On the use of spectral minutiae in high-resolution palmprint recognition

Ruifang Wang, Raymond N.J. Veldhuis, Daniel Ramos, Lieuwe Jan Spreeuwers, Julian Fierrez, H. Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
29 Downloads (Pure)

Abstract

The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89% and 14.2% are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1% and 3.05% on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae.
Original languageUndefined
Title of host publicationProceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013
Place of PublicationUSA
PublisherIEEE Computer Society
Pages1-4
Number of pages4
ISBN (Print)978-1-4673-4987-1
DOIs
Publication statusPublished - 4 Apr 2013

Publication series

Name
PublisherIEEE Computer Society

Keywords

  • METIS-297768
  • minutiae-based fingerprint recognition
  • high-resolution palmprint recognition
  • spectral minutiae based matching
  • EWI-23567
  • Nonlinear distortion
  • Statistical Analysis
  • palmprint database
  • key parameter optimization
  • location-based spectral minutiae representation
  • minutiae rotation
  • minutiae translation
  • IR-86963
  • Complex spectral minutiae representation
  • SCS-Safety

Cite this

Wang, R., Veldhuis, R. N. J., Ramos, D., Spreeuwers, L. J., Fierrez, J., & Xu, H. (2013). On the use of spectral minutiae in high-resolution palmprint recognition. In Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013 (pp. 1-4). USA: IEEE Computer Society. https://doi.org/10.1109/IWBF.2013.6547308
Wang, Ruifang ; Veldhuis, Raymond N.J. ; Ramos, Daniel ; Spreeuwers, Lieuwe Jan ; Fierrez, Julian ; Xu, H. / On the use of spectral minutiae in high-resolution palmprint recognition. Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013. USA : IEEE Computer Society, 2013. pp. 1-4
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title = "On the use of spectral minutiae in high-resolution palmprint recognition",
abstract = "The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89{\%} and 14.2{\%} are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1{\%} and 3.05{\%} on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae.",
keywords = "METIS-297768, minutiae-based fingerprint recognition, high-resolution palmprint recognition, spectral minutiae based matching, EWI-23567, Nonlinear distortion, Statistical Analysis, palmprint database, key parameter optimization, location-based spectral minutiae representation, minutiae rotation, minutiae translation, IR-86963, Complex spectral minutiae representation, SCS-Safety",
author = "Ruifang Wang and Veldhuis, {Raymond N.J.} and Daniel Ramos and Spreeuwers, {Lieuwe Jan} and Julian Fierrez and H. Xu",
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Wang, R, Veldhuis, RNJ, Ramos, D, Spreeuwers, LJ, Fierrez, J & Xu, H 2013, On the use of spectral minutiae in high-resolution palmprint recognition. in Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013. IEEE Computer Society, USA, pp. 1-4. https://doi.org/10.1109/IWBF.2013.6547308

On the use of spectral minutiae in high-resolution palmprint recognition. / Wang, Ruifang; Veldhuis, Raymond N.J.; Ramos, Daniel; Spreeuwers, Lieuwe Jan; Fierrez, Julian; Xu, H.

Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013. USA : IEEE Computer Society, 2013. p. 1-4.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AU - Veldhuis, Raymond N.J.

AU - Ramos, Daniel

AU - Spreeuwers, Lieuwe Jan

AU - Fierrez, Julian

AU - Xu, H.

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PY - 2013/4/4

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N2 - The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89% and 14.2% are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1% and 3.05% on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae.

AB - The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89% and 14.2% are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1% and 3.05% on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae.

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KW - key parameter optimization

KW - location-based spectral minutiae representation

KW - minutiae rotation

KW - minutiae translation

KW - IR-86963

KW - Complex spectral minutiae representation

KW - SCS-Safety

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DO - 10.1109/IWBF.2013.6547308

M3 - Conference contribution

SN - 978-1-4673-4987-1

SP - 1

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BT - Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013

PB - IEEE Computer Society

CY - USA

ER -

Wang R, Veldhuis RNJ, Ramos D, Spreeuwers LJ, Fierrez J, Xu H. On the use of spectral minutiae in high-resolution palmprint recognition. In Proceedings of the International Workshop on Biometrics and Forensics (IWBF), 2013. USA: IEEE Computer Society. 2013. p. 1-4 https://doi.org/10.1109/IWBF.2013.6547308