Damer, Naser ; Terhörst, Philipp ; Braun, Andreas ; Kuijper, Arjan (2018)
Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval.
International Conference on Information Fusion (FUSION). Cambridge, UK (10.07.2018-13.07.2018)
doi: 10.23919/ICIF.2018.8455390
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Indexing of multi-biometric data is required to facilitatefast search in large-scale biometric systems. Previous worksaddressing this issue in multi-biometric databases focused onmulti-instance indexing, mainly iris data. Few works addressedthe indexing in multi-modal databases, with basic candidate listfusion solutions limited to joining face and fingerprint data. Irisand fingerprint are widely used in large-scale biometric systemswhere fast retrieval is a significant issue. This work proposes jointmulti-biometric retrieval solution based on fingerprint and irisdata. This solution is evaluated under eight different candidatelist fusion approaches with variable complexity on a databaseof 10,000 reference and probe records of irises and fingerprints.Our proposed multi-biometric retrieval of fingerprint and irisdata 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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Damer, Naser ; Terhörst, Philipp ; Braun, Andreas ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval |
| Sprache: | Englisch |
| Publikationsjahr: | 2018 |
| Ort: | Los Alamitos |
| Verlag: | IEEE |
| Buchtitel: | 2018 21st International Conference on Information Fusion (FUSION) |
| Veranstaltungstitel: | International Conference on Information Fusion (FUSION) |
| Veranstaltungsort: | Cambridge, UK |
| Veranstaltungsdatum: | 10.07.2018-13.07.2018 |
| DOI: | 10.23919/ICIF.2018.8455390 |
| URL / URN: | https://doi.org/10.23919/ICIF.2018.8455390 |
| Kurzbeschreibung (Abstract): | Indexing of multi-biometric data is required to facilitatefast search in large-scale biometric systems. Previous worksaddressing this issue in multi-biometric databases focused onmulti-instance indexing, mainly iris data. Few works addressedthe indexing in multi-modal databases, with basic candidate listfusion solutions limited to joining face and fingerprint data. Irisand fingerprint are widely used in large-scale biometric systemswhere fast retrieval is a significant issue. This work proposes jointmulti-biometric retrieval solution based on fingerprint and irisdata. This solution is evaluated under eight different candidatelist fusion approaches with variable complexity on a databaseof 10,000 reference and probe records of irises and fingerprints.Our proposed multi-biometric retrieval of fingerprint and irisdata 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. |
| Freie Schlagworte: | Biometrics, Multibiometrics, Indexing |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 26 Jun 2019 11:47 |
| Letzte Änderung: | 03 Jul 2024 10:42 |
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