook of biometrics. Springer

  16. Maple C, Schetinin V (2006) Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics. In: Proc. of the first IEEE international conference on availability, reliability and security, pp 929–935

  17. Monwar MM, Gavrilova ML (2009) Multimodal biometric system using rank-level fusion approach. IEEE Transactions on Systems, Man and Cybernetics 39(4):867–878

    Article  Google Scholar 

  18. Pflug A, Busch C (2012) Ear biometrics: a survey of detection, feature extraction and recognition methods. IET biometrics 1(2):114–129

    Article  Google Scholar 

  19. Raghavendra R, Imran M, Rao A, Hemantha Kumar G (2010) Multimodal biometrics: analysis of Handvein & Palmprint Combination Used for person verification. In: Proc. of third IEEE international conference on emerging trends in engineering and technology, pp 526–530

  20. Rahman MM, Islam MR, Bhuiyan NI, Ahmed B, Islam MA (2007) Person identification using ear biometrics. International Journal of The Computer, the Internet and Management 15(2):1–8

    Google Scholar 

  21. Ross A, Abaza A (2011) Human ear recognition. IEEE Computer Magazine 44(11):718–737

    Article  Google Scholar 

  22. Ross A, Jain AK (2004) Multimodal biometrics: an overview. In: Proc. of 12th European signal processing conference (EUSIPCO), vol 14, no 1, pp 1221–1224

  23. Seal DB, Nasipuri M, Basu DK (2011) Minutiae based thermal face recognition using blood perfusion data. In: 2011 International Conference on Image Information Processing, Shimla, pp 1–4

  24. Semwal VB, Raj M, Nandi GC (2014) Multilayer perceptron based biometric GAIT identification. Robot Auton Syst

  25. Semwal VB, Singha J, Sharma PK, Chauhan A, Behera B (2017) An optimized feature selection technique based on incremental feature analysis for bio-metric gait data classification. Multimed Tools Appl 76(22):24457–24475

    Article  Google Scholar 

  26. Semwal VB, Gaud N, Nandi GC (2019) Human gait state prediction using cellular automata and classification using ELM. In: Machine intelligence and signal analysis. Springer, Singapore, pp 135–145

    Google Scholar 

  27. Yang JC (2010) Biometrics verification techniques combing with digital signature for multimodal biometrics payment system. In: Proc. of IEEE international conference on management of e-commerce and e-government, pp 405–410

  28. Yaoa Y-F, Jing X-Y, Wong H-S (2007) Face and palm print feature level fusion for single sample biometrics recognition. Neuro Computing 9(8)

  29. Yuan L, Mu Z c (2012) Ear recognition based on local information fusion. Pattern Recogn Lett 33(2):182–190

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Padira S. V. V. N. Chanukya.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chanukya, P.S.V.V.N., Thivakaran, T.K. Multimodal biometric cryptosystem for human authentication using fingerprint and ear. Multimed Tools Appl 79, 659–673 (2020). https://doi.org/10.1007/s11042-019-08123-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-08123-w

Keywords

Navigation