Fingerprint and iris multi-biometric data indexing and retrieval

AutorDamer, Naser; Terhörst, Philipp; Braun, Andreas; Kuijper, Arjan
ArtConference Paper
AbstraktIndexing of multi-biometric data is required to facilitate fast search in large-scale biometric systems. Previous works addressing this issue in multi-biometric databases focused on multi-instance indexing, mainly iris data. Few works addressed the indexing in multi-modal databases, with basic candidate list fusion solutions limited to joining face and fingerprint data. Iris and fingerprint are widely used in large-scale biometric systems where fast retrieval is a significant issue. This work proposes joint multi-biometric retrieval solution based on fingerprint and iris data. This solution is evaluated under eight different candidate list fusion approaches with variable complexity on a database of 10,000 reference and probe records of irises and fingerprints. Our proposed multi-biometric retrieval of fingerprint and iris data resulted in a reduction of the miss rate (1- hit rate) at 0.1%penetration rate by 93% compared to fingerprint indexing and88% compared to iris indexing.
KonferenzInternational Conference on Information Fusion (FUSION) <21, 2018, Cambridge>
ProjektBundes­ministerium für Bildung und Forschung BMBF/
ReferenzInstitute of Electrical and Electronics Engineers -IEEE-: 21st International Conference on Information Fusion, FUSION 2018: 10-13 July 2018, Cambridge, United Kingdom. Piscataway, NJ: IEEE, 2018, pp. 2083-2090
SchlüsselISBN : 9780996452762