Fingerprint and Iris Multi-Biometric Data Indexing and Retrieval

Abstract

Indexing 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 and 88% compared to iris indexing.