Skip to main content
SpringerLink
Log in
Book cover

5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011) pp 117–124Cite as

An Enhancement of the Usage of the Poincare Index for the Detection and Classification of Characteristic Points in Dactylograms

  • Conference paper

  • 822 Accesses

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 93))

Abstract

In order to identify subjects in a convenient and efficient way one must use some special feature that makes it possible to discriminate between persons. Some of the features are biometric in nature, such as iris texture, hand shape, the human face, and of course finger prints. These play an important role in many automatic identification systems, since every person is believed to have a unique set of fingerprints. Before a fingerprint image can be looked up in a database, it has to be classified into one of 5 types in order to reduce processing times.

This is a preview of subscription content, 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 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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Karu, K., Jain, A.K.: Fingerprint Classification, A Technical Report from Michigan State University (1995)

    Google Scholar 

  2. Henry, E.R.: Classification and uses of fingerprints. George Routledge and Sons, London (1900)

    Google Scholar 

  3. Miller, B.: Vital signs of identity. IEEE Spectrum 31(2), 22–30 (1994)

    Article  Google Scholar 

  4. Srinivasan, V.S., Murthy, N.N.: Detection of Singular Points in Fingerprint Images. Pattern Recognition 25(2), 139–153 (1992)

    Article  Google Scholar 

  5. Watson, C.I., Wilson, C.L.: NIST Special Database 4. Fingerprint Database. National Institute of Standard and Technology (March 1992)

    Google Scholar 

  6. Watson, C.I.: NIST Special Database 9: Mated Fingerprint Card Pairs. National Institute of standard and Technology (February 1993)

    Google Scholar 

  7. Rao, A.R.: A Taxonomy for Texture Description and Identification. Springer, New York (1990)

    MATH  Google Scholar 

  8. Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: Algorithm and performance evaluation. IEEE Trans. Pattern Anal. Machine Intell. 20, 777–789 (1998)

    Article  Google Scholar 

  9. Woods, K., Kegelmeyer, W.P., Bowyer, K.W.: Combination of Multiple Classifiers Using Local Accuracy Estimates. IEEE Trans. Pattern Analysis and Machine Intelligence 19(4), 405–410 (1997)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computers and Automation Department, University of Salamanca, Salamanca, Spain

    Angélica González & Marco A. Ameller F.

  2. Computers Engineering Department, Autonomous University Tomas Frias, Potosí, Bolivia, Spain

    Marco A. Ameller F.

Authors
  1. Angélica González
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marco A. Ameller F.
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dep. Informática / CCTC, Universidade do Minho, 4710 - 057, Braga, Portugal

    Miguel P. Rocha

  2. Department of Computing Science and Control Faculty of Science, University of Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Juan M. Corchado Rodríguez

  3. Edificio Politécnico, ESEI: Escuela Superior de Ingeniería Informática, 32004, Ourense, Spain

    Florentino Fdez-Riverola

  4. Structural Biology and BioComputing Programme (CNIO), Spanish National Cancer Research Centre, Melchor Fdez Almagro 3, 28029, Madrid, Spain

    Alfonso Valencia

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

González, A., Ameller F., M.A. (2011). An Enhancement of the Usage of the Poincare Index for the Detection and Classification of Characteristic Points in Dactylograms. In: Rocha, M.P., Rodríguez, J.M.C., Fdez-Riverola, F., Valencia, A. (eds) 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011). Advances in Intelligent and Soft Computing, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19914-1_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19914-1_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19913-4

  • Online ISBN: 978-3-642-19914-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation