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)
    32 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
    @inproceedings{0c4011292db842338b593072061b5c8a,
    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",
    note = "10.1109/IWBF.2013.6547308",
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    doi = "10.1109/IWBF.2013.6547308",
    language = "Undefined",
    isbn = "978-1-4673-4987-1",
    publisher = "IEEE Computer Society",
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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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    T1 - On the use of spectral minutiae in high-resolution palmprint recognition

    AU - Wang, Ruifang

    AU - Veldhuis, Raymond N.J.

    AU - Ramos, Daniel

    AU - Spreeuwers, Lieuwe Jan

    AU - Fierrez, Julian

    AU - Xu, H.

    N1 - 10.1109/IWBF.2013.6547308

    PY - 2013/4/4

    Y1 - 2013/4/4

    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 - minutiae-based fingerprint recognition

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    KW - Statistical Analysis

    KW - palmprint database

    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

    U2 - 10.1109/IWBF.2013.6547308

    DO - 10.1109/IWBF.2013.6547308

    M3 - Conference contribution

    SN - 978-1-4673-4987-1

    SP - 1

    EP - 4

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

    PB - IEEE Computer Society

    CY - USA

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    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