Quality Estimation for Vascular Pattern Recognition

Daniel Hartung, Sophie Martin, Christoph Busch

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    The quality of captured samples is a critical aspect in biometric systems. In this paper we present a quality estimation algorithm for vascular images, which uses global and local features based on a Grey Level Co-Occurrence Matrix (GLCM) and optionally available metadata. An evaluation of the algorithm using different processing methods and vein sample databases shows convincing results: disregarding low estimated quality sample images helps to increase the performance. Moreover, metadata gives accurate indications on sample quality. The algorithm works on low level raw images, it is fast and therefore qualified to be used in feedback mode during enrolment or verification operation.
    Original languageEnglish
    Title of host publication2011 International Conference on Hand-Based Biometrics (ICHB)
    PublisherIEEE
    Publication date2011
    ISBN (Print)978-1-4577-0491-8
    ISBN (Electronic)978-1-4577-0489-5
    DOIs
    Publication statusPublished - 2011
    EventInternational Conference on Hand-Based Biometrics - Hong Kong, China
    Duration: 1 Jan 2011 → …

    Conference

    ConferenceInternational Conference on Hand-Based Biometrics
    CityHong Kong, China
    Period01/01/2011 → …

    Cite this

    Hartung, D., Martin, S., & Busch, C. (2011). Quality Estimation for Vascular Pattern Recognition. In 2011 International Conference on Hand-Based Biometrics (ICHB) IEEE. https://doi.org/10.1109/ICHB.2011.6094332