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Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval

Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan (2018):
Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval.
In: 2018 21st International Conference on Information Fusion (FUSION), Los Alamitos, IEEE, In: International Conference on Information Fusion (FUSION), Cambridge, UK, 2018, DOI: 10.23919/ICIF.2018.8455390,
[Online-Edition: https://doi.org/10.23919/ICIF.2018.8455390],
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Damer, Naser and Terhorst, Philipp and Braun, Andreas and Kuijper, Arjan
Title: Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval
Language: English
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.

Title of Book: 2018 21st International Conference on Information Fusion (FUSION)
Place of Publication: Los Alamitos
Publisher: IEEE
Uncontrolled Keywords: Biometrics, Multibiometrics, Indexing
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: International Conference on Information Fusion (FUSION)
Event Location: Cambridge, UK
Event Dates: 2018
Date Deposited: 26 Jun 2019 11:47
DOI: 10.23919/ICIF.2018.8455390
Official URL: https://doi.org/10.23919/ICIF.2018.8455390
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