Skip to main content
SpringerLink
Log in

Multi-Algorithm Decision-Level Fusion Using Finger-Knuckle-Print Biometric

  • Conference paper
  • First Online:
Emerging Research in Electronics, Computer Science and Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 248))

Abstract

This paper proposed the use of multi-algorithm feature-level fusion as a means to improve the performance of finger-knuckle-print (FKP) verification. LG, LPQ, PCA, and LPP have been used to extract the FKP features. Experiments are performed using the FKP database, which consists of 7,920 images. Results indicate that the multi-algorithm verification approach outperforms higher performance than using any single algorithm. The biometric performance using feature-level fusions under different normalization techniques as well has been demonstrated in this paper.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Ville Ojansivu and Janne Heikkilä. “Blur Insensitive Texture Classification Using Local Phase Quantization”. Proceedings of the 3rd International Conference on Image and Signal Processing (ICISP) 2008, LNCS 5099, pp. 236–243 Springer-Verlag Berlin, Heidelberg 2008

    Google Scholar 

  2. Abhilash Bhargav-Spantzel, Anna C. Squicciarini, Shimon Modi, Matthew Young, Elisa Bertino, and Stephen J. Elliott. “Privacy Preserving Multi-Factor Authentication with Biometrics”. journal of computer security (1875-8924) volume 15, Number 5/2007

    Google Scholar 

  3. J. Stan Z. Li, Anil K. Jain. “Encyclopedia of Biometrics”. Springer

    Google Scholar 

  4. Markus Turtinen, Topi Mäenpää, and Matti Pietikäinen. “Texture Classification by Combining Local Binary Pattern Features and a Self-Organizing Map”. Proceeding SCIA’03 Proceedings of the 13th Scandinavian conference on Image analysis Springer-Verlag, Berlin, Heidelberg  2003

    Google Scholar 

  5. Julian Fierrez-Aguilar, Yi Chen, Javier Ortega-Garcia, and Anil K. Jain. “Incorporating Image Quality in Multi-Algorithm Fingerprint verification”. ICB’06 Proceedings of the 2006 international conference on Advances in Biometrics

    Google Scholar 

  6. Seyed Mehdi Lajevardi, Zahir M. Hussain. “Facial Expression Recognition Using Log-Gabor Filters and Local Binary Pattern Operators”. International Conference on Communication, Computer and Power (ICCCP’09) Muscat, February 15-18, 2009

    Google Scholar 

  7. Harbi AlMahafzah, Mohammad Imran, and H.S. Sheshadri. “Multibiometric: Feature Level Fusion Using FKP Multi-Instance biometric”. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 3, July 2012

    Google Scholar 

  8. Hussian Dawood, Hassan Dawood and Ping GUO. “Combining the Contrast Information with LPQ for Texture Classification”. Science of Electronics, Technologies of Information and Telecommunications (SETIT) Sousse 21-24 March 2012-Tunisia

    Google Scholar 

  9. Xiaoyang Tan and Bill Triggs. “Fusing Gabor and LBP Feature Sets for Kernel-based Face Recognition”. 3rd International Workshop Analysis and Modeling of Faces and Gestures (AMFG ‘07) 4778 (2007) 235--249

    Google Scholar 

  10. Zhang Lin, Zhang Lei, Zhang David, Zhu Hailong (2011) Ensemble of local and global information for finger–knuckle-print recognition. Elseveir/Pattern Recognition 44:1990–1998

    Article  Google Scholar 

  11. D.J. Field. “Relation between the statistics of natural images and the response properties of cortical cells”. J. Opt. Soc. Am. A, 4(12):2379_2394, 1987

    Google Scholar 

  12. Xiaofei He Partha Niyogi “Locality Preserving Projections (LPP)”. Advances in Neural Information Processing Systems 16 (NIPS), Vancouver, Canada, 2003

    Google Scholar 

  13. A. Ross, K.Nandakumar, and A.K. Jain. “Handbook of multibiometrics”. Springer-Verlag edition, 2006

    Google Scholar 

  14. John Daugman. “Biometric decision landscapes”. Technical Report UCAM-CL-TR-482 ISSN 1476-2986 Number 482 January 2000

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. P.E.T. Foundation Research, University of Mysore, Mandya, India

    Harbi AlMahafzah

  2. Department E & C Engg, P.E.S College of Engineering, V.T.U,Mandya, India

    H. S. Sheshadri

  3. Department of Study in Computer Science, University of Mysore, Mysore, India

    Mohammad Imran

Authors
  1. Harbi AlMahafzah
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. S. Sheshadri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Imran
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Harbi AlMahafzah .

Editor information

Editors and Affiliations

  1. Department of E & C Engineering, PES College of Engineering, Mandya, Karnataka, India

    V Sridhar

  2. Department of E & C Engineering, PES College of Engineering, Mandya, Karnataka, India

    Holalu Seenappa Sheshadri

  3. Department of Computer Science, PES College of Engineering, Mandya, Karnataka, India

    M C Padma

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer India

About this paper

Cite this paper

AlMahafzah, H., Sheshadri, H.S., Imran, M. (2014). Multi-Algorithm Decision-Level Fusion Using Finger-Knuckle-Print Biometric. In: Sridhar, V., Sheshadri, H., Padma, M. (eds) Emerging Research in Electronics, Computer Science and Technology. Lecture Notes in Electrical Engineering, vol 248. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1157-0_5

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1157-0_5

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1156-3

  • Online ISBN: 978-81-322-1157-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation