Skip to main content

A Finger-vein Biometric System Based on Textural Features

  • Conference paper
  • First Online:
Proceedings of the International Conference on Information Technology & Systems (ICITS 2018) (ICITS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 721))

Included in the following conference series:

Abstract

Biometric systems are being widely used today for automated authentication purposes. In particular, vascular biometrics or vein recognition is receiving a large amount of attention because of its several advantages related to security and convenience. However, images containing vein patterns normally include more information than just those structural arrangements. Thus, we propose a finger-vein biometric system based exclusively on textural features to evaluate the usefulness of the remaining information around vein patters. Textural features are obtained through gray-level co-occurrence matrices from the wavelet detail coefficients belonging to finger-vein images. The evaluation of the proposed biometric system is based on a standardized finger-vein database and its results show favorable improvements on the finger-vein authentication accuracy when textural features are incorporated in the biometric process.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Kaur, G., Singh, G., Kumar, V.: A review on biometric recognition. Int. J. BioSci. BioTechnol. 6, 69–76 (2014)

    Google Scholar 

  2. Wang, P., Sun, D.: A research on palm vein recognition. In: 2016 IEEE 13th International Conference on Signal Processing (ICSP), pp. 1347–1351. IEEE (2016)

    Google Scholar 

  3. Syazana-Itqan, K., Syafeeza, A., Saad, N., Hamid, N.A., Saad, W.H.B.M.: A review of finger-vein biometrics identification approaches. Indian J. Sci. Technol, 9 (2016)

    Google Scholar 

  4. Yang, L., Yang, G., Yin, Y., Xi, X.: Finger vein recognition with anatomy structure analysis. IEEE Transactions on Circuits and Systems for Video Technology (2017)

    Google Scholar 

  5. Cheng, Y.C., Chen, H., Cheng, B.C.: Special point representations for reducing data space requirements of finger-vein recognition applications. Multimedia Tools Appl. 76, 11251–11271 (2017)

    Article  Google Scholar 

  6. Bansal, K., Kaur, S.: Finger vein recognition using minutiae extraction and curve analysis. Int. J. Sci. Res. 4, 2402–2405 (2015)

    Google Scholar 

  7. Beura, S., Majhi, B., Dash, R.: Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer. Neurocomputing 154, 1–14 (2015)

    Article  Google Scholar 

  8. Etehadtavakol, M., Ng, E., Chandran, V., Rabbani, H.: Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms. Infrared Phys. Technol. 61, 274–286 (2013)

    Article  Google Scholar 

  9. Yin, Y., Liu, L., Sun, X.: SDUMLA-HMT: a multimodal biometric database. In: Sun, Z., Lai, J., Chen, X., Tan, T. (eds.) CCBR 2011. LNCS, vol. 7098, pp. 260–268. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25449-9_33

    Chapter  Google Scholar 

  10. Modi, S.K.: Biometrics in identity management: concepts to applications. Artech House, Massachusetts (2011)

    Google Scholar 

  11. Chen, C.H.: Handbook of pattern recognition and computer vision. World Scientific, New Jersey (2015)

    Google Scholar 

  12. Marsland, S.: Machine learning: an algorithmic perspective. CRC Press, Florida (2015)

    Google Scholar 

  13. Trabelsi, R.B., Masmoudi, A.D., Masmoudi, D.S.: A new multimodal biometric system based on finger vein and hand vein recognition. Int. J. Eng. Technol. 4, 3175 (2013)

    Google Scholar 

  14. Lu, Y., Yoon, S., Park, D.S.: Finger vein recognition based on matching score-level fusion of Gabor features. J. Korean Inst. Commun. Inf. Sci. 38, 174–182 (2013)

    Google Scholar 

  15. Lu, Y., Xie, S.J., Yoon, S., Park, D.S.: Finger vein identification using polydirectional local line binary pattern. In: 2013 International Conference on ICT Convergence (ICTC), pp. 61–65. IEEE (2013)

    Google Scholar 

Download references

Acknowledgment

This work was partially supported by the Universidad de las Fuerzas Armadas ESPE under Research Grant 2015-PIC-004.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Enrique V. Carrera .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Carrera, E.V., Izurieta, S., Carrera, R. (2018). A Finger-vein Biometric System Based on Textural Features. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73450-7_35

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73449-1

  • Online ISBN: 978-3-319-73450-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics